{ "schemaVersion": "deck-intelligence.v1", "id": "019dd923-5e88-73ef-bd5c-b1fd37abc6e1", "slug": "3c200098b4db2724", "title": "2025 Agentic AI on the Rise Keys to Unlocking Value", "subtitle": "AWS", "author": "AWS", "pageCount": 19, "kind": "consulting-deck", "orientation": "landscape", "aspectRatio": 1.294, "document": { "id": "019dd923-5e88-73ef-bd5c-b1fd37abc6e1", "slug": "3c200098b4db2724", "title": "2025 Agentic AI on the Rise Keys to Unlocking Value", "rawTitle": "2025 Agentic AI on the Rise Keys to Unlocking Value", "authorId": "AWS", "authorName": "AWS", "authorDisplay": "AWS", "kind": { "slug": "consulting-deck", "label": "Consulting deck" }, "sourceType": { "slug": "vendor_thought_leadership", "label": "Vendor thought leadership" }, "fileName": "2025-Agentic-AI-on-the-Rise-Keys-to-Unlocking-Value.pdf", "sourceUrl": null, "sourceDate": "2025-08-01 00:00:00", "presentationDate": null, "ingestedAt": "2026-04-25 11:55:48+00", "status": "ready", "pageCount": 19, "orientation": "landscape", "aspectRatio": 1.294, "targetCompany": null, "targetTicker": null, "metadata": { "local_root": "/tmp/legacy-images/3c200098b4db2724", "origin_corpus": "consulting" } }, "coverage": { "pageCount": 19, "pagesIndexed": 19, "pagesWithImages": 19, "pagesWithMetadata": 19, "imageCoveragePct": 100, "metadataCoveragePct": 100, "componentCount": 105, "chartCount": 1, "metricSlides": 0, "toolMatches": 49, "documentToolMatches": 0, "frameworkMatches": 8, "arcMatches": 2, "beatMatches": 9, "loopMatches": 4, "patternMatches": 0, "storymakersMatch": true, "scoreAvailable": true, "reviewAvailable": true, "activistThesisAvailable": false, "pitchdeckMetadataAvailable": false, "pitchdeckProfileAvailable": false }, "blocks": [], "matches": { "arcs": [ { "arc": { "name": "AIDA", "slug": "aida", "status": "active", "bestFor": "Marketing presentations, product launches, sales enablement", "canonId": "019dd956-5fb4-77aa-866d-f9bdd47803af", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Attention -> Interest -> Desire -> Action", "description": null, "familyLabel": null, "categoryName": "Strategy & Business", "categorySlug": "strategy-business" }, "matchId": "019de067-2d91-7264-a72e-b60277f83dc2", "evidence": "Vendor eBook moves from cover/definitions (p1-3) to market interest (p4-7) to use cases + AWS stack (p8-17) to Marketplace CTA (p18-19).", "isPrimary": true, "confidence": 72, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null } }, { "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null, "categoryName": "Strategy & Business", "categorySlug": "strategy-business" }, "matchId": "019de067-2e65-73ce-8e5b-7d2ab9a39fa9", "evidence": "Loose fit: context p3-7, implicit complication p7/p9, AWS solution p11-15, proof p8-10, CTA p18-19; evidence/solution order is inverted vs canonical.", "isPrimary": false, "confidence": 48, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null } } ], "beats": [ { "to": 3, "arc": { "name": "AIDA", "slug": "aida", "status": "active", "bestFor": "Marketing presentations, product launches, sales enablement", "canonId": "019dd956-5fb4-77aa-866d-f9bdd47803af", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Attention -> Interest -> Desire -> Action", "description": null, "familyLabel": null, "categoryName": "Strategy & Business", "categorySlug": "strategy-business" }, "from": 1, "name": "Attention", "beatId": "019de067-2dbb-716b-9743-5aade551d0f4", "matchId": "019de067-2d91-7264-a72e-b60277f83dc2", "beatType": null, "evidence": "cover, TOC and intro frame the topic", "position": 1, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 72 }, { "to": 7, "arc": { "name": "AIDA", "slug": "aida", "status": "active", "bestFor": "Marketing presentations, product launches, sales enablement", "canonId": "019dd956-5fb4-77aa-866d-f9bdd47803af", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Attention -> Interest -> Desire -> Action", "description": null, "familyLabel": null, "categoryName": "Strategy & Business", "categorySlug": "strategy-business" }, "from": 4, "name": "Interest", "beatId": "019de067-2de5-70c8-806f-d7d7abb7ab0f", "matchId": "019de067-2d91-7264-a72e-b60277f83dc2", "beatType": null, "evidence": "maturity baseline, definitions, IDC adoption curve", "position": 2, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 72 }, { "to": 17, "arc": { "name": "AIDA", "slug": "aida", "status": "active", "bestFor": "Marketing presentations, product launches, sales enablement", "canonId": "019dd956-5fb4-77aa-866d-f9bdd47803af", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Attention -> Interest -> Desire -> Action", "description": null, "familyLabel": null, "categoryName": "Strategy & Business", "categorySlug": "strategy-business" }, "from": 8, "name": "Desire", "beatId": "019de067-2e0e-73a0-a9c0-e2dabafb5391", "matchId": "019de067-2d91-7264-a72e-b60277f83dc2", "beatType": null, "evidence": "case studies, industries, AWS services, AgentCore stack", "position": 3, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 72 }, { "to": 19, "arc": { "name": "AIDA", "slug": "aida", "status": "active", "bestFor": "Marketing presentations, product launches, sales enablement", "canonId": "019dd956-5fb4-77aa-866d-f9bdd47803af", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Attention -> Interest -> Desire -> Action", "description": null, "familyLabel": null, "categoryName": "Strategy & Business", "categorySlug": "strategy-business" }, "from": 18, "name": "Action", "beatId": "019de067-2e3b-713c-b0d7-a0b5435c3588", "matchId": "019de067-2d91-7264-a72e-b60277f83dc2", "beatType": null, "evidence": "Marketplace value prop and conclusion CTAs", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 72 }, { "to": 7, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null, "categoryName": "Strategy & Business", "categorySlug": "strategy-business" }, "from": 3, "name": "Situation & Context", "beatId": "019de067-2e91-718c-ad8f-08210928f992", "matchId": "019de067-2e65-73ce-8e5b-7d2ab9a39fa9", "beatType": null, "evidence": "definitions, baseline, market trajectory", "position": 1, "isPrimaryArc": false, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 48 }, { "to": 9, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null, "categoryName": "Strategy & Business", "categorySlug": "strategy-business" }, "from": 9, "name": "Problem & Complication", "beatId": "019de067-2eb9-76ff-93b5-9b6d0c143e1b", "matchId": "019de067-2e65-73ce-8e5b-7d2ab9a39fa9", "beatType": null, "evidence": "data-rich industries face challenges agentic AI solves", "position": 2, "isPrimaryArc": false, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 48 }, { "to": 15, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null, "categoryName": "Strategy & Business", "categorySlug": "strategy-business" }, "from": 11, "name": "Solution & Approach", "beatId": "019de067-2ee2-737f-92ef-11630c0cfd36", "matchId": "019de067-2e65-73ce-8e5b-7d2ab9a39fa9", "beatType": null, "evidence": "Choose path, AgentCore, OSS frameworks, MCP", "position": 3, "isPrimaryArc": false, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 48 }, { "to": 10, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null, "categoryName": "Strategy & Business", "categorySlug": "strategy-business" }, "from": 8, "name": "Evidence & Proof", "beatId": "019de067-2f0b-75a8-a4c5-7bf47096cd46", "matchId": "019de067-2e65-73ce-8e5b-7d2ab9a39fa9", "beatType": null, "evidence": "real-world AWS Bedrock customer case studies", "position": 4, "isPrimaryArc": false, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 48 }, { "to": 19, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null, "categoryName": "Strategy & Business", "categorySlug": "strategy-business" }, "from": 18, "name": "Impact & Next Steps", "beatId": "019de067-2f70-72a7-86fa-6ab4de4ac5bb", "matchId": "019de067-2e65-73ce-8e5b-7d2ab9a39fa9", "beatType": null, "evidence": "Marketplace value prop and CTA links", "position": 5, "isPrimaryArc": false, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 48 } ], "loops": [ { "to": 7, "from": 3, "loop": { "name": "06_zoom_in", "slug": "06-zoom-in", "status": "active", "bestFor": "Technical deep-dives, case studies, detailed analysis", "canonId": "019dd956-6846-74db-82be-dff5b058b072", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Big Picture -> Key Area of Focus -> Specific Detail -> Implication", "description": "Start broad, then progressively focus on specific details that prove your point", "familyLabel": null, "categoryName": "Analysis", "categorySlug": "analysis" }, "matchId": "019de067-2f9a-73ab-80d7-790e58b86a2f", "evidence": "p3 big picture intro -> p4 maturity focus -> p5-6 specific definitions -> p7 implication via IDC adoption curve.", "position": 1, "objective": "Establish what agentic AI is and where the market is going", "confidence": 70, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null } }, { "to": 10, "from": 8, "loop": { "name": "02_pattern_hunter", "slug": "02-pattern-hunter", "status": "active", "bestFor": "Time-pressed audiences, building consensus, when data is strong", "canonId": "019dd956-6695-771a-be2e-f1748ef041a4", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion", "description": "Group multiple pieces of evidence that together point to a pattern or conclusion", "familyLabel": null, "categoryName": "Logical Reasoning", "categorySlug": "logical-reasoning" }, "matchId": "019de067-2fc3-7307-8ea6-467bf0022b73", "evidence": "Three slides stack customer cases and industry examples that converge on the pattern that agentic AI is delivering today.", "position": 2, "objective": "Show real-world adoption proves agentic AI works", "confidence": 75, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null } }, { "to": 15, "from": 11, "loop": { "name": "33_build_up", "slug": "33-build-up", "status": "active", "bestFor": "Pricing justification, cost estimation, market sizing", "canonId": "019dd956-733a-746e-88fd-04b2e4b51b61", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Base -> Add Component A -> Add Component B -> Add Component C -> The Total", "description": "Start from zero and add components to arrive at a total", "familyLabel": null, "categoryName": "Consulting Framework", "categorySlug": "consulting-framework" }, "matchId": "019de067-2fec-767b-9083-66d2218cde61", "evidence": "Base choice (p11) + AgentCore (p12) + service modules (p13) + OSS frameworks (p14) + MCP (p15) sums to full AWS offering.", "position": 3, "objective": "Build up the AWS agentic stack as a complete solution", "confidence": 72, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null } }, { "to": 18, "from": 16, "loop": { "name": "33_build_up", "slug": "33-build-up", "status": "active", "bestFor": "Pricing justification, cost estimation, market sizing", "canonId": "019dd956-733a-746e-88fd-04b2e4b51b61", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Base -> Add Component A -> Add Component B -> Add Component C -> The Total", "description": "Start from zero and add components to arrive at a total", "familyLabel": null, "categoryName": "Consulting Framework", "categorySlug": "consulting-framework" }, "matchId": "019de067-3016-7644-b28d-b82150ce5bd6", "evidence": "Catalog breadth (p16) + deployment architecture (p17) + three-pillar value prop (p18) builds Marketplace pitch.", "position": 4, "objective": "Position AWS Marketplace as the operational layer", "confidence": 65, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null } } ], "tools": [ { "tool": { "name": "The Rule of Three", "slug": "the-rule-of-three", "status": "active", "bestFor": null, "canonId": "019dd956-8962-75cf-b4f8-9394501a6f33", "version": 1, "bodyDocId": null, "description": "Ideas presented in threes are more memorable and satisfying", "familyLabel": null, "categoryName": "Block", "categorySlug": "block" }, "agent": "Storyteller", "layer": "block", "agents": [ "Storyteller" ], "matchId": "019de067-30ed-76da-a98a-aea84608c7fe", "evidence": "three maturity stages structure the slide", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 75, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 4, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "The Rule of Three", "slug": "the-rule-of-three", "status": "active", "bestFor": null, "canonId": "019dd956-8962-75cf-b4f8-9394501a6f33", "version": 1, "bodyDocId": null, "description": "Ideas presented in threes are more memorable and satisfying", "familyLabel": null, "categoryName": "Block", "categorySlug": "block" }, "agent": "Storyteller", "layer": "block", "agents": [ "Storyteller" ], "matchId": "019de067-31d2-7101-80ed-615a3fbd26c1", "evidence": "Generative AI / AI Agents / Agentic AI triad", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 80, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 5, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Social Proof", "slug": "social-proof", "status": "active", "bestFor": null, "canonId": "019dd956-990d-7620-82b3-6dd286f34568", "version": 1, "bodyDocId": null, "description": "People adapt behavior based on what others do - show adoption and testimonials", "familyLabel": null, "categoryName": "Block", "categorySlug": "block" }, "agent": "Storyteller", "layer": "block", "agents": [ "Storyteller" ], "matchId": "019de067-3408-72c1-9d04-c85883bf6664", "evidence": "three real implementation examples in healthcare and HPC given as proof", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 10, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "The Rule of Three", "slug": "the-rule-of-three", "status": "active", "bestFor": null, "canonId": "019dd956-8962-75cf-b4f8-9394501a6f33", "version": 1, "bodyDocId": null, "description": "Ideas presented in threes are more memorable and satisfying", "familyLabel": null, "categoryName": "Block", "categorySlug": "block" }, "agent": "Storyteller", "layer": "block", "agents": [ "Storyteller" ], "matchId": "019de067-34d9-7156-ad6c-8b618ef036be", "evidence": "three benefit columns: speed, flexibility, security", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 80, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 12, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "The Rule of Three", "slug": "the-rule-of-three", "status": "active", "bestFor": null, "canonId": "019dd956-8962-75cf-b4f8-9394501a6f33", "version": 1, "bodyDocId": null, "description": "Ideas presented in threes are more memorable and satisfying", "familyLabel": null, "categoryName": "Block", "categorySlug": "block" }, "agent": "Storyteller", "layer": "block", "agents": [ "Storyteller" ], "matchId": "019de067-3737-735b-bce1-6e403f6e8c3b", "evidence": "three columns: Centralized catalog, Streamlined procurement, Trusted marketplace", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 85, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 18, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Chunking", "slug": "chunking", "status": "active", "bestFor": null, "canonId": "019dd956-abab-72ce-b64c-2924cc83cf39", "version": 1, "bodyDocId": null, "description": "Information grouped into chunks is remembered better - structure content in digestible units", "familyLabel": null, "categoryName": "Loop", "categorySlug": "loop" }, "agent": "Architect", "layer": "loop", "agents": [ "Architect" ], "matchId": "019de067-31fc-77ca-a448-08cd477f19d5", "evidence": "capabilities listed as digestible bullets", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 65, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 6, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Inductive Reasoning", "slug": "inductive-reasoning", "status": "active", "bestFor": null, "canonId": "019dd956-99c6-705e-94cc-76a504c3da37", "version": 1, "bodyDocId": null, "description": "Grouping similar evidence to form a conclusion (Evidence → Pattern → Conclusion)", "familyLabel": null, "categoryName": "Loop", "categorySlug": "loop" }, "agent": "Architect", "layer": "loop", "agents": [ "Architect" ], "matchId": "019de067-32ce-7747-ac66-c7599c80b6a1", "evidence": "loop opens with first set of customer cases pointing to a pattern", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 8, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Contrast Pairs", "slug": "contrast-pairs", "status": "active", "bestFor": null, "canonId": "019dd956-9b77-70d3-88b1-f34e26f60860", "version": 1, "bodyDocId": null, "description": "Creating tension through opposites: Before↔After, Problem↔Solution, Pain↔Relief", "familyLabel": null, "categoryName": "Loop", "categorySlug": "loop" }, "agent": "Storyteller", "layer": "loop", "agents": [ "Storyteller" ], "matchId": "019de067-345a-7543-be73-83b532cd8b9e", "evidence": "two-column Agentic AI applications vs Build custom agents", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 80, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 11, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Chunking", "slug": "chunking", "status": "active", "bestFor": null, "canonId": "019dd956-abab-72ce-b64c-2924cc83cf39", "version": 1, "bodyDocId": null, "description": "Information grouped into chunks is remembered better - structure content in digestible units", "familyLabel": null, "categoryName": "Loop", "categorySlug": "loop" }, "agent": "Architect", "layer": "loop", "agents": [ "Architect" ], "matchId": "019de067-3597-7418-a324-698034fea764", "evidence": "complex platform broken into seven named modules", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 60, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 13, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Build-Up (Gradatio)", "slug": "build-up-gradatio", "status": "active", "bestFor": null, "canonId": "019dd956-a19a-73fd-9f74-c3f50dbb266d", "version": 1, "bodyDocId": null, "description": "Arranging ideas in ascending order of importance or intensity", "familyLabel": null, "categoryName": "Loop", "categorySlug": "loop" }, "agent": "Storyteller", "layer": "loop", "agents": [ "Storyteller" ], "matchId": "019de067-3667-72ac-89b1-3725ef745705", "evidence": "loop assembles Marketplace catalog, deployment, value", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 60, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 16, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Executive summary", "slug": "executive-summary", "status": "active", "bestFor": null, "canonId": "019dd9e1-4b63-72d5-9734-da757d91ca61", "version": 1, "bodyDocId": null, "description": "A condensed view of the entire argument on a single slide / block.", "familyLabel": null, "categoryName": null, "categorySlug": null }, "agent": null, "layer": "slide", "agents": null, "matchId": "d626acc6-3e89-407a-93e2-a98ef0691001", "evidence": "Understanding agentic AI", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.8, "extraction": { "at": "2026-07-16 21:56:23.292571+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 3, "whyItWorks": null, "antipattern": null, "cardinality": "common", "narrativePurpose": null }, { "tool": { "name": "Typography Hierarchy", "slug": "typography-hierarchy", "status": "active", "bestFor": null, "canonId": "019dd956-ba98-77ab-9513-ff2344da8bc7", "version": 1, "bodyDocId": null, "description": "Using font size, weight, and style to create reading order", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019de067-3041-736d-aac3-7e4c5136c83f", "evidence": "kicker label, large title, body sets reading order", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 3, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Action Titles", "slug": "action-titles", "status": "active", "bestFor": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "canonId": "019dd956-ac70-700b-a608-ba58e78f5dcc", "version": 1, "bodyDocId": "816dad3c-9983-41c1-a86e-978ebd582841", "description": "The McKinsey-bred discipline of writing every slide title as a complete declarative sentence with a verb and an insight, not a topic label. Each title is a sub-claim that ladders up to the deck's governing thought; read in sequence, the titles reconstruct the executive summary.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019de067-306d-746a-a34e-5cd835368d3b", "evidence": "callout states the so-what about baselines and alignment", "pageRefs": null, "priority": "Core", "whenToUse": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "confidence": 70, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 4, "whyItWorks": "Solves two failure modes at once. (1) The buried claim: action titles place the conclusion on the page before any analysis is read, so a busy reader doesn't reverse-engineer it from the chart. (2) The spineless deck: because each title is a claim, slides have to ladder up to the governing thought; logical gaps become visible as topic-shaped titles in a sequence that no longer reads as a story.", "antipattern": "Topic labels disguised as titles — Volume by quarter, Key findings, Pricing strategy, Margins have been impacted. No verb, or a passive verb with no agent, or a fact (Revenue grew 12%) without the so-what. Also: titles that overreach the chart's evidence, multi-claim X-grew-but-Y-fell welded titles, and mechanical repetition of the same X-drove-Y template across the deck.", "cardinality": null, "narrativePurpose": "Forces the deck to carry its argument in the title bar so a senior reader can extract the recommendation without opening a single slide; converts a binder of topics into a navigable pyramid where every slide is a node defending the apex." }, { "tool": { "name": "Gestalt Principles", "slug": "gestalt-principles", "status": "active", "bestFor": null, "canonId": "019dd956-b266-7631-9b7e-44d83bd5d4f3", "version": 1, "bodyDocId": null, "description": "Proximity, Similarity, Enclosure, Continuity, Closure, Connection - how humans perceive visual groups", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer", "Architect" ], "matchId": "019de067-30c3-77e8-8ea7-8df651d17526", "evidence": "table grid uses proximity and similarity to group rows/columns", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 80, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 4, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Maturity model", "slug": "maturity-model", "status": "active", "bestFor": null, "canonId": "019de52d-1923-75fc-9be0-131883ed3458", "version": 1, "bodyDocId": null, "description": null, "familyLabel": null, "categoryName": null, "categorySlug": null }, "agent": null, "layer": "slide", "agents": null, "matchId": "1b8dd93f-d703-44ef-bc5e-ce4c7a827f17", "evidence": "type: maturity_model, framework/instance: Maturity Model", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.9, "extraction": { "at": "2026-07-16 21:55:50.38719+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 4, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Small Multiples", "slug": "small-multiples", "status": "active", "bestFor": null, "canonId": "019dd956-b32d-7586-b368-baa1dd388ed4", "version": 1, "bodyDocId": null, "description": "Repeating similar charts for comparison across categories or time", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019de067-3098-717c-a927-d022969fff56", "evidence": "Emerging/Developing/Mature columns repeat across 6 dimensions", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 85, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 4, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Law of Similarity", "slug": "law-of-similarity", "status": "active", "bestFor": null, "canonId": "019dd956-c025-70d9-a411-8efa41ae179b", "version": 1, "bodyDocId": null, "description": "Similar-looking elements perceived as related - consistent styling for related concepts", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019de067-31aa-724c-a919-47dd67fceef1", "evidence": "three identically-styled cards mark the same level of abstraction", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 75, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 5, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "One Idea Rule", "slug": "one-idea-rule", "status": "active", "bestFor": null, "canonId": "019dd956-b0f0-7630-a2f5-bb38f9bd9c57", "version": 1, "bodyDocId": null, "description": "Each slide should communicate exactly one concept", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019de067-317f-73da-8e8c-afabaaf69fc0", "evidence": "single concept: definitional taxonomy", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 5, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Picture Superiority Effect", "slug": "picture-superiority-effect", "status": "active", "bestFor": null, "canonId": "019dd956-c201-7014-bb58-3e85e3e11dfd", "version": 1, "bodyDocId": null, "description": "Pictures remembered 6x better than words - prioritize visuals over text", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019de067-3118-7677-8fd0-f767e9f42374", "evidence": "icon-led cards anchor each definition", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 5, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "So What? Test", "slug": "so-what-test", "status": "active", "bestFor": "On every slide carrying a chart, number, list, or finding intended to inform a decision; whenever a draft title is descriptive rather than directive; whenever the deck will circulate without its author.", "canonId": "019dd956-acd2-76f8-b59a-9bf15a89f10a", "version": 1, "bodyDocId": "fec04b06-b2f1-432b-a97b-916dc7563f64", "description": "The recursive editorial discipline of asking so-what of every slide, chart, and statement until the answer is an implication for the audience — that final answer becomes the slide's title; the chain becomes its body.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019de067-3227-72ba-931a-a14e64c1a053", "evidence": "callout converts capability list into customer outcome", "pageRefs": null, "priority": "Core", "whenToUse": "On every slide carrying a chart, number, list, or finding intended to inform a decision; whenever a draft title is descriptive rather than directive; whenever the deck will circulate without its author.", "confidence": 65, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 6, "whyItWorks": "Solves the two failure modes of analytical communication at once: stopping at description (analyst-confidence problem) and leaving insight stranded in the analyst's head (translation problem). The recursion is what guarantees the implication makes it into ink.", "antipattern": "Stopping at the first tighter description (still a fact, not an implication), regressing past the audience's decision space into philosophy, smuggling the so-what into speaker notes, or re-using an implication aimed at a previous audience.", "cardinality": null, "narrativePurpose": "Forces every analytical artefact to close the gap between fact and decision, so the reader holds the recommendation by reading titles alone rather than reconstructing the analyst's mental model from raw evidence." }, { "tool": { "name": "Annotation", "slug": "annotation", "status": "active", "bestFor": null, "canonId": "019dd956-b5b9-7668-bf0e-3af99823ec5c", "version": 1, "bodyDocId": null, "description": "Adding explanatory labels to highlight key data points", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019de067-327b-77f8-b7b8-bddbc3be7120", "evidence": "stage labels and percentages annotate the curve", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 7, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Credibility Transfer", "slug": "credibility-transfer", "status": "active", "bestFor": null, "canonId": "019dd956-bd34-759a-8e3b-2f14b571a2a1", "version": 1, "bodyDocId": null, "description": "Borrowing authority from trusted sources or vivid details", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019de067-32a5-708c-897b-239456fe1f49", "evidence": "IDC source explicitly cited under chart", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 80, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 7, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Picture Superiority Effect", "slug": "picture-superiority-effect", "status": "active", "bestFor": null, "canonId": "019dd956-c201-7014-bb58-3e85e3e11dfd", "version": 1, "bodyDocId": null, "description": "Pictures remembered 6x better than words - prioritize visuals over text", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019de067-3251-71ba-a6fe-cc37d93889f6", "evidence": "IDC S-curve dominates the slide", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 75, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 7, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "SCQA Framework", "slug": "scqa-framework", "status": "active", "bestFor": null, "canonId": "019dd956-7bcb-763f-bdf6-1dfedf3bd36c", "version": 1, "bodyDocId": "019df22a-a0b0-719e-937e-2ac31e53d32c", "description": "Situation, Complication, Question, Answer - structured problem framing", "familyLabel": null, "categoryName": "Block", "categorySlug": "block" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "15ba7849-e4b0-4486-95ad-feb0806976b3", "evidence": "chart/line: Adoption curve over time", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 21:55:50.561235+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 7, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Action Titles", "slug": "action-titles", "status": "active", "bestFor": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "canonId": "019dd956-ac70-700b-a608-ba58e78f5dcc", "version": 1, "bodyDocId": "816dad3c-9983-41c1-a86e-978ebd582841", "description": "The McKinsey-bred discipline of writing every slide title as a complete declarative sentence with a verb and an insight, not a topic label. Each title is a sub-claim that ladders up to the deck's governing thought; read in sequence, the titles reconstruct the executive summary.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019de067-3321-71e9-8d33-008ec2276cbc", "evidence": "kicker frames the takeaway as real-world proof", "pageRefs": null, "priority": "Core", "whenToUse": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "confidence": 60, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 8, "whyItWorks": "Solves two failure modes at once. (1) The buried claim: action titles place the conclusion on the page before any analysis is read, so a busy reader doesn't reverse-engineer it from the chart. (2) The spineless deck: because each title is a claim, slides have to ladder up to the governing thought; logical gaps become visible as topic-shaped titles in a sequence that no longer reads as a story.", "antipattern": "Topic labels disguised as titles — Volume by quarter, Key findings, Pricing strategy, Margins have been impacted. No verb, or a passive verb with no agent, or a fact (Revenue grew 12%) without the so-what. Also: titles that overreach the chart's evidence, multi-claim X-grew-but-Y-fell welded titles, and mechanical repetition of the same X-drove-Y template across the deck.", "cardinality": null, "narrativePurpose": "Forces the deck to carry its argument in the title bar so a senior reader can extract the recommendation without opening a single slide; converts a binder of topics into a navigable pyramid where every slide is a node defending the apex." }, { "tool": { "name": "Social Validation", "slug": "social-validation", "status": "active", "bestFor": null, "canonId": "019dd956-ddaa-77f9-890c-a1cf082c5ccd", "version": 1, "bodyDocId": null, "description": "Showing others have done something, especially similar others", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019de067-32f7-727f-93c0-36189c962e45", "evidence": "names AWS customers using Bedrock Agents", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 75, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 8, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Color Strategy", "slug": "color-strategy", "status": "active", "bestFor": null, "canonId": "019dd956-b202-77cf-8a6e-f445b08c0fd3", "version": 1, "bodyDocId": null, "description": "Using color for emphasis, categories, sentiment, and hierarchy", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019de067-33b5-7374-9c77-b74d32860452", "evidence": "purple gradient on industry headers separates from white use-case rows", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 9, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Gestalt Principles", "slug": "gestalt-principles", "status": "active", "bestFor": null, "canonId": "019dd956-b266-7631-9b7e-44d83bd5d4f3", "version": 1, "bodyDocId": null, "description": "Proximity, Similarity, Enclosure, Continuity, Closure, Connection - how humans perceive visual groups", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer", "Architect" ], "matchId": "019de067-33df-76de-913d-67f143c613c1", "evidence": "icon-over-label-over-cell groups via proximity", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 9, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Small Multiples", "slug": "small-multiples", "status": "active", "bestFor": null, "canonId": "019dd956-b32d-7586-b368-baa1dd388ed4", "version": 1, "bodyDocId": null, "description": "Repeating similar charts for comparison across categories or time", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019de067-338c-7258-84f8-d5d1142264b9", "evidence": "five identical industry/use-case columns", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 85, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 9, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Action Titles", "slug": "action-titles", "status": "active", "bestFor": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "canonId": "019dd956-ac70-700b-a608-ba58e78f5dcc", "version": 1, "bodyDocId": "816dad3c-9983-41c1-a86e-978ebd582841", "description": "The McKinsey-bred discipline of writing every slide title as a complete declarative sentence with a verb and an insight, not a topic label. Each title is a sub-claim that ladders up to the deck's governing thought; read in sequence, the titles reconstruct the executive summary.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019de067-3431-74ac-9352-f52906326d52", "evidence": "callout asserts agentic AI can transform your organization", "pageRefs": null, "priority": "Core", "whenToUse": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "confidence": 65, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 10, "whyItWorks": "Solves two failure modes at once. (1) The buried claim: action titles place the conclusion on the page before any analysis is read, so a busy reader doesn't reverse-engineer it from the chart. (2) The spineless deck: because each title is a claim, slides have to ladder up to the governing thought; logical gaps become visible as topic-shaped titles in a sequence that no longer reads as a story.", "antipattern": "Topic labels disguised as titles — Volume by quarter, Key findings, Pricing strategy, Margins have been impacted. No verb, or a passive verb with no agent, or a fact (Revenue grew 12%) without the so-what. Also: titles that overreach the chart's evidence, multi-claim X-grew-but-Y-fell welded titles, and mechanical repetition of the same X-drove-Y template across the deck.", "cardinality": null, "narrativePurpose": "Forces the deck to carry its argument in the title bar so a senior reader can extract the recommendation without opening a single slide; converts a binder of topics into a navigable pyramid where every slide is a node defending the apex." }, { "tool": { "name": "Action Titles", "slug": "action-titles", "status": "active", "bestFor": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "canonId": "019dd956-ac70-700b-a608-ba58e78f5dcc", "version": 1, "bodyDocId": "816dad3c-9983-41c1-a86e-978ebd582841", "description": "The McKinsey-bred discipline of writing every slide title as a complete declarative sentence with a verb and an insight, not a topic label. Each title is a sub-claim that ladders up to the deck's governing thought; read in sequence, the titles reconstruct the executive summary.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019de067-34b0-753f-bf8c-af3c17d0f70b", "evidence": "title Choose your path to implement agents on AWS is directive", "pageRefs": null, "priority": "Core", "whenToUse": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "confidence": 70, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 11, "whyItWorks": "Solves two failure modes at once. (1) The buried claim: action titles place the conclusion on the page before any analysis is read, so a busy reader doesn't reverse-engineer it from the chart. (2) The spineless deck: because each title is a claim, slides have to ladder up to the governing thought; logical gaps become visible as topic-shaped titles in a sequence that no longer reads as a story.", "antipattern": "Topic labels disguised as titles — Volume by quarter, Key findings, Pricing strategy, Margins have been impacted. No verb, or a passive verb with no agent, or a fact (Revenue grew 12%) without the so-what. Also: titles that overreach the chart's evidence, multi-claim X-grew-but-Y-fell welded titles, and mechanical repetition of the same X-drove-Y template across the deck.", "cardinality": null, "narrativePurpose": "Forces the deck to carry its argument in the title bar so a senior reader can extract the recommendation without opening a single slide; converts a binder of topics into a navigable pyramid where every slide is a node defending the apex." }, { "tool": { "name": "Contrast Principle", "slug": "contrast-principle", "status": "active", "bestFor": null, "canonId": "019dd956-bf0f-73ae-b9df-e60508cdaa65", "version": 1, "bodyDocId": null, "description": "Higher visual weight draws attention - use contrast strategically for emphasis", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019de067-3483-7190-972e-5a76e2494274", "evidence": "binary side-by-side panels emphasize the choice", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 75, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 11, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Action Titles", "slug": "action-titles", "status": "active", "bestFor": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "canonId": "019dd956-ac70-700b-a608-ba58e78f5dcc", "version": 1, "bodyDocId": "816dad3c-9983-41c1-a86e-978ebd582841", "description": "The McKinsey-bred discipline of writing every slide title as a complete declarative sentence with a verb and an insight, not a topic label. Each title is a sub-claim that ladders up to the deck's governing thought; read in sequence, the titles reconstruct the executive summary.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019de067-3501-75af-8c3d-c05cc0369afe", "evidence": "callout states AgentCore helps developers accelerate AI agents into production", "pageRefs": null, "priority": "Core", "whenToUse": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "confidence": 70, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 12, "whyItWorks": "Solves two failure modes at once. (1) The buried claim: action titles place the conclusion on the page before any analysis is read, so a busy reader doesn't reverse-engineer it from the chart. (2) The spineless deck: because each title is a claim, slides have to ladder up to the governing thought; logical gaps become visible as topic-shaped titles in a sequence that no longer reads as a story.", "antipattern": "Topic labels disguised as titles — Volume by quarter, Key findings, Pricing strategy, Margins have been impacted. No verb, or a passive verb with no agent, or a fact (Revenue grew 12%) without the so-what. Also: titles that overreach the chart's evidence, multi-claim X-grew-but-Y-fell welded titles, and mechanical repetition of the same X-drove-Y template across the deck.", "cardinality": null, "narrativePurpose": "Forces the deck to carry its argument in the title bar so a senior reader can extract the recommendation without opening a single slide; converts a binder of topics into a navigable pyramid where every slide is a node defending the apex." }, { "tool": { "name": "Executive summary", "slug": "executive-summary", "status": "active", "bestFor": null, "canonId": "019dd9e1-4b63-72d5-9734-da757d91ca61", "version": 1, "bodyDocId": null, "description": "A condensed view of the entire argument on a single slide / block.", "familyLabel": null, "categoryName": null, "categorySlug": null }, "agent": null, "layer": "slide", "agents": null, "matchId": "bf2a0b28-f6b1-4df8-a730-41a8c0b6b76a", "evidence": "list/bullet: Faster time to value", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 21:55:50.798307+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 12, "whyItWorks": null, "antipattern": null, "cardinality": "common", "narrativePurpose": null }, { "tool": { "name": "Small Multiples", "slug": "small-multiples", "status": "active", "bestFor": null, "canonId": "019dd956-b32d-7586-b368-baa1dd388ed4", "version": 1, "bodyDocId": null, "description": "Repeating similar charts for comparison across categories or time", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019de067-352b-73db-9ed3-b6058121c413", "evidence": "seven AgentCore services laid out with same row pattern", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 80, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 13, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Halo Effect", "slug": "halo-effect", "status": "active", "bestFor": null, "canonId": "019dd956-c7a3-757c-82ed-429da0d9256f", "version": 1, "bodyDocId": null, "description": "Positive impression in one area influences opinions in others", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019de067-35e8-763a-885a-911bd5e76384", "evidence": "names CrewAI, LangChain, Strands to borrow ecosystem credibility", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 55, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 14, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Small Multiples", "slug": "small-multiples", "status": "active", "bestFor": null, "canonId": "019dd956-b32d-7586-b368-baa1dd388ed4", "version": 1, "bodyDocId": null, "description": "Repeating similar charts for comparison across categories or time", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019de067-35bf-736e-bd74-1c6c886bfd62", "evidence": "three OSS framework cards with same structure", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 75, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 14, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Authority Bias", "slug": "authority-bias", "status": "active", "bestFor": null, "canonId": "019dd956-c38d-70b9-a284-b2b479763356", "version": 1, "bodyDocId": null, "description": "Expert opinions are weighted more heavily - cite credible sources", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Architect", "Storyteller" ], "matchId": "019de067-363d-773c-abcf-11253e6681f4", "evidence": "leans on MCP being an open standard for credibility", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 60, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 15, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Typography Hierarchy", "slug": "typography-hierarchy", "status": "active", "bestFor": null, "canonId": "019dd956-ba98-77ab-9513-ff2344da8bc7", "version": 1, "bodyDocId": null, "description": "Using font size, weight, and style to create reading order", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019de067-3613-764e-a643-d1016a8062bd", "evidence": "split layout with title, definition callout and resource sidebar", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 60, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 15, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Small Multiples", "slug": "small-multiples", "status": "active", "bestFor": null, "canonId": "019dd956-b32d-7586-b368-baa1dd388ed4", "version": 1, "bodyDocId": null, "description": "Repeating similar charts for comparison across categories or time", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019de067-3692-7787-aad9-fa7da9506f7b", "evidence": "six category callout boxes share identical structure", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 80, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 16, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Mapping", "slug": "mapping", "status": "active", "bestFor": null, "canonId": "019dd956-d74b-74cd-b645-119646136d81", "version": 1, "bodyDocId": null, "description": "Relationship between controls and their effects - make it natural", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019de067-370e-73af-8fe8-87ee5b32ee83", "evidence": "diagram maps marketplace tools to AgentCore Runtime and Gateway", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 60, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 17, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Picture Superiority Effect", "slug": "picture-superiority-effect", "status": "active", "bestFor": null, "canonId": "019dd956-c201-7014-bb58-3e85e3e11dfd", "version": 1, "bodyDocId": null, "description": "Pictures remembered 6x better than words - prioritize visuals over text", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019de067-36bd-72e4-967a-825c8a50ff0c", "evidence": "architecture diagram dominates with partner logos and arrows", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 75, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 17, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Visual Anchors", "slug": "visual-anchors", "status": "active", "bestFor": null, "canonId": "019dd956-c264-7357-a791-89fa5f02a400", "version": 1, "bodyDocId": null, "description": "Design elements that guide users' eyes through the content intentionally", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019de067-36e5-733f-94a5-fea7eda0596b", "evidence": "arrows and central Your AWS account panel guide the eye", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 17, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Action Titles", "slug": "action-titles", "status": "active", "bestFor": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "canonId": "019dd956-ac70-700b-a608-ba58e78f5dcc", "version": 1, "bodyDocId": "816dad3c-9983-41c1-a86e-978ebd582841", "description": "The McKinsey-bred discipline of writing every slide title as a complete declarative sentence with a verb and an insight, not a topic label. Each title is a sub-claim that ladders up to the deck's governing thought; read in sequence, the titles reconstruct the executive summary.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019de067-37a3-74dd-80d3-a124fb5fbb6e", "evidence": "title Accelerate AI agent innovation with AWS Marketplace states the value", "pageRefs": null, "priority": "Core", "whenToUse": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "confidence": 75, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 18, "whyItWorks": "Solves two failure modes at once. (1) The buried claim: action titles place the conclusion on the page before any analysis is read, so a busy reader doesn't reverse-engineer it from the chart. (2) The spineless deck: because each title is a claim, slides have to ladder up to the governing thought; logical gaps become visible as topic-shaped titles in a sequence that no longer reads as a story.", "antipattern": "Topic labels disguised as titles — Volume by quarter, Key findings, Pricing strategy, Margins have been impacted. No verb, or a passive verb with no agent, or a fact (Revenue grew 12%) without the so-what. Also: titles that overreach the chart's evidence, multi-claim X-grew-but-Y-fell welded titles, and mechanical repetition of the same X-drove-Y template across the deck.", "cardinality": null, "narrativePurpose": "Forces the deck to carry its argument in the title bar so a senior reader can extract the recommendation without opening a single slide; converts a binder of topics into a navigable pyramid where every slide is a node defending the apex." }, { "tool": { "name": "Law of Similarity", "slug": "law-of-similarity", "status": "active", "bestFor": null, "canonId": "019dd956-c025-70d9-a411-8efa41ae179b", "version": 1, "bodyDocId": null, "description": "Similar-looking elements perceived as related - consistent styling for related concepts", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019de067-37cf-771d-9a96-cae2ed4d028a", "evidence": "three identical card layouts read as parallel pillars", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 18, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "List presentation", "slug": "list-presentation", "status": "active", "bestFor": null, "canonId": "019dd9e1-4ef7-777d-ba68-9074c2b3bcf1", "version": 1, "bodyDocId": null, "description": "Bulleted, numbered, or checklist enumerations.", "familyLabel": null, "categoryName": null, "categorySlug": null }, "agent": null, "layer": "slide", "agents": null, "matchId": "362accb8-f61e-4f14-90e9-af8c4884b0d6", "evidence": "The slide contains a list of bullet points.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.9, "extraction": { "at": "2026-07-16 21:56:03.967184+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 18, "whyItWorks": null, "antipattern": null, "cardinality": "common", "narrativePurpose": null }, { "tool": { "name": "Closing Techniques", "slug": "closing-techniques", "status": "active", "bestFor": null, "canonId": "019dd956-af13-774b-a4fd-7db0a3a88d51", "version": 1, "bodyDocId": null, "description": "Strong endings: Callback, challenge, vision, clear CTA, memorable line", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019de067-37fa-7482-b950-b6417770c1de", "evidence": "Conclusion slide with three explicit CTA links", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 80, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 19, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Nudge", "slug": "nudge", "status": "active", "bestFor": null, "canonId": "019dd956-c61a-72f9-920c-88acf4ecc336", "version": 1, "bodyDocId": null, "description": "Subtle hints can significantly affect decisions - strategic CTA placement", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Architect", "Designer" ], "matchId": "019de067-3824-7568-8f0b-00d0fa4ada47", "evidence": "purple sidebar surfaces next-step links prominently", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 55, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 19, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Storytelling: the closing ask", "slug": "closing-ask", "status": "active", "bestFor": null, "canonId": "019df269-24e0-70ab-8dd9-983832c1c665", "version": 1, "bodyDocId": "019df269-24bc-7554-b88d-245127606b8d", "description": "The single most important slide in the deck — after the cover. The final", "familyLabel": "narrative-block", "categoryName": "Narrative & Transformation", "categorySlug": "narrative-transformation" }, "agent": "storyteller", "layer": "slide", "agents": [ "storyteller" ], "matchId": "a02443be-76f2-47de-96e6-e249b2039d63", "evidence": "The slide has a title 'Conclusion' and a callout with a primary key resource.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.8, "extraction": { "at": "2026-07-16 21:56:04.039098+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 19, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [ { "matchId": "312c5393-6805-4694-b79c-8e03193ac878", "evidence": "The slide presents a progression of organizational capabilities across three distinct stages.", "framework": null, "confidence": 1, "extraction": { "at": "2026-05-02 17:43:45.12+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 4, "frameworkName": "maturity-model" }, { "matchId": "019de067-3850-73bc-b6d4-3521384be794", "evidence": "Emerging / Developing / Mature stages across six capability dimensions", "framework": null, "confidence": 90, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 4, "frameworkName": "Maturity Model" }, { "matchId": "019de067-38a5-77da-b6be-271a06ff7fc0", "evidence": "explicit six-stage IDC framework labelled on chart", "framework": null, "confidence": 85, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 7, "frameworkName": "IDC Agentic Evolution of Enterprise Applications" }, { "matchId": "103b3530-3d03-422a-8f92-af59986fac25", "evidence": "The slide maps the evolution of enterprise applications through distinct stages of AI adoption over time.", "framework": null, "confidence": 0.9, "extraction": { "at": "2026-05-02 17:43:46.159+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 7, "frameworkName": "maturity-model" }, { "matchId": "019de067-387a-73c3-8658-95051565e187", "evidence": "IDC chart shows adoption percentages on an S-curve across 2025-2037", "framework": null, "confidence": 70, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 7, "frameworkName": "S-Curve Adoption Model" }, { "matchId": "019de067-38ce-70ba-a30a-453db25c092f", "evidence": "two-column ready-to-deploy vs build custom choice", "framework": null, "confidence": 75, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 11, "frameworkName": "Buy vs Build Framework" }, { "matchId": "8e6f3d1b-b792-47e8-881b-ac0389011b04", "evidence": "Categorization of market offerings into distinct functional segments.", "framework": null, "confidence": 0.6, "extraction": { "at": "2026-05-02 17:43:50.426+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 16, "frameworkName": "market-segmentation-pyramid" }, { "matchId": "30694fbf-5d6d-4626-90d6-1abe5205326f", "evidence": "The diagram shows a central 'Your AWS account' box connecting to external Marketplace sources.", "framework": null, "confidence": 0.9, "extraction": { "at": "2026-05-02 17:43:46.588+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 17, "frameworkName": "hub-spoke" } ], "patterns": [] }, "storymakers": { "model": "claude-cli", "backend": "claude", "rawJson": { "arc": { "id": 5, "slug": "aida", "beats": [ { "name": "Attention", "end_page": 3, "evidence": "cover, TOC and intro frame the topic", "position": 1, "start_page": 1 }, { "name": "Interest", "end_page": 7, "evidence": "maturity baseline, definitions, IDC adoption curve", "position": 2, "start_page": 4 }, { "name": "Desire", "end_page": 17, "evidence": "case studies, industries, AWS services, AgentCore stack", "position": 3, "start_page": 8 }, { "name": "Action", "end_page": 19, "evidence": "Marketplace value prop and conclusion CTAs", "position": 4, "start_page": 18 } ], "evidence": "Vendor eBook moves from cover/definitions (p1-3) to market interest (p4-7) to use cases + AWS stack (p8-17) to Marketplace CTA (p18-19).", "confidence": 72 }, "loops": [ { "id": 6, "slug": "06-zoom-in", "end_page": 7, "evidence": "p3 big picture intro -> p4 maturity focus -> p5-6 specific definitions -> p7 implication via IDC adoption curve.", "position": 1, "objective": "Establish what agentic AI is and where the market is going", "confidence": 70, "start_page": 3 }, { "id": 2, "slug": "02-pattern-hunter", "end_page": 10, "evidence": "Three slides stack customer cases and industry examples that converge on the pattern that agentic AI is delivering today.", "position": 2, "objective": "Show real-world adoption proves agentic AI works", "confidence": 75, "start_page": 8 }, { "id": 33, "slug": "33-build-up", "end_page": 15, "evidence": "Base choice (p11) + AgentCore (p12) + service modules (p13) + OSS frameworks (p14) + MCP (p15) sums to full AWS offering.", "position": 3, "objective": "Build up the AWS agentic stack as a complete solution", "confidence": 72, "start_page": 11 }, { "id": 33, "slug": "33-build-up", "end_page": 18, "evidence": "Catalog breadth (p16) + deployment architecture (p17) + three-pillar value prop (p18) builds Marketplace pitch.", "position": 4, "objective": "Position AWS Marketplace as the operational layer", "confidence": 65, "start_page": 16 } ], "slide_tools": [ { "tools": [ { "id": 6, "slug": "06-zoom-in", "layer": "Loop", "evidence": "first page of zoom-in loop introducing agentic AI", "confidence": 65 }, { "id": 149, "slug": "typography-hierarchy", "layer": "Slide", "evidence": "kicker label, large title, body sets reading order", "confidence": 70 } ], "page_number": 3 }, { "tools": [ { "id": 118, "slug": "action-titles", "layer": "Slide", "evidence": "callout states the so-what about baselines and alignment", "confidence": 70 }, { "id": 133, "slug": "small-multiples", "layer": "Slide", "evidence": "Emerging/Developing/Mature columns repeat across 6 dimensions", "confidence": 85 }, { "id": 131, "slug": "gestalt-principles", "layer": "Slide", "evidence": "table grid uses proximity and similarity to group rows/columns", "confidence": 80 }, { "id": 34, "slug": "the-rule-of-three", "layer": "Block", "evidence": "three maturity stages structure the slide", "confidence": 75 } ], "page_number": 4 }, { "tools": [ { "id": 165, "slug": "picture-superiority-effect", "layer": "Slide", "evidence": "icon-led cards anchor each definition", "confidence": 70 }, { "id": 128, "slug": "one-idea-rule", "layer": "Slide", "evidence": "single concept: definitional taxonomy", "confidence": 70 }, { "id": 161, "slug": "law-of-similarity", "layer": "Slide", "evidence": "three identically-styled cards mark the same level of abstraction", "confidence": 75 }, { "id": 34, "slug": "the-rule-of-three", "layer": "Block", "evidence": "Generative AI / AI Agents / Agentic AI triad", "confidence": 80 } ], "page_number": 5 }, { "tools": [ { "id": 116, "slug": "chunking", "layer": "Loop", "evidence": "capabilities listed as digestible bullets", "confidence": 65 }, { "id": 119, "slug": "so-what-test", "layer": "Slide", "evidence": "callout converts capability list into customer outcome", "confidence": 65 } ], "page_number": 6 }, { "tools": [ { "id": 165, "slug": "picture-superiority-effect", "layer": "Slide", "evidence": "IDC S-curve dominates the slide", "confidence": 75 }, { "id": 138, "slug": "annotation", "layer": "Slide", "evidence": "stage labels and percentages annotate the curve", "confidence": 70 }, { "id": 155, "slug": "credibility-transfer", "layer": "Slide", "evidence": "IDC source explicitly cited under chart", "confidence": 80 } ], "page_number": 7 }, { "tools": [ { "id": 74, "slug": "inductive-reasoning", "layer": "Loop", "evidence": "loop opens with first set of customer cases pointing to a pattern", "confidence": 70 }, { "id": 226, "slug": "social-validation", "layer": "Slide", "evidence": "names AWS customers using Bedrock Agents", "confidence": 75 }, { "id": 118, "slug": "action-titles", "layer": "Slide", "evidence": "kicker frames the takeaway as real-world proof", "confidence": 60 } ], "page_number": 8 }, { "tools": [ { "id": 133, "slug": "small-multiples", "layer": "Slide", "evidence": "five identical industry/use-case columns", "confidence": 85 }, { "id": 130, "slug": "color-strategy", "layer": "Slide", "evidence": "purple gradient on industry headers separates from white use-case rows", "confidence": 70 }, { "id": 131, "slug": "gestalt-principles", "layer": "Slide", "evidence": "icon-over-label-over-cell groups via proximity", "confidence": 70 } ], "page_number": 9 }, { "tools": [ { "id": 72, "slug": "social-proof", "layer": "Block", "evidence": "three real implementation examples in healthcare and HPC given as proof", "confidence": 70 }, { "id": 118, "slug": "action-titles", "layer": "Slide", "evidence": "callout asserts agentic AI can transform your organization", "confidence": 65 } ], "page_number": 10 }, { "tools": [ { "id": 78, "slug": "contrast-pairs", "layer": "Loop", "evidence": "two-column Agentic AI applications vs Build custom agents", "confidence": 80 }, { "id": 159, "slug": "contrast-principle", "layer": "Slide", "evidence": "binary side-by-side panels emphasize the choice", "confidence": 75 }, { "id": 118, "slug": "action-titles", "layer": "Slide", "evidence": "title Choose your path to implement agents on AWS is directive", "confidence": 70 } ], "page_number": 11 }, { "tools": [ { "id": 34, "slug": "the-rule-of-three", "layer": "Block", "evidence": "three benefit columns: speed, flexibility, security", "confidence": 80 }, { "id": 118, "slug": "action-titles", "layer": "Slide", "evidence": "callout states AgentCore helps developers accelerate AI agents into production", "confidence": 70 } ], "page_number": 12 }, { "tools": [ { "id": 133, "slug": "small-multiples", "layer": "Slide", "evidence": "seven AgentCore services laid out with same row pattern", "confidence": 80 }, { "id": 116, "slug": "chunking", "layer": "Loop", "evidence": "complex platform broken into seven named modules", "confidence": 60 } ], "page_number": 13 }, { "tools": [ { "id": 133, "slug": "small-multiples", "layer": "Slide", "evidence": "three OSS framework cards with same structure", "confidence": 75 }, { "id": 178, "slug": "halo-effect", "layer": "Slide", "evidence": "names CrewAI, LangChain, Strands to borrow ecosystem credibility", "confidence": 55 } ], "page_number": 14 }, { "tools": [ { "id": 149, "slug": "typography-hierarchy", "layer": "Slide", "evidence": "split layout with title, definition callout and resource sidebar", "confidence": 60 }, { "id": 169, "slug": "authority-bias", "layer": "Slide", "evidence": "leans on MCP being an open standard for credibility", "confidence": 60 } ], "page_number": 15 }, { "tools": [ { "id": 93, "slug": "build-up-gradatio", "layer": "Loop", "evidence": "loop assembles Marketplace catalog, deployment, value", "confidence": 60 }, { "id": 133, "slug": "small-multiples", "layer": "Slide", "evidence": "six category callout boxes share identical structure", "confidence": 80 } ], "page_number": 16 }, { "tools": [ { "id": 165, "slug": "picture-superiority-effect", "layer": "Slide", "evidence": "architecture diagram dominates with partner logos and arrows", "confidence": 75 }, { "id": 166, "slug": "visual-anchors", "layer": "Slide", "evidence": "arrows and central Your AWS account panel guide the eye", "confidence": 70 }, { "id": 212, "slug": "mapping", "layer": "Slide", "evidence": "diagram maps marketplace tools to AgentCore Runtime and Gateway", "confidence": 60 } ], "page_number": 17 }, { "tools": [ { "id": 34, "slug": "the-rule-of-three", "layer": "Block", "evidence": "three columns: Centralized catalog, Streamlined procurement, Trusted marketplace", "confidence": 85 }, { "id": 118, "slug": "action-titles", "layer": "Slide", "evidence": "title Accelerate AI agent innovation with AWS Marketplace states the value", "confidence": 75 }, { "id": 161, "slug": "law-of-similarity", "layer": "Slide", "evidence": "three identical card layouts read as parallel pillars", "confidence": 70 } ], "page_number": 18 }, { "tools": [ { "id": 124, "slug": "closing-techniques", "layer": "Slide", "evidence": "Conclusion slide with three explicit CTA links", "confidence": 80 }, { "id": 174, "slug": "nudge", "layer": "Slide", "evidence": "purple sidebar surfaces next-step links prominently", "confidence": 55 } ], "page_number": 19 } ], "slides_seen": 19, "deck_summary": "AWS Marketplace vendor eBook with a loose AIDA shape and a clean Marketplace CTA, but weak narrative tension, no SCQA framing, and only intermittent action titles - moderate Storymakers alignment.", "secondary_arcs": [ { "id": 1, "slug": "consultants-gambit", "beats": [ { "name": "Situation & Context", "end_page": 7, "evidence": "definitions, baseline, market trajectory", "position": 1, "start_page": 3 }, { "name": "Problem & Complication", "end_page": 9, "evidence": "data-rich industries face challenges agentic AI solves", "position": 2, "start_page": 9 }, { "name": "Solution & Approach", "end_page": 15, "evidence": "Choose path, AgentCore, OSS frameworks, MCP", "position": 3, "start_page": 11 }, { "name": "Evidence & Proof", "end_page": 10, "evidence": "real-world AWS Bedrock customer case studies", "position": 4, "start_page": 8 }, { "name": "Impact & Next Steps", "end_page": 19, "evidence": "Marketplace value prop and CTA links", "position": 5, "start_page": 18 } ], "evidence": "Loose fit: context p3-7, implicit complication p7/p9, AWS solution p11-15, proof p8-10, CTA p18-19; evidence/solution order is inverted vs canonical.", "confidence": 48 } ], "images_inspected": 8, "slide_frameworks": [ { "frameworks": [ { "name": "Maturity Model", "slug": "maturity-model", "evidence": "Emerging / Developing / Mature stages across six capability dimensions", "confidence": 90 } ], "page_number": 4 }, { "frameworks": [ { "name": "S-Curve Adoption Model", "slug": "s-curve-adoption", "evidence": "IDC chart shows adoption percentages on an S-curve across 2025-2037", "confidence": 70 }, { "name": "IDC Agentic Evolution of Enterprise Applications", "slug": "idc-agentic-evolution", "evidence": "explicit six-stage IDC framework labelled on chart", "confidence": 85 } ], "page_number": 7 }, { "frameworks": [ { "name": "Buy vs Build Framework", "slug": "buy-vs-build", "evidence": "two-column ready-to-deploy vs build custom choice", "confidence": 75 } ], "page_number": 11 } ] }, "matchedAt": "2026-04-30 21:59:11.462+00", "slidesSeen": 19, "deckSummary": "AWS Marketplace vendor eBook with a loose AIDA shape and a clean Marketplace CTA, but weak narrative tension, no SCQA framing, and only intermittent action titles - moderate Storymakers alignment.", "imagesInspected": 8, "extractionSeconds": 277.942 }, "score": { "backend": "codex", "scoredAt": "2026-05-02 22:43:45.312+00", "subScores": { "scqa_arc": 52, "action_titles": 35, "mece_structure": 58, "closing_strength": 55, "evidence_quality": 56, "clarity_of_thesis": 55, "production_quality": 60, "visual_storytelling": 68 }, "totalScore": 55, "coveragePct": 100, "explanations": { "scqa_arc": "Slides 1-7 establish the situation and emerging shift, but the complication and governing question remain mostly implied, making slides 8-18 feel more like an analytical and product-resource tour than a crisp SCQA answer.", "action_titles": "Most titles are topic labels or imperatives rather than insight sentences; for example, slide 6 uses \"Agentic AI capabilities\" instead of a takeaway about why those capabilities matter.", "mece_structure": "The deck has a sensible progression from definition to examples to AWS implementation paths, but slides 12-18 overlap across AgentCore, OSS frameworks, MCP, and Marketplace solutions without a fully MECE decision architecture.", "closing_strength": "Slide 19 provides a conclusion and starter resources, but it stops short of a specific recommendation, decision request, owner path, or sequenced next steps.", "evidence_quality": "Evidence is moderate, with IDC framing on slide 7 and case/resource examples on slides 8 and 10, but many claims are vendor assertions without quantified outcomes or independent proof.", "clarity_of_thesis": "The thesis is directionally visible in slides 1-5 as agentic AI is rising and AWS can help unlock value, but it is not stated as a sharp declarative argument until the Marketplace value proposition becomes clearer around slides 16-18.", "production_quality": "Production quality is acceptable, but action-title density is low, several slides are dense with repeated title/body elements, and the resource/sidebar pattern is not consistently disciplined across slides 12-19.", "visual_storytelling": "The deck uses appropriate tools such as the maturity model on slide 4, evolution framework on slide 7, use-case tables on slide 9, and architecture diagram on slide 17, though several dense resource slides dilute the message." }, "slidesAnalyzed": 19 }, "review": { "backend": "claude", "verdict": "A competent but conventional vendor thought-leadership eBook — structurally tidy and well-branded, but a weak Storymakers exemplar because it leads with definitions instead of a thesis and relies on topic labels rather than action titles.", "reviewedAt": "2026-05-02 07:08:14.036+00", "slidesSeen": 19, "suggestions": [ "Rewrite the cover and slide 3 to lead with the answer — e.g. 'Agentic AI will reshape enterprise workflows by 2030; here is how to capture value on AWS'", "Convert topic titles into action titles: 'Bedrock AgentCore services' → 'Seven AgentCore modules cover the full agent lifecycle'; 'Conclusion' → 'Start with Marketplace agents, scale with AgentCore'", "Insert a Complication slide between slides 7 and 8 that names the specific cost, risk, or competitive penalty of not adopting agentic AI", "Merge slides 8 and 10 (both case-study resource hubs) into one slide and use the recovered space for a customer-outcome metric", "Add a synthesis slide before the Conclusion that restates the 3-4 takeaways as a single visual so the reader leaves with a memorable mental model" ], "closingScore": 70, "openingScore": 45, "topStrengths": [ "Clear modular pillar structure visible in the TOC (slide 2) and consistent AWS visual branding", "Slide 11 ('Choose your path...') uses a genuine action title and a binary MECE build-vs-buy framing", "Closing slides 18-19 deliver an explicit recommendation and CTA, which is rare in vendor decks" ], "topWeaknesses": [ "Opening five slides are definitional/glossary-heavy with no thesis or stakes — the 'so what' arrives too late", "Roughly 80% of titles are topic labels ('Conclusion', 'Bedrock AgentCore services', 'Agentic AI capabilities') rather than insight-bearing assertions", "No genuine Complication act: the deck skips from context to solutions without articulating customer pain or risk of inaction", "Slides 8 and 10 are near-duplicate 'resource hub' case-study slides, suggesting redundancy rather than escalation" ], "narrativeScore": 55, "pillarCritique": "The TOC pillars (overview → landscape → industry → AWS deployment → marketplace) are coherent but topic-driven rather than MECE arguments; they describe content categories, not a logical chain of claims.", "closingCritique": "Slides 18-19 land an explicit recommendation ('Accelerate AI agent innovation with AWS Marketplace') and a CTA with resource links — solid for a vendor eBook. However, the close is a marketing pitch rather than a memorable synthesis of the journey.", "openingCritique": "Slides 1-5 spend time defining terms (slide 3 'Understanding agentic AI', slide 5 'Generative AI, agentic AI, and AI agents') before stating any thesis or stake. The reader reaches page 7 before grasping why this matters, and even there the hook is buried inside an IDC infographic.", "extractionSeconds": 54.99, "narrativeCritique": "The deck follows a soft Setup (slides 1-7) → Analysis (8-15) → Resolution (16-19) arc but skips a true Complication act — there is no clear tension or business problem framed before solutions appear. It reads more as a vendor catalog walkthrough than a story arc.", "titleQualityScore": 35, "titleQualityCritique": "Most titles are noun-phrase topic labels — 'Understanding agentic AI' (3), 'Agentic AI capabilities' (6), 'Bedrock AgentCore services' (13), 'Conclusion' (19). Only a handful approach action-title quality, e.g. 'Choose your path to implement agents on AWS' (11) and 'Accelerate AI agent innovation with AWS Marketplace' (18)." }, "activistThesis": null, "pitchdeck": { "metadata": null, "profile": null }, "slides": [ { "page": 1, "type": "setup", "function": "front_matter", "imagePath": "https://imgproxy.kitesheet.com/Ut2sCydhTDpJbZqqb8cVLSa50T88l62U0lERGX7E2uc/rs:fit:1200:1200:0/q:82/f:webp/czM6Ly9raXRlc2hlZXQvY29ycHVzL3NsaWRlcy8zYzIwMDA5OGI0ZGIyNzI0L3AwMDEuanBn", "rawType": "cover", "block": null, "metadata": { "slideType": "cover", "slideTypeCanon": { "name": "Cover", "slug": "cover", "status": "active", "canonId": "019de52d-05f2-729d-9f93-e0504f0a2410", "version": 1, "description": null }, "function": "front_matter", "functionCanon": { "name": "Front matter", "slug": "front_matter", "status": "active", "canonId": "019de52d-133d-73f0-9e26-201eda96b098", "version": 1, "description": null }, "density": "sparse", "densityScore": 10, "componentCount": 3, "textChars": 135, "nDataPoints": 0, "notes": null, "elementsJson": [ "logo_grid" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:43:43.919+00", "seconds": 1.876, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5c-b1fd37abc6e1/1", "deck": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1#slide-1", "deckJson": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1.json" }, "components": [ { "bbox": { "h": 0.02, "w": 0.3, "x": 0.058, "y": 0.95 }, "kind": "disclaimer", "text": "© 2025, Amazon Web Services, Inc. or its affiliates. All rights reserved.", "attrs": null, "canon": { "kind": { "name": "Disclaimer", "slug": "disclaimer", "status": "active", "canonId": "91173477-d91f-4024-bbaf-d4f93e3f82dc", "version": 1, "description": "Legal/cautionary text that occupies most of the body of its slide." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:43.919+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "2238c80e-4772-44a6-9fef-fdc990bd025e", "parentComponentId": null }, { "bbox": { "h": 0.045, "w": 0.309, "x": 0.058, "y": 0.083 }, "kind": "image", "text": "aws marketplace", "attrs": null, "canon": { "kind": { "name": "Image", "slug": "image", "status": "active", "canonId": "019de52c-f978-701f-a720-51d029d769e7", "version": 1, "description": "Photo, illustration, screenshot or icon." }, "tool": null, "subkind": { "name": "Logo", "slug": "logo", "status": "active", "canonId": "019de52c-fdaf-743d-94c4-d7c6a0e55302", "version": 1, "description": null }, "framework": null }, "subkind": "logo", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:43.919+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "505bef94-325c-47c1-93dd-a158b79fd89e", "parentComponentId": null }, { "bbox": { "h": 0.15, "w": 0.625, "x": 0.058, "y": 0.288 }, "kind": "title", "text": "Agentic AI on the rise: Keys to unlocking value", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:43.919+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "1cc8ae68-c115-442d-84a9-90ff8e479473", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 3, "arc": { "name": "AIDA", "slug": "aida", "status": "active", "bestFor": "Marketing presentations, product launches, sales enablement", "canonId": "019dd956-5fb4-77aa-866d-f9bdd47803af", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Attention -> Interest -> Desire -> Action", "description": null, "familyLabel": null }, "from": 1, "name": "Attention", "beatId": "019de067-2dbb-716b-9743-5aade551d0f4", "matchId": "019de067-2d91-7264-a72e-b60277f83dc2", "beatType": null, "evidence": "cover, TOC and intro frame the topic", "position": 1, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 72 } ], "loops": [], "thumbSrc": "https://imgproxy.kitesheet.com/PMQyyRNaepigQeQr4snqz6XhpWCLjbz2LNmOzyKslbo/rs:fit:480:480:0/q:78/f:webp/czM6Ly9raXRlc2hlZXQvY29ycHVzL3NsaWRlcy8zYzIwMDA5OGI0ZGIyNzI0L3AwMDEuanBn", "imagePathAlt": "https://imgproxy.kitesheet.com/jNyxEAuSYJ954bD8RMWLQW05Gz5UAb0Ci2pWcBhFazc/rs:fit:1200:1200:0/q:82/f:webp/czM6Ly9raXRlc2hlZXQvY29ycHVzL3NsaWRlcy8zYzIwMDA5OGI0ZGIyNzI0L3AwMDEucG5n", "thumbSrcAlt": "https://imgproxy.kitesheet.com/vaAJFkauV86xbECO_WYGXs9qNYesdNpKUhMJgQMMJXo/rs:fit:480:480:0/q:78/f:webp/czM6Ly9raXRlc2hlZXQvY29ycHVzL3NsaWRlcy8zYzIwMDA5OGI0ZGIyNzI0L3AwMDEucG5n" }, { "page": 2, "type": "setup", "function": "front_matter", "rawType": "table_of_contents", "block": null, "metadata": { "slideType": "table_of_contents", "slideTypeCanon": { "name": "Table of contents", "slug": "table_of_contents", "status": "active", "canonId": "019de52d-0643-721b-9b85-69676bb85cf8", "version": 1, "description": null }, "function": "front_matter", "functionCanon": { "name": "Front matter", "slug": "front_matter", "status": "active", "canonId": "019de52d-133d-73f0-9e26-201eda96b098", "version": 1, "description": null }, "density": "sparse", "densityScore": 23, "componentCount": 2, "textChars": 531, "nDataPoints": 0, "notes": null, "elementsJson": [ "numbered_list" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:43:44.604+00", "seconds": 2.474, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5c-b1fd37abc6e1/2", "deck": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1#slide-2", "deckJson": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1.json" }, "components": [ { "bbox": { "h": 0.02, "w": 0.3, "x": 0.22, "y": 0.96 }, "kind": "disclaimer", "text": "© 2025, Amazon Web Services, Inc. or its affiliates. All rights reserved.", "attrs": null, "canon": { "kind": { "name": "Disclaimer", "slug": "disclaimer", "status": "active", "canonId": "91173477-d91f-4024-bbaf-d4f93e3f82dc", "version": 1, "description": "Legal/cautionary text that occupies most of the body of its slide." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:44.604+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "d0764bcb-3523-4736-a004-a7b704a97adb", "parentComponentId": null }, { "bbox": { "h": 0.8, "w": 0.6, "x": 0.05, "y": 0.1 }, "kind": "list", "text": "Agentic AI overview (3)\nUnderstanding Agentic AI\nAgentic AI landscape (4)\nAI maturity baseline, agentic AI features, evolution\nEnabling data-reliant industries to thrive (9)\nIndustry use cases and real-world customer stories\nBuy, build, and deploy agents with AWS (11)\nAWS agentic services overview, open-source frameworks, and standard protocols\nAI agents and tools in AWS Marketplace (19)\nDiscover agent solutions from AWS Partners to accelerate innovation", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:44.604+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "2b0e2864-3076-4d78-93b8-6cd185b7e840", "parentComponentId": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 3, "arc": { "name": "AIDA", "slug": "aida", "status": "active", "bestFor": "Marketing presentations, product launches, sales enablement", "canonId": "019dd956-5fb4-77aa-866d-f9bdd47803af", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Attention -> Interest -> Desire -> Action", "description": null, "familyLabel": null }, "from": 1, "name": "Attention", "beatId": "019de067-2dbb-716b-9743-5aade551d0f4", "matchId": "019de067-2d91-7264-a72e-b60277f83dc2", "beatType": null, "evidence": "cover, TOC and intro frame the topic", "position": 1, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 72 } ], "loops": [], "locked": true }, { "page": 3, "type": "setup", "title": "The slide serves as an introductory page for an eBook or presentation deck.", "function": "establish_context", "rawType": "executive_summary", "block": null, "metadata": { "slideType": "executive_summary", "slideTypeCanon": { "name": "Executive summary", "slug": "executive_summary", "status": "active", "canonId": "019de52d-06be-73ff-81b3-f99fe7f0025e", "version": 1, "description": null }, "function": "establish_context", "functionCanon": { "name": "Establish context", "slug": "establish_context", "status": "active", "canonId": "019de52d-1314-74e6-9074-d213dc0bdcdf", "version": 1, "description": null }, "density": "dense", "densityScore": 71, "componentCount": 8, "textChars": 943, "nDataPoints": 0, "notes": "The slide serves as an introductory page for an eBook or presentation deck.", "elementsJson": [ "paragraph", "bullet_list" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:43:45.169+00", "seconds": 3.014, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5c-b1fd37abc6e1/3", "deck": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1#slide-3", "deckJson": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1.json" }, "components": [ { "bbox": { "h": 0.03, "w": 0.12, "x": 0.06, "y": 0.94 }, "kind": "image", "text": "aws marketplace", "attrs": null, "canon": { "kind": { "name": "Image", "slug": "image", "status": "active", "canonId": "019de52c-f978-701f-a720-51d029d769e7", "version": 1, "description": "Photo, illustration, screenshot or icon." }, "tool": null, "subkind": { "name": "Logo", "slug": "logo", "status": "active", "canonId": "019de52c-fdaf-743d-94c4-d7c6a0e55302", "version": 1, "description": null }, "framework": null }, "subkind": "logo", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:45.169+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "c3273e8e-8007-45dd-99c0-d59cbd0322ff", "parentComponentId": null }, { "bbox": { "h": 0.15, "w": 0.45, "x": 0.06, "y": 0.45 }, "kind": "list", "text": "How organizations are transforming with agentic AI through real-world customer examples\nKey resources to help navigate operational and technical implementation\nHow AWS Marketplace streamlines discovery, procurement, and deployment of AI agent solutions", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:45.169+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "7f9be750-4a34-49b6-a1db-81142750319c", "parentComponentId": null }, { "bbox": { "h": 0.15, "w": 0.45, "x": 0.06, "y": 0.16 }, "kind": "paragraph", "text": "Organizations face increasingly complex operational challenges that traditional automation can't adequately address. AI agents on AWS represent a new approach to these challenges, combining the reasoning capabilities of foundation models with sophisticated orchestration tools.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:45.169+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "005ee7e7-4893-4079-99fc-428e770058a3", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.2, "x": 0.06, "y": 0.41 }, "kind": "paragraph", "text": "In this eBook, we explore", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:45.169+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "0c2e11be-30f2-42de-a842-09c2aaf3c766", "parentComponentId": null }, { "bbox": { "h": 0.08, "w": 0.45, "x": 0.06, "y": 0.62 }, "kind": "paragraph", "text": "Whether you're just getting started or moving quickly to improve operations, drive sales, or increase employee efficiency, it is helpful to create a baseline of your organization's AI maturity.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:45.169+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "4aa055a3-b2b6-4405-ab7c-2bd12668f8f0", "parentComponentId": null }, { "bbox": { "h": 0.08, "w": 0.45, "x": 0.06, "y": 0.32 }, "kind": "paragraph", "text": "These agents don't simply follow pre-programmed rules; they can reason, plan, and act to accomplish goals, with limited human involvement.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:45.169+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "54aeecab-fb88-479a-8ed8-3909650bf4ea", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.35, "x": 0.06, "y": 0.08 }, "kind": "title", "text": "Understanding agentic AI", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:45.169+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "3699f85c-b109-44c9-a6f1-d700d3ddff2c", "parentComponentId": null }, { "bbox": { "h": 0.02, "w": 0.15, "x": 0.06, "y": 0.04 }, "kind": "title", "text": "AGENTIC AI OVERVIEW", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Subtitle", "slug": "subtitle", "status": "active", "canonId": "019de52c-fb09-739d-900c-815b0d9ac526", "version": 1, "description": null }, "framework": null }, "subkind": "subtitle", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:45.169+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "86e421a8-a9ed-48d3-8a02-f3e620a6dba0", "parentComponentId": null } ], "metrics": [], "tools": [ { "tool": { "name": "Executive summary", "slug": "executive-summary", "status": "active", "bestFor": null, "canonId": "019dd9e1-4b63-72d5-9734-da757d91ca61", "version": 1, "bodyDocId": null, "description": "A condensed view of the entire argument on a single slide / block.", "familyLabel": null, "categoryName": null, "categorySlug": null }, "agent": null, "layer": "slide", "agents": null, "matchId": "d626acc6-3e89-407a-93e2-a98ef0691001", "evidence": "Understanding agentic AI", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.8, "extraction": { "at": "2026-07-16 21:56:23.292571+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 3, "whyItWorks": null, "antipattern": null, "cardinality": "common", "narrativePurpose": null }, { "tool": { "name": "Typography Hierarchy", "slug": "typography-hierarchy", "status": "active", "bestFor": null, "canonId": "019dd956-ba98-77ab-9513-ff2344da8bc7", "version": 1, "bodyDocId": null, "description": "Using font size, weight, and style to create reading order", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019de067-3041-736d-aac3-7e4c5136c83f", "evidence": "kicker label, large title, body sets reading order", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 3, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 3, "arc": { "name": "AIDA", "slug": "aida", "status": "active", "bestFor": "Marketing presentations, product launches, sales enablement", "canonId": "019dd956-5fb4-77aa-866d-f9bdd47803af", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Attention -> Interest -> Desire -> Action", "description": null, "familyLabel": null }, "from": 1, "name": "Attention", "beatId": "019de067-2dbb-716b-9743-5aade551d0f4", "matchId": "019de067-2d91-7264-a72e-b60277f83dc2", "beatType": null, "evidence": "cover, TOC and intro frame the topic", "position": 1, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 72 }, { "to": 7, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null }, "from": 3, "name": "Situation & Context", "beatId": "019de067-2e91-718c-ad8f-08210928f992", "matchId": "019de067-2e65-73ce-8e5b-7d2ab9a39fa9", "beatType": null, "evidence": "definitions, baseline, market trajectory", "position": 1, "isPrimaryArc": false, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 48 } ], "loops": [ { "to": 7, "from": 3, "loop": { "name": "06_zoom_in", "slug": "06-zoom-in", "status": "active", "bestFor": "Technical deep-dives, case studies, detailed analysis", "canonId": "019dd956-6846-74db-82be-dff5b058b072", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Big Picture -> Key Area of Focus -> Specific Detail -> Implication", "description": "Start broad, then progressively focus on specific details that prove your point", "familyLabel": null }, "matchId": "019de067-2f9a-73ab-80d7-790e58b86a2f", "evidence": "p3 big picture intro -> p4 maturity focus -> p5-6 specific definitions -> p7 implication via IDC adoption curve.", "position": 1, "objective": "Establish what agentic AI is and where the market is going", "confidence": 70, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null } } ], "locked": true }, { "page": 4, "type": "setup", "title": "The slide uses a standard maturity model structure to help organizations assess their current AI capabilities.", "function": "present_framework", "rawType": "maturity_model", "block": null, "metadata": { "slideType": "maturity_model", "slideTypeCanon": null, "function": "present_framework", "functionCanon": { "name": "Present framework", "slug": "present_framework", "status": "active", "canonId": "019de52d-1403-7667-9100-d2ac6709f750", "version": 1, "description": null }, "density": "balanced", "densityScore": 37, "componentCount": 5, "textChars": 519, "nDataPoints": 0, "notes": "The slide uses a standard maturity model structure to help organizations assess their current AI capabilities.", "elementsJson": [ "headline_text", "paragraph", "comparison_table", "other" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:43:45.12+00", "seconds": 2.63, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5c-b1fd37abc6e1/4", "deck": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1#slide-4", "deckJson": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1.json" }, "components": [ { "bbox": null, "kind": "callout", "text": "Establishing a baseline of team skills and technical capabilities helps you gain cross-organization alignment enabling you to set realistic goals for your future AI adoption.", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-25 11:59:02+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-41aa-7578-83cd-5f373b2293f5", "parentComponentId": null }, { "bbox": { "h": 0.6, "w": 0.88, "x": 0.06, "y": 0.285 }, "kind": "framework", "text": "Maturity Model", "attrs": null, "canon": { "kind": { "name": "Framework", "slug": "framework", "status": "active", "canonId": "019de52c-fa18-77c6-b10a-ccb8277ac0fa", "version": 1, "description": "Named conceptual framework instance." }, "tool": null, "subkind": { "name": "Framework instance", "slug": "instance", "status": "active", "canonId": "019de52d-05a2-72af-be0b-7edc60708a03", "version": 1, "description": null }, "framework": null }, "subkind": "instance", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:45.12+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "b10add85-039a-4bbd-bb9d-30a710a3d2f5", "parentComponentId": null }, { "bbox": { "h": 0.06, "w": 0.88, "x": 0.06, "y": 0.15 }, "kind": "paragraph", "text": "Establishing a baseline of team skills and technical capabilities helps you gain cross-organization alignment enabling you to set realistic goals for your future AI adoption.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:45.12+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "90d1130c-7ddf-48b9-a081-fd72011216ac", "parentComponentId": null }, { "bbox": { "h": 0.5, "w": 0.88, "x": 0.06, "y": 0.39 }, "kind": "table", "text": "Matrix of AI maturity stages across Strategic phase, Organizational focus, Policies, Staff skills, Implementation, and AI integration.", "attrs": null, "canon": { "kind": { "name": "Table", "slug": "table", "status": "active", "canonId": "019de52c-f9c8-7148-8119-eaac9594cd28", "version": 1, "description": "Tabular data layout." }, "tool": null, "subkind": { "name": "Data table", "slug": "data", "status": "active", "canonId": "019de52d-02d5-75b8-8abf-88e92bf63569", "version": 1, "description": null }, "framework": null }, "subkind": "data", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:45.12+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "baba6a98-80cd-457e-92dc-7ba08616a43f", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.35, "x": 0.06, "y": 0.08 }, "kind": "title", "text": "Creating an AI baseline", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:45.12+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "cd3741bc-2909-4c23-9e9b-76f48532088c", "parentComponentId": null } ], "metrics": [], "tools": [ { "tool": { "name": "The Rule of Three", "slug": "the-rule-of-three", "status": "active", "bestFor": null, "canonId": "019dd956-8962-75cf-b4f8-9394501a6f33", "version": 1, "bodyDocId": null, "description": "Ideas presented in threes are more memorable and satisfying", "familyLabel": null, "categoryName": "Block", "categorySlug": "block" }, "agent": "Storyteller", "layer": "block", "agents": [ "Storyteller" ], "matchId": "019de067-30ed-76da-a98a-aea84608c7fe", "evidence": "three maturity stages structure the slide", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 75, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 4, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Action Titles", "slug": "action-titles", "status": "active", "bestFor": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "canonId": "019dd956-ac70-700b-a608-ba58e78f5dcc", "version": 1, "bodyDocId": "816dad3c-9983-41c1-a86e-978ebd582841", "description": "The McKinsey-bred discipline of writing every slide title as a complete declarative sentence with a verb and an insight, not a topic label. Each title is a sub-claim that ladders up to the deck's governing thought; read in sequence, the titles reconstruct the executive summary.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019de067-306d-746a-a34e-5cd835368d3b", "evidence": "callout states the so-what about baselines and alignment", "pageRefs": null, "priority": "Core", "whenToUse": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "confidence": 70, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 4, "whyItWorks": "Solves two failure modes at once. (1) The buried claim: action titles place the conclusion on the page before any analysis is read, so a busy reader doesn't reverse-engineer it from the chart. (2) The spineless deck: because each title is a claim, slides have to ladder up to the governing thought; logical gaps become visible as topic-shaped titles in a sequence that no longer reads as a story.", "antipattern": "Topic labels disguised as titles — Volume by quarter, Key findings, Pricing strategy, Margins have been impacted. No verb, or a passive verb with no agent, or a fact (Revenue grew 12%) without the so-what. Also: titles that overreach the chart's evidence, multi-claim X-grew-but-Y-fell welded titles, and mechanical repetition of the same X-drove-Y template across the deck.", "cardinality": null, "narrativePurpose": "Forces the deck to carry its argument in the title bar so a senior reader can extract the recommendation without opening a single slide; converts a binder of topics into a navigable pyramid where every slide is a node defending the apex." }, { "tool": { "name": "Gestalt Principles", "slug": "gestalt-principles", "status": "active", "bestFor": null, "canonId": "019dd956-b266-7631-9b7e-44d83bd5d4f3", "version": 1, "bodyDocId": null, "description": "Proximity, Similarity, Enclosure, Continuity, Closure, Connection - how humans perceive visual groups", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer", "Architect" ], "matchId": "019de067-30c3-77e8-8ea7-8df651d17526", "evidence": "table grid uses proximity and similarity to group rows/columns", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 80, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 4, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Maturity model", "slug": "maturity-model", "status": "active", "bestFor": null, "canonId": "019de52d-1923-75fc-9be0-131883ed3458", "version": 1, "bodyDocId": null, "description": null, "familyLabel": null, "categoryName": null, "categorySlug": null }, "agent": null, "layer": "slide", "agents": null, "matchId": "1b8dd93f-d703-44ef-bc5e-ce4c7a827f17", "evidence": "type: maturity_model, framework/instance: Maturity Model", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.9, "extraction": { "at": "2026-07-16 21:55:50.38719+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 4, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Small Multiples", "slug": "small-multiples", "status": "active", "bestFor": null, "canonId": "019dd956-b32d-7586-b368-baa1dd388ed4", "version": 1, "bodyDocId": null, "description": "Repeating similar charts for comparison across categories or time", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019de067-3098-717c-a927-d022969fff56", "evidence": "Emerging/Developing/Mature columns repeat across 6 dimensions", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 85, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 4, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [ { "matchId": "312c5393-6805-4694-b79c-8e03193ac878", "evidence": "The slide presents a progression of organizational capabilities across three distinct stages.", "framework": null, "confidence": 1, "extraction": { "at": "2026-05-02 17:43:45.12+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 4, "frameworkName": "maturity-model" }, { "matchId": "019de067-3850-73bc-b6d4-3521384be794", "evidence": "Emerging / Developing / Mature stages across six capability dimensions", "framework": null, "confidence": 90, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 4, "frameworkName": "Maturity Model" } ], "arcBeats": [ { "to": 7, "arc": { "name": "AIDA", "slug": "aida", "status": "active", "bestFor": "Marketing presentations, product launches, sales enablement", "canonId": "019dd956-5fb4-77aa-866d-f9bdd47803af", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Attention -> Interest -> Desire -> Action", "description": null, "familyLabel": null }, "from": 4, "name": "Interest", "beatId": "019de067-2de5-70c8-806f-d7d7abb7ab0f", "matchId": "019de067-2d91-7264-a72e-b60277f83dc2", "beatType": null, "evidence": "maturity baseline, definitions, IDC adoption curve", "position": 2, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 72 }, { "to": 7, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null }, "from": 3, "name": "Situation & Context", "beatId": "019de067-2e91-718c-ad8f-08210928f992", "matchId": "019de067-2e65-73ce-8e5b-7d2ab9a39fa9", "beatType": null, "evidence": "definitions, baseline, market trajectory", "position": 1, "isPrimaryArc": false, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 48 } ], "loops": [ { "to": 7, "from": 3, "loop": { "name": "06_zoom_in", "slug": "06-zoom-in", "status": "active", "bestFor": "Technical deep-dives, case studies, detailed analysis", "canonId": "019dd956-6846-74db-82be-dff5b058b072", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Big Picture -> Key Area of Focus -> Specific Detail -> Implication", "description": "Start broad, then progressively focus on specific details that prove your point", "familyLabel": null }, "matchId": "019de067-2f9a-73ab-80d7-790e58b86a2f", "evidence": "p3 big picture intro -> p4 maturity focus -> p5-6 specific definitions -> p7 implication via IDC adoption curve.", "position": 1, "objective": "Establish what agentic AI is and where the market is going", "confidence": 70, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null } } ], "locked": true }, { "page": 5, "type": "analysis", "function": "present_framework", "rawType": "market_landscape", "block": null, "metadata": { "slideType": "market_landscape", "slideTypeCanon": { "name": "Market landscape", "slug": "market_landscape", "status": "active", "canonId": "019de52d-0b6d-75db-a946-9ac362e3afc2", "version": 1, "description": null }, "function": "present_framework", "functionCanon": { "name": "Present framework", "slug": "present_framework", "status": "active", "canonId": "019de52d-1403-7667-9100-d2ac6709f750", "version": 1, "description": null }, "density": "balanced", "densityScore": 32, "componentCount": 4, "textChars": 561, "nDataPoints": 0, "notes": null, "elementsJson": [ "headline_text", "paragraph", "icon_grid" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:43:45.22+00", "seconds": 2.71, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5c-b1fd37abc6e1/5", "deck": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1#slide-5", "deckJson": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1.json" }, "components": [ { "bbox": { "h": 0.15, "w": 0.7, "x": 0.15, "y": 0.35 }, "kind": "image", "text": null, "attrs": null, "canon": { "kind": { "name": "Image", "slug": "image", "status": "active", "canonId": "019de52c-f978-701f-a720-51d029d769e7", "version": 1, "description": "Photo, illustration, screenshot or icon." }, "tool": null, "subkind": { "name": "Icon grid", "slug": "icon-grid", "status": "active", "canonId": "019de52c-fdfe-749d-9990-1db465a3eed4", "version": 1, "description": null }, "framework": null }, "subkind": "icon-grid", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:45.22+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "36c21790-ba66-4b20-aa60-56ba51adff52", "parentComponentId": null }, { "bbox": { "h": 0.55, "w": 0.88, "x": 0.06, "y": 0.3 }, "kind": "list", "text": "Generative AI: Learns from historical data and produces new content; Follows a set of rules to automate repetitive tasks. AI Agents: Achieves a singular goal; Addresses broader range of tasks; Automates entire workflows. Agentic AI: Adapts and learns to make real-time decisions; Autonomous – AI Agents collaborate with each other to streamline workflows.", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Comparison list", "slug": "comparison", "status": "active", "canonId": "019de52c-fce7-733e-99d3-030a104727bf", "version": 1, "description": null }, "framework": null }, "subkind": "comparison", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:45.22+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "f32e6cf3-e15f-4ecf-b97f-1fc414ac1b8d", "parentComponentId": null }, { "bbox": { "h": 0.06, "w": 0.88, "x": 0.06, "y": 0.15 }, "kind": "paragraph", "text": "Agentic AI refers to the broad field of developing AI systems, capable of independent and adaptive goal-oriented activities and covering the development of AI agents.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:45.22+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "8e964ebe-11cc-4e95-a59d-134da105e608", "parentComponentId": null }, { "bbox": { "h": 0.04, "w": 0.45, "x": 0.06, "y": 0.08 }, "kind": "title", "text": "Generative AI, agentic AI, and AI agents", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:45.22+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "d4f16096-1232-4700-b45c-c17fcd6d818f", "parentComponentId": null } ], "metrics": [], "tools": [ { "tool": { "name": "The Rule of Three", "slug": "the-rule-of-three", "status": "active", "bestFor": null, "canonId": "019dd956-8962-75cf-b4f8-9394501a6f33", "version": 1, "bodyDocId": null, "description": "Ideas presented in threes are more memorable and satisfying", "familyLabel": null, "categoryName": "Block", "categorySlug": "block" }, "agent": "Storyteller", "layer": "block", "agents": [ "Storyteller" ], "matchId": "019de067-31d2-7101-80ed-615a3fbd26c1", "evidence": "Generative AI / AI Agents / Agentic AI triad", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 80, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 5, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Law of Similarity", "slug": "law-of-similarity", "status": "active", "bestFor": null, "canonId": "019dd956-c025-70d9-a411-8efa41ae179b", "version": 1, "bodyDocId": null, "description": "Similar-looking elements perceived as related - consistent styling for related concepts", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019de067-31aa-724c-a919-47dd67fceef1", "evidence": "three identically-styled cards mark the same level of abstraction", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 75, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 5, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "One Idea Rule", "slug": "one-idea-rule", "status": "active", "bestFor": null, "canonId": "019dd956-b0f0-7630-a2f5-bb38f9bd9c57", "version": 1, "bodyDocId": null, "description": "Each slide should communicate exactly one concept", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019de067-317f-73da-8e8c-afabaaf69fc0", "evidence": "single concept: definitional taxonomy", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 5, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Picture Superiority Effect", "slug": "picture-superiority-effect", "status": "active", "bestFor": null, "canonId": "019dd956-c201-7014-bb58-3e85e3e11dfd", "version": 1, "bodyDocId": null, "description": "Pictures remembered 6x better than words - prioritize visuals over text", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019de067-3118-7677-8fd0-f767e9f42374", "evidence": "icon-led cards anchor each definition", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 5, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 7, "arc": { "name": "AIDA", "slug": "aida", "status": "active", "bestFor": "Marketing presentations, product launches, sales enablement", "canonId": "019dd956-5fb4-77aa-866d-f9bdd47803af", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Attention -> Interest -> Desire -> Action", "description": null, "familyLabel": null }, "from": 4, "name": "Interest", "beatId": "019de067-2de5-70c8-806f-d7d7abb7ab0f", "matchId": "019de067-2d91-7264-a72e-b60277f83dc2", "beatType": null, "evidence": "maturity baseline, definitions, IDC adoption curve", "position": 2, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 72 }, { "to": 7, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null }, "from": 3, "name": "Situation & Context", "beatId": "019de067-2e91-718c-ad8f-08210928f992", "matchId": "019de067-2e65-73ce-8e5b-7d2ab9a39fa9", "beatType": null, "evidence": "definitions, baseline, market trajectory", "position": 1, "isPrimaryArc": false, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 48 } ], "loops": [ { "to": 7, "from": 3, "loop": { "name": "06_zoom_in", "slug": "06-zoom-in", "status": "active", "bestFor": "Technical deep-dives, case studies, detailed analysis", "canonId": "019dd956-6846-74db-82be-dff5b058b072", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Big Picture -> Key Area of Focus -> Specific Detail -> Implication", "description": "Start broad, then progressively focus on specific details that prove your point", "familyLabel": null }, "matchId": "019de067-2f9a-73ab-80d7-790e58b86a2f", "evidence": "p3 big picture intro -> p4 maturity focus -> p5-6 specific definitions -> p7 implication via IDC adoption curve.", "position": 1, "objective": "Establish what agentic AI is and where the market is going", "confidence": 70, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null } } ], "locked": true }, { "page": 6, "type": "setup", "function": "summarize", "rawType": "key_messages", "block": null, "metadata": { "slideType": "key_messages", "slideTypeCanon": { "name": "Key messages", "slug": "key_messages", "status": "active", "canonId": "019de52d-0712-703f-89f5-bda6688faf3f", "version": 1, "description": null }, "function": "summarize", "functionCanon": { "name": "Summarize", "slug": "summarize", "status": "active", "canonId": "019de52d-1541-704f-b86f-bf7b75056373", "version": 1, "description": null }, "density": "balanced", "densityScore": 34, "componentCount": 4, "textChars": 621, "nDataPoints": 0, "notes": null, "elementsJson": [ "headline_text", "bullet_list", "callout_box" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:43:45.083+00", "seconds": 2.549, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5c-b1fd37abc6e1/6", "deck": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1#slide-6", "deckJson": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1.json" }, "components": [ { "bbox": null, "kind": "callout", "text": "Agentic AI can provide personalized experiences and anticipate user needs, driving customer satisfaction.", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-25 11:59:00+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-41aa-7578-83cc-806bacfcce24", "parentComponentId": null }, { "bbox": { "h": 0.3, "w": 0.7, "x": 0.08, "y": 0.38 }, "kind": "list", "text": "Learns, adapts, and makes real-time decisions to achieve goals\nEvaluates available information\nConsults relevant knowledge bases\nBreaks down complex requests into logical steps\nOrchestrates necessary actions within complex multi-faceted workflows\nMaintains security and compliance\nImplement using AWS native agents, Opensource, 3P enterprises and more", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:45.083+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "e2bf73b1-6f83-4456-9f9b-e2f85e92c2b7", "parentComponentId": null }, { "bbox": { "h": 0.06, "w": 0.8, "x": 0.06, "y": 0.15 }, "kind": "paragraph", "text": "Agentic AI can provide personalized experiences and anticipate user needs, driving customer satisfaction. Here is a closer look at agentic AI.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:45.083+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "6937c0e4-cc3d-44a6-a0f2-551386e7211e", "parentComponentId": null }, { "bbox": { "h": 0.04, "w": 0.3, "x": 0.06, "y": 0.08 }, "kind": "title", "text": "Agentic AI capabilities", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:45.083+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "776ad830-861c-49e6-a82e-fa42e72737bc", "parentComponentId": null } ], "metrics": [], "tools": [ { "tool": { "name": "Chunking", "slug": "chunking", "status": "active", "bestFor": null, "canonId": "019dd956-abab-72ce-b64c-2924cc83cf39", "version": 1, "bodyDocId": null, "description": "Information grouped into chunks is remembered better - structure content in digestible units", "familyLabel": null, "categoryName": "Loop", "categorySlug": "loop" }, "agent": "Architect", "layer": "loop", "agents": [ "Architect" ], "matchId": "019de067-31fc-77ca-a448-08cd477f19d5", "evidence": "capabilities listed as digestible bullets", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 65, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 6, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "So What? Test", "slug": "so-what-test", "status": "active", "bestFor": "On every slide carrying a chart, number, list, or finding intended to inform a decision; whenever a draft title is descriptive rather than directive; whenever the deck will circulate without its author.", "canonId": "019dd956-acd2-76f8-b59a-9bf15a89f10a", "version": 1, "bodyDocId": "fec04b06-b2f1-432b-a97b-916dc7563f64", "description": "The recursive editorial discipline of asking so-what of every slide, chart, and statement until the answer is an implication for the audience — that final answer becomes the slide's title; the chain becomes its body.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019de067-3227-72ba-931a-a14e64c1a053", "evidence": "callout converts capability list into customer outcome", "pageRefs": null, "priority": "Core", "whenToUse": "On every slide carrying a chart, number, list, or finding intended to inform a decision; whenever a draft title is descriptive rather than directive; whenever the deck will circulate without its author.", "confidence": 65, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 6, "whyItWorks": "Solves the two failure modes of analytical communication at once: stopping at description (analyst-confidence problem) and leaving insight stranded in the analyst's head (translation problem). The recursion is what guarantees the implication makes it into ink.", "antipattern": "Stopping at the first tighter description (still a fact, not an implication), regressing past the audience's decision space into philosophy, smuggling the so-what into speaker notes, or re-using an implication aimed at a previous audience.", "cardinality": null, "narrativePurpose": "Forces every analytical artefact to close the gap between fact and decision, so the reader holds the recommendation by reading titles alone rather than reconstructing the analyst's mental model from raw evidence." } ], "frameworks": [], "arcBeats": [ { "to": 7, "arc": { "name": "AIDA", "slug": "aida", "status": "active", "bestFor": "Marketing presentations, product launches, sales enablement", "canonId": "019dd956-5fb4-77aa-866d-f9bdd47803af", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Attention -> Interest -> Desire -> Action", "description": null, "familyLabel": null }, "from": 4, "name": "Interest", "beatId": "019de067-2de5-70c8-806f-d7d7abb7ab0f", "matchId": "019de067-2d91-7264-a72e-b60277f83dc2", "beatType": null, "evidence": "maturity baseline, definitions, IDC adoption curve", "position": 2, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 72 }, { "to": 7, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null }, "from": 3, "name": "Situation & Context", "beatId": "019de067-2e91-718c-ad8f-08210928f992", "matchId": "019de067-2e65-73ce-8e5b-7d2ab9a39fa9", "beatType": null, "evidence": "definitions, baseline, market trajectory", "position": 1, "isPrimaryArc": false, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 48 } ], "loops": [ { "to": 7, "from": 3, "loop": { "name": "06_zoom_in", "slug": "06-zoom-in", "status": "active", "bestFor": "Technical deep-dives, case studies, detailed analysis", "canonId": "019dd956-6846-74db-82be-dff5b058b072", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Big Picture -> Key Area of Focus -> Specific Detail -> Implication", "description": "Start broad, then progressively focus on specific details that prove your point", "familyLabel": null }, "matchId": "019de067-2f9a-73ab-80d7-790e58b86a2f", "evidence": "p3 big picture intro -> p4 maturity focus -> p5-6 specific definitions -> p7 implication via IDC adoption curve.", "position": 1, "objective": "Establish what agentic AI is and where the market is going", "confidence": 70, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null } } ], "locked": true }, { "page": 7, "type": "analysis", "title": "The slide uses a maturity model/evolutionary framework to map the transition from traditional software to agentic AI.", "function": "present_framework", "rawType": "industry_trends", "block": null, "metadata": { "slideType": "industry_trends", "slideTypeCanon": { "name": "Industry trends", "slug": "industry_trends", "status": "active", "canonId": "019de52d-0b1d-7705-a0e0-c663199cd1fa", "version": 1, "description": null }, "function": "present_framework", "functionCanon": { "name": "Present framework", "slug": "present_framework", "status": "active", "canonId": "019de52d-1403-7667-9100-d2ac6709f750", "version": 1, "description": null }, "density": "dense", "densityScore": 64, "componentCount": 7, "textChars": 571, "nDataPoints": 36, "notes": "The slide uses a maturity model/evolutionary framework to map the transition from traditional software to agentic AI.", "elementsJson": [ "paragraph", "infographic" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:43:46.159+00", "seconds": 3.16, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5c-b1fd37abc6e1/7", "deck": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1#slide-7", "deckJson": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1.json" }, "components": [ { "bbox": null, "kind": "callout", "text": "The following IDC Market Presentation illustrates how generative and agentic AI are expected to transform the way enterprise applications are designed, delivered, and engaged with by users.", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-25 11:59:00+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-41aa-7578-83cc-a9785b18b679", "parentComponentId": null }, { "bbox": { "h": 0.45, "w": 0.78, "x": 0.11, "y": 0.35 }, "kind": "chart", "text": "Adoption curve over time", "attrs": null, "canon": { "kind": { "name": "Chart", "slug": "chart", "status": "active", "canonId": "019de52c-f9a0-76ef-adc6-0b859109d1f8", "version": 1, "description": "Quantitative chart." }, "tool": null, "subkind": { "name": "Line chart", "slug": "line", "status": "active", "canonId": "019de52c-ff62-778f-8f6c-a952ceae8677", "version": 1, "description": null }, "framework": null }, "subkind": "line", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:46.159+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "ec5fcbfc-1bb8-42f0-9179-0642c264c280", "parentComponentId": null }, { "bbox": { "h": 0.55, "w": 0.88, "x": 0.06, "y": 0.305 }, "kind": "framework", "text": "The Agentic Evolution of Enterprise Applications", "attrs": null, "canon": { "kind": { "name": "Framework", "slug": "framework", "status": "active", "canonId": "019de52c-fa18-77c6-b10a-ccb8277ac0fa", "version": 1, "description": "Named conceptual framework instance." }, "tool": null, "subkind": { "name": "Framework instance", "slug": "instance", "status": "active", "canonId": "019de52d-05a2-72af-be0b-7edc60708a03", "version": 1, "description": null }, "framework": null }, "subkind": "instance", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:46.159+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "871307e8-f178-4b68-a15f-3941312bed4a", "parentComponentId": null }, { "bbox": null, "kind": "metric", "text": "Adoption level", "attrs": null, "canon": { "kind": { "name": "Metric", "slug": "metric", "status": "active", "canonId": "019de52c-f923-73bf-8081-d0b1a8c5264d", "version": 1, "description": "Big-number or KPI value." }, "tool": { "name": "Quantification", "slug": "quantification", "status": "active", "bestFor": null, "canonId": "019dd9e1-47ab-72ce-a079-aab1f5299e88", "version": 1, "bodyDocId": null, "description": "Translating a claim into numbers, charts, or tables.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-25 11:59:00+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-41aa-7578-83cc-ac394e8bfbe6", "parentComponentId": null }, { "bbox": { "h": 0.06, "w": 0.88, "x": 0.06, "y": 0.18 }, "kind": "paragraph", "text": "The following IDC Market Presentation illustrates how generative and agentic AI are expected to transform the way enterprise applications are designed, delivered, and engaged with by users.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:46.159+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "ce898182-3a73-4a0f-bcde-8716e38e623c", "parentComponentId": null }, { "bbox": { "h": 0.02, "w": 0.4, "x": 0.06, "y": 0.91 }, "kind": "source-note", "text": "IDC, the Agentic Evolution of Enterprise Applications, doc#US53194625, Feb 2025", "attrs": null, "canon": { "kind": { "name": "Source note", "slug": "source-note", "status": "active", "canonId": "23484952-494b-4a5e-b1ad-550d0d70e948", "version": 1, "description": "Attribution / source / caveat placed at the slide footer. Numbered footnotes use attrs.numbered." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:46.159+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "faeb4f37-67e5-4cd9-8ec9-5937c3b1c96f", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.35, "x": 0.06, "y": 0.08 }, "kind": "title", "text": "Evolution of AI applications", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:46.159+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "202e5ca5-a422-46c3-a39f-ac703b3fbaf3", "parentComponentId": null } ], "metrics": [], "tools": [ { "tool": { "name": "Annotation", "slug": "annotation", "status": "active", "bestFor": null, "canonId": "019dd956-b5b9-7668-bf0e-3af99823ec5c", "version": 1, "bodyDocId": null, "description": "Adding explanatory labels to highlight key data points", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019de067-327b-77f8-b7b8-bddbc3be7120", "evidence": "stage labels and percentages annotate the curve", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 7, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Credibility Transfer", "slug": "credibility-transfer", "status": "active", "bestFor": null, "canonId": "019dd956-bd34-759a-8e3b-2f14b571a2a1", "version": 1, "bodyDocId": null, "description": "Borrowing authority from trusted sources or vivid details", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019de067-32a5-708c-897b-239456fe1f49", "evidence": "IDC source explicitly cited under chart", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 80, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 7, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Picture Superiority Effect", "slug": "picture-superiority-effect", "status": "active", "bestFor": null, "canonId": "019dd956-c201-7014-bb58-3e85e3e11dfd", "version": 1, "bodyDocId": null, "description": "Pictures remembered 6x better than words - prioritize visuals over text", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019de067-3251-71ba-a6fe-cc37d93889f6", "evidence": "IDC S-curve dominates the slide", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 75, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 7, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "SCQA Framework", "slug": "scqa-framework", "status": "active", "bestFor": null, "canonId": "019dd956-7bcb-763f-bdf6-1dfedf3bd36c", "version": 1, "bodyDocId": "019df22a-a0b0-719e-937e-2ac31e53d32c", "description": "Situation, Complication, Question, Answer - structured problem framing", "familyLabel": null, "categoryName": "Block", "categorySlug": "block" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "15ba7849-e4b0-4486-95ad-feb0806976b3", "evidence": "chart/line: Adoption curve over time", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 21:55:50.561235+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 7, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [ { "matchId": "019de067-38a5-77da-b6be-271a06ff7fc0", "evidence": "explicit six-stage IDC framework labelled on chart", "framework": null, "confidence": 85, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 7, "frameworkName": "IDC Agentic Evolution of Enterprise Applications" }, { "matchId": "103b3530-3d03-422a-8f92-af59986fac25", "evidence": "The slide maps the evolution of enterprise applications through distinct stages of AI adoption over time.", "framework": null, "confidence": 0.9, "extraction": { "at": "2026-05-02 17:43:46.159+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 7, "frameworkName": "maturity-model" }, { "matchId": "019de067-387a-73c3-8658-95051565e187", "evidence": "IDC chart shows adoption percentages on an S-curve across 2025-2037", "framework": null, "confidence": 70, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 7, "frameworkName": "S-Curve Adoption Model" } ], "arcBeats": [ { "to": 7, "arc": { "name": "AIDA", "slug": "aida", "status": "active", "bestFor": "Marketing presentations, product launches, sales enablement", "canonId": "019dd956-5fb4-77aa-866d-f9bdd47803af", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Attention -> Interest -> Desire -> Action", "description": null, "familyLabel": null }, "from": 4, "name": "Interest", "beatId": "019de067-2de5-70c8-806f-d7d7abb7ab0f", "matchId": "019de067-2d91-7264-a72e-b60277f83dc2", "beatType": null, "evidence": "maturity baseline, definitions, IDC adoption curve", "position": 2, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 72 }, { "to": 7, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null }, "from": 3, "name": "Situation & Context", "beatId": "019de067-2e91-718c-ad8f-08210928f992", "matchId": "019de067-2e65-73ce-8e5b-7d2ab9a39fa9", "beatType": null, "evidence": "definitions, baseline, market trajectory", "position": 1, "isPrimaryArc": false, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 48 } ], "loops": [ { "to": 7, "from": 3, "loop": { "name": "06_zoom_in", "slug": "06-zoom-in", "status": "active", "bestFor": "Technical deep-dives, case studies, detailed analysis", "canonId": "019dd956-6846-74db-82be-dff5b058b072", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Big Picture -> Key Area of Focus -> Specific Detail -> Implication", "description": "Start broad, then progressively focus on specific details that prove your point", "familyLabel": null }, "matchId": "019de067-2f9a-73ab-80d7-790e58b86a2f", "evidence": "p3 big picture intro -> p4 maturity focus -> p5-6 specific definitions -> p7 implication via IDC adoption curve.", "position": 1, "objective": "Establish what agentic AI is and where the market is going", "confidence": 70, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null } } ], "locked": true }, { "page": 8, "type": "evidence", "title": "The slide uses a three-column layout to present different content types (Blog, Article, Video) as examples of agentic AI implementation.", "function": "illustrate_case", "rawType": "client_example", "block": null, "metadata": { "slideType": "client_example", "slideTypeCanon": { "name": "Client example", "slug": "client_example", "status": "active", "canonId": "019de52d-0c87-77cb-9867-613ae22e95ac", "version": 1, "description": null }, "function": "illustrate_case", "functionCanon": { "name": "Illustrate case", "slug": "illustrate_case", "status": "active", "canonId": "019de52d-13b4-772c-bb73-1873612a7463", "version": 1, "description": null }, "density": "dense", "densityScore": 68, "componentCount": 9, "textChars": 595, "nDataPoints": 0, "notes": "The slide uses a three-column layout to present different content types (Blog, Article, Video) as examples of agentic AI implementation.", "elementsJson": [ "headline_text", "paragraph", "callout_box" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:43:45.9+00", "seconds": 2.807, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5c-b1fd37abc6e1/8", "deck": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1#slide-8", "deckJson": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1.json" }, "components": [ { "bbox": null, "kind": "callout", "text": "The journey to implementing agentic AI solutions takes different paths depending on your organizational needs and technical maturity.", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-25 11:59:01+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-41aa-7578-83cd-30f1f4811f0c", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.25, "x": 0.37, "y": 0.34 }, "kind": "list", "text": "Agentic AI implementation patterns", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:45.9+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "94624bc2-c89d-472e-acc2-e55c323366ee", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.25, "x": 0.66, "y": 0.34 }, "kind": "list", "text": "Salesforce customer experience evolution", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:45.9+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "a94d96e7-a276-4c3f-93c3-1fc84b774e6a", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.25, "x": 0.07, "y": 0.34 }, "kind": "list", "text": "Twitch's ad sales transformation", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:45.9+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "e51ec0e0-3c81-4429-b920-5e720b584975", "parentComponentId": null }, { "bbox": { "h": 0.02, "w": 0.05, "x": 0.4, "y": 0.29 }, "kind": "other", "text": "ARTICLE", "attrs": null, "canon": { "kind": { "name": "Other", "slug": "other", "status": "active", "canonId": "019de52c-fa90-743c-8bf6-20d1fbe82b6d", "version": 1, "description": "Fallback when no canonical kind applies." }, "tool": null, "subkind": { "name": "Unclassified", "slug": "unclassified", "status": "active", "canonId": "019de52d-05ca-77db-81fb-db7d4234bbc0", "version": 1, "description": null }, "framework": null }, "subkind": "unclassified", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:45.9+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "39470ef0-c353-4533-acda-5dfb20e1ddde", "parentComponentId": null }, { "bbox": { "h": 0.02, "w": 0.05, "x": 0.09, "y": 0.29 }, "kind": "other", "text": "BLOG", "attrs": null, "canon": { "kind": { "name": "Other", "slug": "other", "status": "active", "canonId": "019de52c-fa90-743c-8bf6-20d1fbe82b6d", "version": 1, "description": "Fallback when no canonical kind applies." }, "tool": null, "subkind": { "name": "Unclassified", "slug": "unclassified", "status": "active", "canonId": "019de52d-05ca-77db-81fb-db7d4234bbc0", "version": 1, "description": null }, "framework": null }, "subkind": "unclassified", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:45.9+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "6a21d0c3-1619-4251-ac2e-b2e832ef3c22", "parentComponentId": null }, { "bbox": { "h": 0.02, "w": 0.05, "x": 0.69, "y": 0.29 }, "kind": "other", "text": "VIDEO", "attrs": null, "canon": { "kind": { "name": "Other", "slug": "other", "status": "active", "canonId": "019de52c-fa90-743c-8bf6-20d1fbe82b6d", "version": 1, "description": "Fallback when no canonical kind applies." }, "tool": null, "subkind": { "name": "Unclassified", "slug": "unclassified", "status": "active", "canonId": "019de52d-05ca-77db-81fb-db7d4234bbc0", "version": 1, "description": null }, "framework": null }, "subkind": "unclassified", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:45.9+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "d8269566-9ac0-44b7-99db-6eb04f54278c", "parentComponentId": null }, { "bbox": { "h": 0.08, "w": 0.88, "x": 0.06, "y": 0.18 }, "kind": "paragraph", "text": "The journey to implementing agentic AI solutions takes different paths depending on your organizational needs and technical maturity. Through real-world implementations, we can understand how organizations navigate this transformation. See how AWS customers and Partners are innovating with agentic applications.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:45.9+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "310341ef-53e3-4755-83aa-960c39a2c6dd", "parentComponentId": null }, { "bbox": { "h": 0.04, "w": 0.35, "x": 0.06, "y": 0.08 }, "kind": "title", "text": "Real-world agentic AI on AWS", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:45.9+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "3d1b1604-ed07-4ab6-9720-4d86e6c0aa76", "parentComponentId": null } ], "metrics": [], "tools": [ { "tool": { "name": "Inductive Reasoning", "slug": "inductive-reasoning", "status": "active", "bestFor": null, "canonId": "019dd956-99c6-705e-94cc-76a504c3da37", "version": 1, "bodyDocId": null, "description": "Grouping similar evidence to form a conclusion (Evidence → Pattern → Conclusion)", "familyLabel": null, "categoryName": "Loop", "categorySlug": "loop" }, "agent": "Architect", "layer": "loop", "agents": [ "Architect" ], "matchId": "019de067-32ce-7747-ac66-c7599c80b6a1", "evidence": "loop opens with first set of customer cases pointing to a pattern", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 8, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Action Titles", "slug": "action-titles", "status": "active", "bestFor": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "canonId": "019dd956-ac70-700b-a608-ba58e78f5dcc", "version": 1, "bodyDocId": "816dad3c-9983-41c1-a86e-978ebd582841", "description": "The McKinsey-bred discipline of writing every slide title as a complete declarative sentence with a verb and an insight, not a topic label. Each title is a sub-claim that ladders up to the deck's governing thought; read in sequence, the titles reconstruct the executive summary.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019de067-3321-71e9-8d33-008ec2276cbc", "evidence": "kicker frames the takeaway as real-world proof", "pageRefs": null, "priority": "Core", "whenToUse": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "confidence": 60, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 8, "whyItWorks": "Solves two failure modes at once. (1) The buried claim: action titles place the conclusion on the page before any analysis is read, so a busy reader doesn't reverse-engineer it from the chart. (2) The spineless deck: because each title is a claim, slides have to ladder up to the governing thought; logical gaps become visible as topic-shaped titles in a sequence that no longer reads as a story.", "antipattern": "Topic labels disguised as titles — Volume by quarter, Key findings, Pricing strategy, Margins have been impacted. No verb, or a passive verb with no agent, or a fact (Revenue grew 12%) without the so-what. Also: titles that overreach the chart's evidence, multi-claim X-grew-but-Y-fell welded titles, and mechanical repetition of the same X-drove-Y template across the deck.", "cardinality": null, "narrativePurpose": "Forces the deck to carry its argument in the title bar so a senior reader can extract the recommendation without opening a single slide; converts a binder of topics into a navigable pyramid where every slide is a node defending the apex." }, { "tool": { "name": "Social Validation", "slug": "social-validation", "status": "active", "bestFor": null, "canonId": "019dd956-ddaa-77f9-890c-a1cf082c5ccd", "version": 1, "bodyDocId": null, "description": "Showing others have done something, especially similar others", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019de067-32f7-727f-93c0-36189c962e45", "evidence": "names AWS customers using Bedrock Agents", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 75, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 8, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 17, "arc": { "name": "AIDA", "slug": "aida", "status": "active", "bestFor": "Marketing presentations, product launches, sales enablement", "canonId": "019dd956-5fb4-77aa-866d-f9bdd47803af", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Attention -> Interest -> Desire -> Action", "description": null, "familyLabel": null }, "from": 8, "name": "Desire", "beatId": "019de067-2e0e-73a0-a9c0-e2dabafb5391", "matchId": "019de067-2d91-7264-a72e-b60277f83dc2", "beatType": null, "evidence": "case studies, industries, AWS services, AgentCore stack", "position": 3, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 72 }, { "to": 10, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null }, "from": 8, "name": "Evidence & Proof", "beatId": "019de067-2f0b-75a8-a4c5-7bf47096cd46", "matchId": "019de067-2e65-73ce-8e5b-7d2ab9a39fa9", "beatType": null, "evidence": "real-world AWS Bedrock customer case studies", "position": 4, "isPrimaryArc": false, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 48 } ], "loops": [ { "to": 10, "from": 8, "loop": { "name": "02_pattern_hunter", "slug": "02-pattern-hunter", "status": "active", "bestFor": "Time-pressed audiences, building consensus, when data is strong", "canonId": "019dd956-6695-771a-be2e-f1748ef041a4", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion", "description": "Group multiple pieces of evidence that together point to a pattern or conclusion", "familyLabel": null }, "matchId": "019de067-2fc3-7307-8ea6-467bf0022b73", "evidence": "Three slides stack customer cases and industry examples that converge on the pattern that agentic AI is delivering today.", "position": 2, "objective": "Show real-world adoption proves agentic AI works", "confidence": 75, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null } } ], "locked": true }, { "page": 9, "type": "evidence", "title": "The slide uses a structured grid to demonstrate the application of agentic AI across different sectors.", "function": "illustrate_case", "rawType": "client_example", "block": null, "metadata": { "slideType": "client_example", "slideTypeCanon": { "name": "Client example", "slug": "client_example", "status": "active", "canonId": "019de52d-0c87-77cb-9867-613ae22e95ac", "version": 1, "description": null }, "function": "illustrate_case", "functionCanon": { "name": "Illustrate case", "slug": "illustrate_case", "status": "active", "canonId": "019de52d-13b4-772c-bb73-1873612a7463", "version": 1, "description": null }, "density": "sparse", "densityScore": 24, "componentCount": 3, "textChars": 468, "nDataPoints": 0, "notes": "The slide uses a structured grid to demonstrate the application of agentic AI across different sectors.", "elementsJson": [ "headline_text", "paragraph", "icon_grid", "comparison_table" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:43:45.262+00", "seconds": 2.037, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5c-b1fd37abc6e1/9", "deck": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1#slide-9", "deckJson": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1.json" }, "components": [ { "bbox": { "h": 0.12, "w": 0.88, "x": 0.06, "y": 0.16 }, "kind": "paragraph", "text": "Why is agentic AI more capable and impactful in data-intense industries? Historically, data-rich industries face a variety of challenges that agentic AI can help solve. Using innovative strategies to harness this technology is resulting in incredible advancements. Here are just a few examples of agentic AI in action.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:45.262+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "5044456c-d5fa-4d3c-9184-30c6ac175cc2", "parentComponentId": null }, { "bbox": { "h": 0.55, "w": 0.88, "x": 0.06, "y": 0.35 }, "kind": "table", "text": "Industry and Use case mapping for Healthcare, Transportation, Financial services, Manufacturing, and Customer service.", "attrs": null, "canon": { "kind": { "name": "Table", "slug": "table", "status": "active", "canonId": "019de52c-f9c8-7148-8119-eaac9594cd28", "version": 1, "description": "Tabular data layout." }, "tool": null, "subkind": { "name": "Data table", "slug": "data", "status": "active", "canonId": "019de52d-02d5-75b8-8abf-88e92bf63569", "version": 1, "description": null }, "framework": null }, "subkind": "data", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:45.262+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "5de384a2-bb81-453f-ab31-78a29a7afaf4", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.45, "x": 0.06, "y": 0.08 }, "kind": "title", "text": "Agentic AI for data-intense jobs", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:45.262+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "26350836-335a-43f7-b2db-ef0a79cc1021", "parentComponentId": null } ], "metrics": [], "tools": [ { "tool": { "name": "Color Strategy", "slug": "color-strategy", "status": "active", "bestFor": null, "canonId": "019dd956-b202-77cf-8a6e-f445b08c0fd3", "version": 1, "bodyDocId": null, "description": "Using color for emphasis, categories, sentiment, and hierarchy", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019de067-33b5-7374-9c77-b74d32860452", "evidence": "purple gradient on industry headers separates from white use-case rows", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 9, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Gestalt Principles", "slug": "gestalt-principles", "status": "active", "bestFor": null, "canonId": "019dd956-b266-7631-9b7e-44d83bd5d4f3", "version": 1, "bodyDocId": null, "description": "Proximity, Similarity, Enclosure, Continuity, Closure, Connection - how humans perceive visual groups", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer", "Architect" ], "matchId": "019de067-33df-76de-913d-67f143c613c1", "evidence": "icon-over-label-over-cell groups via proximity", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 9, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Small Multiples", "slug": "small-multiples", "status": "active", "bestFor": null, "canonId": "019dd956-b32d-7586-b368-baa1dd388ed4", "version": 1, "bodyDocId": null, "description": "Repeating similar charts for comparison across categories or time", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019de067-338c-7258-84f8-d5d1142264b9", "evidence": "five identical industry/use-case columns", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 85, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 9, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 17, "arc": { "name": "AIDA", "slug": "aida", "status": "active", "bestFor": "Marketing presentations, product launches, sales enablement", "canonId": "019dd956-5fb4-77aa-866d-f9bdd47803af", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Attention -> Interest -> Desire -> Action", "description": null, "familyLabel": null }, "from": 8, "name": "Desire", "beatId": "019de067-2e0e-73a0-a9c0-e2dabafb5391", "matchId": "019de067-2d91-7264-a72e-b60277f83dc2", "beatType": null, "evidence": "case studies, industries, AWS services, AgentCore stack", "position": 3, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 72 }, { "to": 9, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null }, "from": 9, "name": "Problem & Complication", "beatId": "019de067-2eb9-76ff-93b5-9b6d0c143e1b", "matchId": "019de067-2e65-73ce-8e5b-7d2ab9a39fa9", "beatType": null, "evidence": "data-rich industries face challenges agentic AI solves", "position": 2, "isPrimaryArc": false, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 48 }, { "to": 10, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null }, "from": 8, "name": "Evidence & Proof", "beatId": "019de067-2f0b-75a8-a4c5-7bf47096cd46", "matchId": "019de067-2e65-73ce-8e5b-7d2ab9a39fa9", "beatType": null, "evidence": "real-world AWS Bedrock customer case studies", "position": 4, "isPrimaryArc": false, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 48 } ], "loops": [ { "to": 10, "from": 8, "loop": { "name": "02_pattern_hunter", "slug": "02-pattern-hunter", "status": "active", "bestFor": "Time-pressed audiences, building consensus, when data is strong", "canonId": "019dd956-6695-771a-be2e-f1748ef041a4", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion", "description": "Group multiple pieces of evidence that together point to a pattern or conclusion", "familyLabel": null }, "matchId": "019de067-2fc3-7307-8ea6-467bf0022b73", "evidence": "Three slides stack customer cases and industry examples that converge on the pattern that agentic AI is delivering today.", "position": 2, "objective": "Show real-world adoption proves agentic AI works", "confidence": 75, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null } } ], "locked": true }, { "page": 10, "type": "evidence", "function": "illustrate_case", "rawType": "client_example", "block": null, "metadata": { "slideType": "client_example", "slideTypeCanon": { "name": "Client example", "slug": "client_example", "status": "active", "canonId": "019de52d-0c87-77cb-9867-613ae22e95ac", "version": 1, "description": null }, "function": "illustrate_case", "functionCanon": { "name": "Illustrate case", "slug": "illustrate_case", "status": "active", "canonId": "019de52d-13b4-772c-bb73-1873612a7463", "version": 1, "description": null }, "density": "sparse", "densityScore": 23, "componentCount": 4, "textChars": 334, "nDataPoints": 0, "notes": null, "elementsJson": [ "paragraph", "icon_grid" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:43:45.149+00", "seconds": 1.885, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5c-b1fd37abc6e1/10", "deck": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1#slide-10", "deckJson": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1.json" }, "components": [ { "bbox": null, "kind": "callout", "text": "Adopting agentic AI in data-intensive scenarios can transform your organization.", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-25 11:59:00+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-41aa-7578-83cc-efaca53adabb", "parentComponentId": null }, { "bbox": { "h": 0.6, "w": 0.9, "x": 0.06, "y": 0.28 }, "kind": "list", "text": "Transforming Patient Care Coordination; Accelerating Research Through Intelligent Automation; Building Production-Grade Agentic Applications", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:45.149+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "3586eb69-5ac1-4c83-812e-2afc3a67e9f3", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.6, "x": 0.06, "y": 0.18 }, "kind": "paragraph", "text": "Adopting agentic AI in data-intensive scenarios can transform your organization.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:45.149+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "9f7bd021-e861-4f0d-a95a-5d7c04a3ca38", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.45, "x": 0.06, "y": 0.08 }, "kind": "title", "text": "Enabling data-rich implementations", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:45.149+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "55b3ddb7-245f-4bd7-a915-6b7e45a353dc", "parentComponentId": null } ], "metrics": [], "tools": [ { "tool": { "name": "Social Proof", "slug": "social-proof", "status": "active", "bestFor": null, "canonId": "019dd956-990d-7620-82b3-6dd286f34568", "version": 1, "bodyDocId": null, "description": "People adapt behavior based on what others do - show adoption and testimonials", "familyLabel": null, "categoryName": "Block", "categorySlug": "block" }, "agent": "Storyteller", "layer": "block", "agents": [ "Storyteller" ], "matchId": "019de067-3408-72c1-9d04-c85883bf6664", "evidence": "three real implementation examples in healthcare and HPC given as proof", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 10, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Action Titles", "slug": "action-titles", "status": "active", "bestFor": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "canonId": "019dd956-ac70-700b-a608-ba58e78f5dcc", "version": 1, "bodyDocId": "816dad3c-9983-41c1-a86e-978ebd582841", "description": "The McKinsey-bred discipline of writing every slide title as a complete declarative sentence with a verb and an insight, not a topic label. Each title is a sub-claim that ladders up to the deck's governing thought; read in sequence, the titles reconstruct the executive summary.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019de067-3431-74ac-9352-f52906326d52", "evidence": "callout asserts agentic AI can transform your organization", "pageRefs": null, "priority": "Core", "whenToUse": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "confidence": 65, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 10, "whyItWorks": "Solves two failure modes at once. (1) The buried claim: action titles place the conclusion on the page before any analysis is read, so a busy reader doesn't reverse-engineer it from the chart. (2) The spineless deck: because each title is a claim, slides have to ladder up to the governing thought; logical gaps become visible as topic-shaped titles in a sequence that no longer reads as a story.", "antipattern": "Topic labels disguised as titles — Volume by quarter, Key findings, Pricing strategy, Margins have been impacted. No verb, or a passive verb with no agent, or a fact (Revenue grew 12%) without the so-what. Also: titles that overreach the chart's evidence, multi-claim X-grew-but-Y-fell welded titles, and mechanical repetition of the same X-drove-Y template across the deck.", "cardinality": null, "narrativePurpose": "Forces the deck to carry its argument in the title bar so a senior reader can extract the recommendation without opening a single slide; converts a binder of topics into a navigable pyramid where every slide is a node defending the apex." } ], "frameworks": [], "arcBeats": [ { "to": 17, "arc": { "name": "AIDA", "slug": "aida", "status": "active", "bestFor": "Marketing presentations, product launches, sales enablement", "canonId": "019dd956-5fb4-77aa-866d-f9bdd47803af", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Attention -> Interest -> Desire -> Action", "description": null, "familyLabel": null }, "from": 8, "name": "Desire", "beatId": "019de067-2e0e-73a0-a9c0-e2dabafb5391", "matchId": "019de067-2d91-7264-a72e-b60277f83dc2", "beatType": null, "evidence": "case studies, industries, AWS services, AgentCore stack", "position": 3, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 72 }, { "to": 10, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null }, "from": 8, "name": "Evidence & Proof", "beatId": "019de067-2f0b-75a8-a4c5-7bf47096cd46", "matchId": "019de067-2e65-73ce-8e5b-7d2ab9a39fa9", "beatType": null, "evidence": "real-world AWS Bedrock customer case studies", "position": 4, "isPrimaryArc": false, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 48 } ], "loops": [ { "to": 10, "from": 8, "loop": { "name": "02_pattern_hunter", "slug": "02-pattern-hunter", "status": "active", "bestFor": "Time-pressed audiences, building consensus, when data is strong", "canonId": "019dd956-6695-771a-be2e-f1748ef041a4", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "Evidence A -> Evidence B -> Evidence C -> Pattern/Conclusion", "description": "Group multiple pieces of evidence that together point to a pattern or conclusion", "familyLabel": null }, "matchId": "019de067-2fc3-7307-8ea6-467bf0022b73", "evidence": "Three slides stack customer cases and industry examples that converge on the pattern that agentic AI is delivering today.", "position": 2, "objective": "Show real-world adoption proves agentic AI works", "confidence": 75, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null } } ], "locked": true }, { "page": 11, "type": "setup", "function": "compare_options", "rawType": "strategic_options", "block": null, "metadata": { "slideType": "strategic_options", "slideTypeCanon": { "name": "Strategic options", "slug": "strategic_options", "status": "active", "canonId": "019de52d-0c0d-745a-8f0a-50898a91cc12", "version": 1, "description": null }, "function": "compare_options", "functionCanon": { "name": "Compare options", "slug": "compare_options", "status": "active", "canonId": "019de52d-167f-7038-aebc-70a9d2e0e33b", "version": 1, "description": null }, "density": "balanced", "densityScore": 28, "componentCount": 4, "textChars": 463, "nDataPoints": 0, "notes": null, "elementsJson": [ "headline_text", "paragraph", "comparison_table" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:43:45.471+00", "seconds": 1.989, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5c-b1fd37abc6e1/11", "deck": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1#slide-11", "deckJson": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1.json" }, "components": [ { "bbox": null, "kind": "callout", "text": "AWS is committed to being the best place to build and deploy the world's most trusted and useful agents.", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-25 11:59:00+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-41aa-7578-83cc-447d776d8bc7", "parentComponentId": null }, { "bbox": { "h": 0.55, "w": 0.88, "x": 0.06, "y": 0.3 }, "kind": "list", "text": "Agentic AI applications vs Build custom agents", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Comparison list", "slug": "comparison", "status": "active", "canonId": "019de52c-fce7-733e-99d3-030a104727bf", "version": 1, "description": null }, "framework": null }, "subkind": "comparison", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:45.471+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "d905d56c-24ae-470b-963d-5913ddeaddaf", "parentComponentId": null }, { "bbox": { "h": 0.08, "w": 0.88, "x": 0.06, "y": 0.15 }, "kind": "paragraph", "text": "AWS is committed to being the best place to build and deploy the world's most trusted and useful agents. Whether you need ready-to-deploy solutions or fully customizable frameworks, AWS provides flexible options to meet your organization's unique needs and capabilities.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:45.471+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "23f2646e-d98b-4368-8fcf-9e814098e8d2", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.5, "x": 0.06, "y": 0.08 }, "kind": "title", "text": "Choose your path to implement agents on AWS", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:45.471+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "859079ac-e294-46d1-95ab-33540d2b1a67", "parentComponentId": null } ], "metrics": [], "tools": [ { "tool": { "name": "Contrast Pairs", "slug": "contrast-pairs", "status": "active", "bestFor": null, "canonId": "019dd956-9b77-70d3-88b1-f34e26f60860", "version": 1, "bodyDocId": null, "description": "Creating tension through opposites: Before↔After, Problem↔Solution, Pain↔Relief", "familyLabel": null, "categoryName": "Loop", "categorySlug": "loop" }, "agent": "Storyteller", "layer": "loop", "agents": [ "Storyteller" ], "matchId": "019de067-345a-7543-be73-83b532cd8b9e", "evidence": "two-column Agentic AI applications vs Build custom agents", "pageRefs": null, "priority": "Core", "whenToUse": null, "confidence": 80, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 11, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Action Titles", "slug": "action-titles", "status": "active", "bestFor": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "canonId": "019dd956-ac70-700b-a608-ba58e78f5dcc", "version": 1, "bodyDocId": "816dad3c-9983-41c1-a86e-978ebd582841", "description": "The McKinsey-bred discipline of writing every slide title as a complete declarative sentence with a verb and an insight, not a topic label. Each title is a sub-claim that ladders up to the deck's governing thought; read in sequence, the titles reconstruct the executive summary.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019de067-34b0-753f-bf8c-af3c17d0f70b", "evidence": "title Choose your path to implement agents on AWS is directive", "pageRefs": null, "priority": "Core", "whenToUse": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "confidence": 70, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 11, "whyItWorks": "Solves two failure modes at once. (1) The buried claim: action titles place the conclusion on the page before any analysis is read, so a busy reader doesn't reverse-engineer it from the chart. (2) The spineless deck: because each title is a claim, slides have to ladder up to the governing thought; logical gaps become visible as topic-shaped titles in a sequence that no longer reads as a story.", "antipattern": "Topic labels disguised as titles — Volume by quarter, Key findings, Pricing strategy, Margins have been impacted. No verb, or a passive verb with no agent, or a fact (Revenue grew 12%) without the so-what. Also: titles that overreach the chart's evidence, multi-claim X-grew-but-Y-fell welded titles, and mechanical repetition of the same X-drove-Y template across the deck.", "cardinality": null, "narrativePurpose": "Forces the deck to carry its argument in the title bar so a senior reader can extract the recommendation without opening a single slide; converts a binder of topics into a navigable pyramid where every slide is a node defending the apex." }, { "tool": { "name": "Contrast Principle", "slug": "contrast-principle", "status": "active", "bestFor": null, "canonId": "019dd956-bf0f-73ae-b9df-e60508cdaa65", "version": 1, "bodyDocId": null, "description": "Higher visual weight draws attention - use contrast strategically for emphasis", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019de067-3483-7190-972e-5a76e2494274", "evidence": "binary side-by-side panels emphasize the choice", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 75, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 11, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [ { "matchId": "019de067-38ce-70ba-a30a-453db25c092f", "evidence": "two-column ready-to-deploy vs build custom choice", "framework": null, "confidence": 75, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 11, "frameworkName": "Buy vs Build Framework" } ], "arcBeats": [ { "to": 17, "arc": { "name": "AIDA", "slug": "aida", "status": "active", "bestFor": "Marketing presentations, product launches, sales enablement", "canonId": "019dd956-5fb4-77aa-866d-f9bdd47803af", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Attention -> Interest -> Desire -> Action", "description": null, "familyLabel": null }, "from": 8, "name": "Desire", "beatId": "019de067-2e0e-73a0-a9c0-e2dabafb5391", "matchId": "019de067-2d91-7264-a72e-b60277f83dc2", "beatType": null, "evidence": "case studies, industries, AWS services, AgentCore stack", "position": 3, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 72 }, { "to": 15, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null }, "from": 11, "name": "Solution & Approach", "beatId": "019de067-2ee2-737f-92ef-11630c0cfd36", "matchId": "019de067-2e65-73ce-8e5b-7d2ab9a39fa9", "beatType": null, "evidence": "Choose path, AgentCore, OSS frameworks, MCP", "position": 3, "isPrimaryArc": false, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 48 } ], "loops": [ { "to": 15, "from": 11, "loop": { "name": "33_build_up", "slug": "33-build-up", "status": "active", "bestFor": "Pricing justification, cost estimation, market sizing", "canonId": "019dd956-733a-746e-88fd-04b2e4b51b61", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Base -> Add Component A -> Add Component B -> Add Component C -> The Total", "description": "Start from zero and add components to arrive at a total", "familyLabel": null }, "matchId": "019de067-2fec-767b-9083-66d2218cde61", "evidence": "Base choice (p11) + AgentCore (p12) + service modules (p13) + OSS frameworks (p14) + MCP (p15) sums to full AWS offering.", "position": 3, "objective": "Build up the AWS agentic stack as a complete solution", "confidence": 72, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null } } ], "locked": true }, { "page": 12, "type": "resolution", "function": "summarize", "rawType": "key_takeaways", "block": null, "metadata": { "slideType": "key_takeaways", "slideTypeCanon": { "name": "Key takeaways", "slug": "key_takeaways", "status": "active", "canonId": "019de52d-06e7-7674-a891-9f7de3b11b6d", "version": 1, "description": null }, "function": "summarize", "functionCanon": { "name": "Summarize", "slug": "summarize", "status": "active", "canonId": "019de52d-1541-704f-b86f-bf7b75056373", "version": 1, "description": null }, "density": "dense", "densityScore": 74, "componentCount": 8, "textChars": 1249, "nDataPoints": 0, "notes": null, "elementsJson": [ "headline_text", "paragraph", "callout_box", "icon_grid" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:43:47.014+00", "seconds": 3.389, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5c-b1fd37abc6e1/12", "deck": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1#slide-12", "deckJson": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1.json" }, "components": [ { "bbox": { "h": 0.05, "w": 0.46, "x": 0.27, "y": 0.65 }, "kind": "callout", "text": "Key resources for Amazon Bedrock AgentCore", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": null, "subkind": { "name": "Primary callout", "slug": "primary", "status": "active", "canonId": "019de52c-fbd1-70eb-a9ce-8997f8674c1d", "version": 1, "description": null }, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:47.014+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "c3b70d70-d35f-4f74-8946-4bcee1a88215", "parentComponentId": null }, { "bbox": null, "kind": "callout", "text": "Amazon Bedrock AgentCore (preview) helps developers accelerate AI agents into production with the scale, reliability, and security, critical to real-world deployment.", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-25 11:59:00+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-41aa-7578-83cc-96efd325100b", "parentComponentId": null }, { "bbox": { "h": 0.25, "w": 0.3, "x": 0.37, "y": 0.32 }, "kind": "list", "text": "Flexibility and choice: Build agents your way using any framework, model, or tool—while maintaining complete control over how your agents operate and integrate with existing systems.", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:47.014+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "09bb5c57-e20a-4080-b091-2e851fb15881", "parentComponentId": null }, { "bbox": { "h": 0.25, "w": 0.3, "x": 0.06, "y": 0.32 }, "kind": "list", "text": "Faster time to value: Accelerate from prototype to production with fully-managed services that eliminate infrastructure complexity, so you can bring groundbreaking agentic solutions to market faster.", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:47.014+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "2680ff65-8bb8-40eb-bd42-a44ad08c7008", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.9, "x": 0.06, "y": 0.74 }, "kind": "list", "text": "Learn more about AgentCore | See how AgentCore works | Explore code examples and integration guides", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:47.014+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "8189e789-c5b8-499c-87b0-edd4a5a2f50f", "parentComponentId": null }, { "bbox": { "h": 0.25, "w": 0.3, "x": 0.67, "y": 0.32 }, "kind": "list", "text": "Security and trust: Deploy with confidence using enterprise-grade security, complete session isolation, and comprehensive controls that help your agents operate reliably and securely at scale.", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:47.014+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "869f9df5-06a8-473d-a445-be34d539214d", "parentComponentId": null }, { "bbox": { "h": 0.1, "w": 0.9, "x": 0.06, "y": 0.15 }, "kind": "paragraph", "text": "Amazon Bedrock AgentCore (preview) helps developers accelerate AI agents into production with the scale, reliability, and security, critical to real-world deployment. It offers infrastructure purpose-built for dynamic agent workloads, powerful tools to enhance agents, and essential controls for real-world deployment.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:47.014+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "60858f1d-678a-452a-88c8-40c42c6d4022", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.9, "x": 0.06, "y": 0.08 }, "kind": "title", "text": "Deploy and operate agents: Amazon Bedrock AgentCore", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:47.014+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "c79cf35b-04f7-4d98-be5c-d3c40694af86", "parentComponentId": null } ], "metrics": [], "tools": [ { "tool": { "name": "The Rule of Three", "slug": "the-rule-of-three", "status": "active", "bestFor": null, "canonId": "019dd956-8962-75cf-b4f8-9394501a6f33", "version": 1, "bodyDocId": null, "description": "Ideas presented in threes are more memorable and satisfying", "familyLabel": null, "categoryName": "Block", "categorySlug": "block" }, "agent": "Storyteller", "layer": "block", "agents": [ "Storyteller" ], "matchId": "019de067-34d9-7156-ad6c-8b618ef036be", "evidence": "three benefit columns: speed, flexibility, security", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 80, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 12, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Action Titles", "slug": "action-titles", "status": "active", "bestFor": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "canonId": "019dd956-ac70-700b-a608-ba58e78f5dcc", "version": 1, "bodyDocId": "816dad3c-9983-41c1-a86e-978ebd582841", "description": "The McKinsey-bred discipline of writing every slide title as a complete declarative sentence with a verb and an insight, not a topic label. Each title is a sub-claim that ladders up to the deck's governing thought; read in sequence, the titles reconstruct the executive summary.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019de067-3501-75af-8c3d-c05cc0369afe", "evidence": "callout states AgentCore helps developers accelerate AI agents into production", "pageRefs": null, "priority": "Core", "whenToUse": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "confidence": 70, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 12, "whyItWorks": "Solves two failure modes at once. (1) The buried claim: action titles place the conclusion on the page before any analysis is read, so a busy reader doesn't reverse-engineer it from the chart. (2) The spineless deck: because each title is a claim, slides have to ladder up to the governing thought; logical gaps become visible as topic-shaped titles in a sequence that no longer reads as a story.", "antipattern": "Topic labels disguised as titles — Volume by quarter, Key findings, Pricing strategy, Margins have been impacted. No verb, or a passive verb with no agent, or a fact (Revenue grew 12%) without the so-what. Also: titles that overreach the chart's evidence, multi-claim X-grew-but-Y-fell welded titles, and mechanical repetition of the same X-drove-Y template across the deck.", "cardinality": null, "narrativePurpose": "Forces the deck to carry its argument in the title bar so a senior reader can extract the recommendation without opening a single slide; converts a binder of topics into a navigable pyramid where every slide is a node defending the apex." }, { "tool": { "name": "Executive summary", "slug": "executive-summary", "status": "active", "bestFor": null, "canonId": "019dd9e1-4b63-72d5-9734-da757d91ca61", "version": 1, "bodyDocId": null, "description": "A condensed view of the entire argument on a single slide / block.", "familyLabel": null, "categoryName": null, "categorySlug": null }, "agent": null, "layer": "slide", "agents": null, "matchId": "bf2a0b28-f6b1-4df8-a730-41a8c0b6b76a", "evidence": "list/bullet: Faster time to value", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 21:55:50.798307+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 12, "whyItWorks": null, "antipattern": null, "cardinality": "common", "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 17, "arc": { "name": "AIDA", "slug": "aida", "status": "active", "bestFor": "Marketing presentations, product launches, sales enablement", "canonId": "019dd956-5fb4-77aa-866d-f9bdd47803af", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Attention -> Interest -> Desire -> Action", "description": null, "familyLabel": null }, "from": 8, "name": "Desire", "beatId": "019de067-2e0e-73a0-a9c0-e2dabafb5391", "matchId": "019de067-2d91-7264-a72e-b60277f83dc2", "beatType": null, "evidence": "case studies, industries, AWS services, AgentCore stack", "position": 3, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 72 }, { "to": 15, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null }, "from": 11, "name": "Solution & Approach", "beatId": "019de067-2ee2-737f-92ef-11630c0cfd36", "matchId": "019de067-2e65-73ce-8e5b-7d2ab9a39fa9", "beatType": null, "evidence": "Choose path, AgentCore, OSS frameworks, MCP", "position": 3, "isPrimaryArc": false, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 48 } ], "loops": [ { "to": 15, "from": 11, "loop": { "name": "33_build_up", "slug": "33-build-up", "status": "active", "bestFor": "Pricing justification, cost estimation, market sizing", "canonId": "019dd956-733a-746e-88fd-04b2e4b51b61", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Base -> Add Component A -> Add Component B -> Add Component C -> The Total", "description": "Start from zero and add components to arrive at a total", "familyLabel": null }, "matchId": "019de067-2fec-767b-9083-66d2218cde61", "evidence": "Base choice (p11) + AgentCore (p12) + service modules (p13) + OSS frameworks (p14) + MCP (p15) sums to full AWS offering.", "position": 3, "objective": "Build up the AWS agentic stack as a complete solution", "confidence": 72, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null } } ], "locked": true }, { "page": 13, "type": "setup", "function": "present_solution", "rawType": "initiative_list", "block": null, "metadata": { "slideType": "initiative_list", "slideTypeCanon": { "name": "Initiative list", "slug": "initiative_list", "status": "active", "canonId": "019de52d-0caf-770e-9b91-b99239121f50", "version": 1, "description": null }, "function": "present_solution", "functionCanon": { "name": "Present solution", "slug": "present_solution", "status": "active", "canonId": "019de52d-15b8-71da-bd23-2b767850cbce", "version": 1, "description": null }, "density": "balanced", "densityScore": 39, "componentCount": 4, "textChars": 827, "nDataPoints": 0, "notes": null, "elementsJson": [ "comparison_table", "paragraph" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:43:46.119+00", "seconds": 2.365, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5c-b1fd37abc6e1/13", "deck": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1#slide-13", "deckJson": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1.json" }, "components": [ { "bbox": null, "kind": "callout", "text": "Bedrock AgentCore services can be used together or independently and work with any framework, including CrewAI, LangGraph, LlamaIndex, and Strands Agents.", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-25 11:59:00+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-41aa-7578-83cc-c0ec6b90b845", "parentComponentId": null }, { "bbox": { "h": 0.07, "w": 0.88, "x": 0.06, "y": 0.18 }, "kind": "paragraph", "text": "Bedrock AgentCore services can be used together or independently and work with any framework, including CrewAI, LangGraph, LlamaIndex, and Strands Agents. These services also work with any foundation model in or outside of Amazon Bedrock, giving you ultimate flexibility.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:46.119+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "779482fc-841a-4203-94b9-85933df6a4d8", "parentComponentId": null }, { "bbox": { "h": 0.6, "w": 0.88, "x": 0.06, "y": 0.28 }, "kind": "table", "text": "AgentCore Runtime: Provides low-latency serverless environments... AgentCore Memory: Manages session context... AgentCore Gateway: Transforms existing APIs... AgentCore Identity: Enables secure access... AgentCore Observability: Delivers comprehensive monitoring... AgentCore Browser: Provides managed web browser... AgentCore Code Interpreter: Offers isolated environments...", "attrs": null, "canon": { "kind": { "name": "Table", "slug": "table", "status": "active", "canonId": "019de52c-f9c8-7148-8119-eaac9594cd28", "version": 1, "description": "Tabular data layout." }, "tool": null, "subkind": { "name": "Data table", "slug": "data", "status": "active", "canonId": "019de52d-02d5-75b8-8abf-88e92bf63569", "version": 1, "description": null }, "framework": null }, "subkind": "data", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:46.119+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "26cd0156-9b06-474c-bacd-ca1d13014f28", "parentComponentId": null }, { "bbox": { "h": 0.04, "w": 0.35, "x": 0.06, "y": 0.08 }, "kind": "title", "text": "Bedrock AgentCore services", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:46.119+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "a44f1cdf-2cc6-4138-be1b-13ffa0d35afb", "parentComponentId": null } ], "metrics": [], "tools": [ { "tool": { "name": "Chunking", "slug": "chunking", "status": "active", "bestFor": null, "canonId": "019dd956-abab-72ce-b64c-2924cc83cf39", "version": 1, "bodyDocId": null, "description": "Information grouped into chunks is remembered better - structure content in digestible units", "familyLabel": null, "categoryName": "Loop", "categorySlug": "loop" }, "agent": "Architect", "layer": "loop", "agents": [ "Architect" ], "matchId": "019de067-3597-7418-a324-698034fea764", "evidence": "complex platform broken into seven named modules", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 60, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 13, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Small Multiples", "slug": "small-multiples", "status": "active", "bestFor": null, "canonId": "019dd956-b32d-7586-b368-baa1dd388ed4", "version": 1, "bodyDocId": null, "description": "Repeating similar charts for comparison across categories or time", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019de067-352b-73db-9ed3-b6058121c413", "evidence": "seven AgentCore services laid out with same row pattern", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 80, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 13, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 17, "arc": { "name": "AIDA", "slug": "aida", "status": "active", "bestFor": "Marketing presentations, product launches, sales enablement", "canonId": "019dd956-5fb4-77aa-866d-f9bdd47803af", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Attention -> Interest -> Desire -> Action", "description": null, "familyLabel": null }, "from": 8, "name": "Desire", "beatId": "019de067-2e0e-73a0-a9c0-e2dabafb5391", "matchId": "019de067-2d91-7264-a72e-b60277f83dc2", "beatType": null, "evidence": "case studies, industries, AWS services, AgentCore stack", "position": 3, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 72 }, { "to": 15, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null }, "from": 11, "name": "Solution & Approach", "beatId": "019de067-2ee2-737f-92ef-11630c0cfd36", "matchId": "019de067-2e65-73ce-8e5b-7d2ab9a39fa9", "beatType": null, "evidence": "Choose path, AgentCore, OSS frameworks, MCP", "position": 3, "isPrimaryArc": false, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 48 } ], "loops": [ { "to": 15, "from": 11, "loop": { "name": "33_build_up", "slug": "33-build-up", "status": "active", "bestFor": "Pricing justification, cost estimation, market sizing", "canonId": "019dd956-733a-746e-88fd-04b2e4b51b61", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Base -> Add Component A -> Add Component B -> Add Component C -> The Total", "description": "Start from zero and add components to arrive at a total", "familyLabel": null }, "matchId": "019de067-2fec-767b-9083-66d2218cde61", "evidence": "Base choice (p11) + AgentCore (p12) + service modules (p13) + OSS frameworks (p14) + MCP (p15) sums to full AWS offering.", "position": 3, "objective": "Build up the AWS agentic stack as a complete solution", "confidence": 72, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null } } ], "locked": true }, { "page": 14, "type": "analysis", "function": "present_solution", "rawType": "market_landscape", "block": null, "metadata": { "slideType": "market_landscape", "slideTypeCanon": { "name": "Market landscape", "slug": "market_landscape", "status": "active", "canonId": "019de52d-0b6d-75db-a946-9ac362e3afc2", "version": 1, "description": null }, "function": "present_solution", "functionCanon": { "name": "Present solution", "slug": "present_solution", "status": "active", "canonId": "019de52d-15b8-71da-bd23-2b767850cbce", "version": 1, "description": null }, "density": "dense", "densityScore": 67, "componentCount": 9, "textChars": 572, "nDataPoints": 0, "notes": null, "elementsJson": [ "icon_grid", "bullet_list" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:43:46.658+00", "seconds": 2.816, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5c-b1fd37abc6e1/14", "deck": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1#slide-14", "deckJson": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1.json" }, "components": [ { "bbox": null, "kind": "callout", "text": "Deploy your agents built on these leading open-source frameworks on AgentCore for enterprise-grade security and reliability.", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-25 11:59:00+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-41aa-7578-83cc-d5610b9d3222", "parentComponentId": null }, { "bbox": { "h": 0.06, "w": 0.15, "x": 0.68, "y": 0.3 }, "kind": "image", "text": "LangChain logo", "attrs": null, "canon": { "kind": { "name": "Image", "slug": "image", "status": "active", "canonId": "019de52c-f978-701f-a720-51d029d769e7", "version": 1, "description": "Photo, illustration, screenshot or icon." }, "tool": null, "subkind": { "name": "Logo", "slug": "logo", "status": "active", "canonId": "019de52c-fdaf-743d-94c4-d7c6a0e55302", "version": 1, "description": null }, "framework": null }, "subkind": "logo", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:46.658+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "179dcf37-d25f-4b3f-b521-0d4b237bc9f9", "parentComponentId": null }, { "bbox": { "h": 0.06, "w": 0.15, "x": 0.42, "y": 0.3 }, "kind": "image", "text": "CrewAI logo", "attrs": null, "canon": { "kind": { "name": "Image", "slug": "image", "status": "active", "canonId": "019de52c-f978-701f-a720-51d029d769e7", "version": 1, "description": "Photo, illustration, screenshot or icon." }, "tool": null, "subkind": { "name": "Logo", "slug": "logo", "status": "active", "canonId": "019de52c-fdaf-743d-94c4-d7c6a0e55302", "version": 1, "description": null }, "framework": null }, "subkind": "logo", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:46.658+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "5c4b94a1-a03e-4d64-9615-f2dbdb6e761b", "parentComponentId": null }, { "bbox": { "h": 0.06, "w": 0.05, "x": 0.09, "y": 0.3 }, "kind": "image", "text": "Strands Agents logo", "attrs": null, "canon": { "kind": { "name": "Image", "slug": "image", "status": "active", "canonId": "019de52c-f978-701f-a720-51d029d769e7", "version": 1, "description": "Photo, illustration, screenshot or icon." }, "tool": null, "subkind": { "name": "Logo", "slug": "logo", "status": "active", "canonId": "019de52c-fdaf-743d-94c4-d7c6a0e55302", "version": 1, "description": null }, "framework": null }, "subkind": "logo", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:46.658+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "7b74954a-9261-4af3-8931-6efdd7da03d6", "parentComponentId": null }, { "bbox": { "h": 0.4, "w": 0.28, "x": 0.06, "y": 0.415 }, "kind": "list", "text": "Strands Agents: AWS native, Python SDK, AgentCore support, enterprise-ready.", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:46.658+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "1f91153d-2090-4681-9c57-5909c58d65dd", "parentComponentId": null }, { "bbox": { "h": 0.4, "w": 0.28, "x": 0.66, "y": 0.415 }, "kind": "list", "text": "LangChain: LLM development, rich ecosystem, AWS-managed support, enterprise-ready.", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:46.658+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "2fc3fb8f-0845-4ecf-bcb6-7ef35a7747e1", "parentComponentId": null }, { "bbox": { "h": 0.4, "w": 0.28, "x": 0.36, "y": 0.415 }, "kind": "list", "text": "CrewAI: Multi-agent orchestration, LiteLLM integration, production scaling.", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:46.658+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "5eff4652-e3de-428b-a1d9-17d14eb5ceea", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.8, "x": 0.06, "y": 0.18 }, "kind": "paragraph", "text": "Deploy your agents built on these leading open-source frameworks on AgentCore for enterprise-grade security and reliability.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:46.658+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "9e387270-ad9b-4e99-b61b-d5e69a36a83e", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.5, "x": 0.06, "y": 0.08 }, "kind": "title", "text": "Popular OSS frameworks used for building agents", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:46.658+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "18ddc1a8-8ef9-40a0-924e-40eef02952a5", "parentComponentId": null } ], "metrics": [], "tools": [ { "tool": { "name": "Halo Effect", "slug": "halo-effect", "status": "active", "bestFor": null, "canonId": "019dd956-c7a3-757c-82ed-429da0d9256f", "version": 1, "bodyDocId": null, "description": "Positive impression in one area influences opinions in others", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019de067-35e8-763a-885a-911bd5e76384", "evidence": "names CrewAI, LangChain, Strands to borrow ecosystem credibility", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 55, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 14, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Small Multiples", "slug": "small-multiples", "status": "active", "bestFor": null, "canonId": "019dd956-b32d-7586-b368-baa1dd388ed4", "version": 1, "bodyDocId": null, "description": "Repeating similar charts for comparison across categories or time", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019de067-35bf-736e-bd74-1c6c886bfd62", "evidence": "three OSS framework cards with same structure", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 75, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 14, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 17, "arc": { "name": "AIDA", "slug": "aida", "status": "active", "bestFor": "Marketing presentations, product launches, sales enablement", "canonId": "019dd956-5fb4-77aa-866d-f9bdd47803af", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Attention -> Interest -> Desire -> Action", "description": null, "familyLabel": null }, "from": 8, "name": "Desire", "beatId": "019de067-2e0e-73a0-a9c0-e2dabafb5391", "matchId": "019de067-2d91-7264-a72e-b60277f83dc2", "beatType": null, "evidence": "case studies, industries, AWS services, AgentCore stack", "position": 3, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 72 }, { "to": 15, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null }, "from": 11, "name": "Solution & Approach", "beatId": "019de067-2ee2-737f-92ef-11630c0cfd36", "matchId": "019de067-2e65-73ce-8e5b-7d2ab9a39fa9", "beatType": null, "evidence": "Choose path, AgentCore, OSS frameworks, MCP", "position": 3, "isPrimaryArc": false, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 48 } ], "loops": [ { "to": 15, "from": 11, "loop": { "name": "33_build_up", "slug": "33-build-up", "status": "active", "bestFor": "Pricing justification, cost estimation, market sizing", "canonId": "019dd956-733a-746e-88fd-04b2e4b51b61", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Base -> Add Component A -> Add Component B -> Add Component C -> The Total", "description": "Start from zero and add components to arrive at a total", "familyLabel": null }, "matchId": "019de067-2fec-767b-9083-66d2218cde61", "evidence": "Base choice (p11) + AgentCore (p12) + service modules (p13) + OSS frameworks (p14) + MCP (p15) sums to full AWS offering.", "position": 3, "objective": "Build up the AWS agentic stack as a complete solution", "confidence": 72, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null } } ], "locked": true }, { "page": 15, "type": "appendix", "title": "The slide uses a split-layout with a main content area and a right-hand sidebar for resources.", "function": "present_solution", "rawType": "other", "block": null, "metadata": { "slideType": "other", "slideTypeCanon": { "name": "Other (fallback)", "slug": "other", "status": "active", "canonId": "019de52d-0af5-71ed-83de-d51ae245fc43", "version": 1, "description": null }, "function": "present_solution", "functionCanon": { "name": "Present solution", "slug": "present_solution", "status": "active", "canonId": "019de52d-15b8-71da-bd23-2b767850cbce", "version": 1, "description": null }, "density": "overcrowded", "densityScore": 75, "componentCount": 8, "textChars": 1344, "nDataPoints": 0, "notes": "The slide uses a split-layout with a main content area and a right-hand sidebar for resources.", "elementsJson": [ "headline_text", "bullet_list", "paragraph", "callout_box", "icon_grid" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:43:46.721+00", "seconds": 2.811, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5c-b1fd37abc6e1/15", "deck": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1#slide-15", "deckJson": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1.json" }, "components": [ { "bbox": { "h": 0.05, "w": 0.25, "x": 0.65, "y": 0.15 }, "kind": "callout", "text": "Key resources to accelerate MCP", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": null, "subkind": { "name": "Primary callout", "slug": "primary", "status": "active", "canonId": "019de52c-fbd1-70eb-a9ce-8997f8674c1d", "version": 1, "description": null }, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:46.721+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "37f7a71a-90af-4d23-9d39-eac469160102", "parentComponentId": null }, { "bbox": null, "kind": "callout", "text": "MCP is an open standard to enable seamless integration between LLM models and external tools, databases, and APIs.", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-25 11:59:00+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-41aa-7578-83cb-f2d54575e15e", "parentComponentId": null }, { "bbox": { "h": 0.25, "w": 0.55, "x": 0.06, "y": 0.28 }, "kind": "list", "text": "AgentCore Runtime enables secure and scalable hosting of MCP servers\nAgentCore Gateway converts APIs into MCP compatible tools\nAWS Marketplace offers ready-to-use MCP tools with optional AgentCore integration\nAmazon Bedrock supports MCP tools through inline Agents API\nAmazon Q Developer CLI includes MCP support\nRun MCP servers and clients on AWS using open source MCP libraries", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:46.721+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "39cb0f81-65ce-460a-96b2-1b21e3e00132", "parentComponentId": null }, { "bbox": { "h": 0.15, "w": 0.55, "x": 0.06, "y": 0.7 }, "kind": "list", "text": "Developers: Simplify integration with external tools, reducing dev time.\nEnd Users: Enable powerful and context-rich generative AI applications. Create better user experiences.\nEnterprises: Fosters a standardized ecosystem. Easier to maintain and extend LLM integrations.", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:46.721+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "67cdf94f-c079-4204-bfa3-75ac5b7ec592", "parentComponentId": null }, { "bbox": { "h": 0.4, "w": 0.3, "x": 0.65, "y": 0.25 }, "kind": "list", "text": "Learn how to deploy MCP servers on AgentCore Runtime\nLearn to convert APIs into MCP compatible tools using Gateway\nBuild MCP with Amazon Bedrock Agents\nBest Practice Guidance for deploying MCP servers on AWS", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:46.721+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "7d6daa63-59be-4a13-8112-1ceb6055ce7a", "parentComponentId": null }, { "bbox": { "h": 0.1, "w": 0.55, "x": 0.06, "y": 0.15 }, "kind": "paragraph", "text": "MCP is an open standard to enable seamless integration between LLM models and external tools, databases, and APIs. It acts as a universal connector, allowing LLM-based systems to access real-time data and perform actions in external systems.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:46.721+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "95ab203e-7b77-4efc-b8cb-9a5088d9cb11", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.55, "x": 0.06, "y": 0.63 }, "kind": "paragraph", "text": "MCP makes it easier for teams to work together on AI-powered applications", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:46.721+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "c99369c7-a127-4def-a7ed-784290fab494", "parentComponentId": null }, { "bbox": { "h": 0.04, "w": 0.4, "x": 0.06, "y": 0.08 }, "kind": "title", "text": "Model context protocol (MCP)", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:46.721+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "14f5c8eb-4e21-461f-9633-0eeaeedda701", "parentComponentId": null } ], "metrics": [], "tools": [ { "tool": { "name": "Authority Bias", "slug": "authority-bias", "status": "active", "bestFor": null, "canonId": "019dd956-c38d-70b9-a284-b2b479763356", "version": 1, "bodyDocId": null, "description": "Expert opinions are weighted more heavily - cite credible sources", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Architect", "Storyteller" ], "matchId": "019de067-363d-773c-abcf-11253e6681f4", "evidence": "leans on MCP being an open standard for credibility", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 60, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 15, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Typography Hierarchy", "slug": "typography-hierarchy", "status": "active", "bestFor": null, "canonId": "019dd956-ba98-77ab-9513-ff2344da8bc7", "version": 1, "bodyDocId": null, "description": "Using font size, weight, and style to create reading order", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019de067-3613-764e-a643-d1016a8062bd", "evidence": "split layout with title, definition callout and resource sidebar", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 60, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 15, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 17, "arc": { "name": "AIDA", "slug": "aida", "status": "active", "bestFor": "Marketing presentations, product launches, sales enablement", "canonId": "019dd956-5fb4-77aa-866d-f9bdd47803af", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Attention -> Interest -> Desire -> Action", "description": null, "familyLabel": null }, "from": 8, "name": "Desire", "beatId": "019de067-2e0e-73a0-a9c0-e2dabafb5391", "matchId": "019de067-2d91-7264-a72e-b60277f83dc2", "beatType": null, "evidence": "case studies, industries, AWS services, AgentCore stack", "position": 3, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 72 }, { "to": 15, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null }, "from": 11, "name": "Solution & Approach", "beatId": "019de067-2ee2-737f-92ef-11630c0cfd36", "matchId": "019de067-2e65-73ce-8e5b-7d2ab9a39fa9", "beatType": null, "evidence": "Choose path, AgentCore, OSS frameworks, MCP", "position": 3, "isPrimaryArc": false, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 48 } ], "loops": [ { "to": 15, "from": 11, "loop": { "name": "33_build_up", "slug": "33-build-up", "status": "active", "bestFor": "Pricing justification, cost estimation, market sizing", "canonId": "019dd956-733a-746e-88fd-04b2e4b51b61", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Base -> Add Component A -> Add Component B -> Add Component C -> The Total", "description": "Start from zero and add components to arrive at a total", "familyLabel": null }, "matchId": "019de067-2fec-767b-9083-66d2218cde61", "evidence": "Base choice (p11) + AgentCore (p12) + service modules (p13) + OSS frameworks (p14) + MCP (p15) sums to full AWS offering.", "position": 3, "objective": "Build up the AWS agentic stack as a complete solution", "confidence": 72, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null } } ], "locked": true }, { "page": 16, "type": "analysis", "title": "The slide uses a grid layout to categorize AI agent offerings into six distinct segments: Pre-built agents, Agent development solutions, Agent tools, Agent infr", "function": "present_solution", "rawType": "market_landscape", "block": null, "metadata": { "slideType": "market_landscape", "slideTypeCanon": { "name": "Market landscape", "slug": "market_landscape", "status": "active", "canonId": "019de52d-0b6d-75db-a946-9ac362e3afc2", "version": 1, "description": null }, "function": "present_solution", "functionCanon": { "name": "Present solution", "slug": "present_solution", "status": "active", "canonId": "019de52d-15b8-71da-bd23-2b767850cbce", "version": 1, "description": null }, "density": "balanced", "densityScore": 43, "componentCount": 6, "textChars": 473, "nDataPoints": 0, "notes": "The slide uses a grid layout to categorize AI agent offerings into six distinct segments: Pre-built agents, Agent development solutions, Agent tools, Agent infrastructure, Professional services, and Software with embedded agents.", "elementsJson": [ "headline_text", "icon_grid", "callout_box" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:43:50.426+00", "seconds": 6.402, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5c-b1fd37abc6e1/16", "deck": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1#slide-16", "deckJson": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1.json" }, "components": [ { "bbox": null, "kind": "callout", "text": "This is not a complete list. To view all products listed in AWS Marketplace, visit AWS Marketplace.", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-25 11:59:00+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-41aa-7578-83cd-045fbec8d2ab", "parentComponentId": null }, { "bbox": { "h": 0.04, "w": 0.75, "x": 0.06, "y": 0.87 }, "kind": "disclaimer", "text": "This is not a complete list. To view all products listed in AWS Marketplace, visit AWS Marketplace. This list is current as of July 23, 2025.", "attrs": null, "canon": { "kind": { "name": "Disclaimer", "slug": "disclaimer", "status": "active", "canonId": "91173477-d91f-4024-bbaf-d4f93e3f82dc", "version": 1, "description": "Legal/cautionary text that occupies most of the body of its slide." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:50.426+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "0e799390-052c-4fe3-a4d4-0b18d1bfd12c", "parentComponentId": null }, { "bbox": { "h": 0.03, "w": 0.15, "x": 0.06, "y": 0.95 }, "kind": "image", "text": "aws marketplace", "attrs": null, "canon": { "kind": { "name": "Image", "slug": "image", "status": "active", "canonId": "019de52c-f978-701f-a720-51d029d769e7", "version": 1, "description": "Photo, illustration, screenshot or icon." }, "tool": null, "subkind": { "name": "Logo", "slug": "logo", "status": "active", "canonId": "019de52c-fdaf-743d-94c4-d7c6a0e55302", "version": 1, "description": null }, "framework": null }, "subkind": "logo", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:50.426+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "1e6d17c4-638e-4dde-9e6e-6a081c9bb866", "parentComponentId": null }, { "bbox": { "h": 0.65, "w": 0.88, "x": 0.06, "y": 0.18 }, "kind": "list", "text": "Pre-built agents, Agent development solutions, Agent tools, Agent infrastructure, Professional services, Software with embedded agents", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:50.426+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "91e6640f-086f-491d-b266-a573ee813963", "parentComponentId": null }, { "bbox": { "h": 0.04, "w": 0.5, "x": 0.06, "y": 0.08 }, "kind": "title", "text": "Discover AI agent solutions in AWS Marketplace", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:50.426+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "a683a496-8725-4256-b2b1-e82c6dd358a1", "parentComponentId": null }, { "bbox": { "h": 0.02, "w": 0.3, "x": 0.06, "y": 0.04 }, "kind": "title", "text": "AI AGENTS AND TOOLS IN AWS MARKETPLACE", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Subtitle", "slug": "subtitle", "status": "active", "canonId": "019de52c-fb09-739d-900c-815b0d9ac526", "version": 1, "description": null }, "framework": null }, "subkind": "subtitle", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:50.426+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "7aa6df90-8f11-4460-9062-4f5f0befbe57", "parentComponentId": null } ], "metrics": [], "tools": [ { "tool": { "name": "Build-Up (Gradatio)", "slug": "build-up-gradatio", "status": "active", "bestFor": null, "canonId": "019dd956-a19a-73fd-9f74-c3f50dbb266d", "version": 1, "bodyDocId": null, "description": "Arranging ideas in ascending order of importance or intensity", "familyLabel": null, "categoryName": "Loop", "categorySlug": "loop" }, "agent": "Storyteller", "layer": "loop", "agents": [ "Storyteller" ], "matchId": "019de067-3667-72ac-89b1-3725ef745705", "evidence": "loop assembles Marketplace catalog, deployment, value", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 60, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 16, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Small Multiples", "slug": "small-multiples", "status": "active", "bestFor": null, "canonId": "019dd956-b32d-7586-b368-baa1dd388ed4", "version": 1, "bodyDocId": null, "description": "Repeating similar charts for comparison across categories or time", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019de067-3692-7787-aad9-fa7da9506f7b", "evidence": "six category callout boxes share identical structure", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 80, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 16, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [ { "matchId": "8e6f3d1b-b792-47e8-881b-ac0389011b04", "evidence": "Categorization of market offerings into distinct functional segments.", "framework": null, "confidence": 0.6, "extraction": { "at": "2026-05-02 17:43:50.426+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 16, "frameworkName": "market-segmentation-pyramid" } ], "arcBeats": [ { "to": 17, "arc": { "name": "AIDA", "slug": "aida", "status": "active", "bestFor": "Marketing presentations, product launches, sales enablement", "canonId": "019dd956-5fb4-77aa-866d-f9bdd47803af", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Attention -> Interest -> Desire -> Action", "description": null, "familyLabel": null }, "from": 8, "name": "Desire", "beatId": "019de067-2e0e-73a0-a9c0-e2dabafb5391", "matchId": "019de067-2d91-7264-a72e-b60277f83dc2", "beatType": null, "evidence": "case studies, industries, AWS services, AgentCore stack", "position": 3, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 72 } ], "loops": [ { "to": 18, "from": 16, "loop": { "name": "33_build_up", "slug": "33-build-up", "status": "active", "bestFor": "Pricing justification, cost estimation, market sizing", "canonId": "019dd956-733a-746e-88fd-04b2e4b51b61", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Base -> Add Component A -> Add Component B -> Add Component C -> The Total", "description": "Start from zero and add components to arrive at a total", "familyLabel": null }, "matchId": "019de067-3016-7644-b28d-b82150ce5bd6", "evidence": "Catalog breadth (p16) + deployment architecture (p17) + three-pillar value prop (p18) builds Marketplace pitch.", "position": 4, "objective": "Position AWS Marketplace as the operational layer", "confidence": 65, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null } } ], "locked": true }, { "page": 17, "type": "appendix", "title": "The slide uses a hub-and-spoke style architecture diagram to show integration flow.", "function": "present_solution", "rawType": "other", "block": null, "metadata": { "slideType": "other", "slideTypeCanon": { "name": "Other (fallback)", "slug": "other", "status": "active", "canonId": "019de52d-0af5-71ed-83de-d51ae245fc43", "version": 1, "description": null }, "function": "present_solution", "functionCanon": { "name": "Present solution", "slug": "present_solution", "status": "active", "canonId": "019de52d-15b8-71da-bd23-2b767850cbce", "version": 1, "description": null }, "density": "balanced", "densityScore": 44, "componentCount": 5, "textChars": 744, "nDataPoints": 0, "notes": "The slide uses a hub-and-spoke style architecture diagram to show integration flow.", "elementsJson": [ "process_diagram", "logo_grid" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:43:46.588+00", "seconds": 2.559, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5c-b1fd37abc6e1/17", "deck": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1#slide-17", "deckJson": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1.json" }, "components": [ { "bbox": null, "kind": "callout", "text": "Run select pre-built agents and tools from AWS Marketplace with AgentCore Runtime. Quickly allow your agents to securely connect to API-based agents and tools from AWS Marketplace with AgentCore Gateway.", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-25 11:59:00+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-41aa-7578-83cd-1a17703adfdc", "parentComponentId": null }, { "bbox": { "h": 0.55, "w": 0.88, "x": 0.06, "y": 0.28 }, "kind": "diagram", "text": "Architecture diagram showing AWS Marketplace sources connecting to AgentCore Runtime and Gateway within a user's AWS account.", "attrs": null, "canon": { "kind": { "name": "Diagram", "slug": "diagram", "status": "active", "canonId": "019de52c-f9f0-734a-81de-15382ff28c65", "version": 1, "description": "Schematic or relational diagram." }, "tool": null, "subkind": { "name": "Hub and spoke", "slug": "hub-spoke", "status": "active", "canonId": "019de52d-04db-73e6-81ca-a234f2f23fc1", "version": 1, "description": null }, "framework": null }, "subkind": "hub-spoke", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:46.588+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "b2ad19ed-760c-4c0b-bb1c-db6c030b4078", "parentComponentId": null }, { "bbox": { "h": 0.04, "w": 0.8, "x": 0.06, "y": 0.88 }, "kind": "disclaimer", "text": "This is not a complete list. To view all products listed in AWS Marketplace, visit AWS Marketplace. This list is current as of July 23, 2025.", "attrs": null, "canon": { "kind": { "name": "Disclaimer", "slug": "disclaimer", "status": "active", "canonId": "91173477-d91f-4024-bbaf-d4f93e3f82dc", "version": 1, "description": "Legal/cautionary text that occupies most of the body of its slide." }, "tool": null, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:46.588+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "97a0a07c-51d6-46d9-8bc1-b1bb6d41c5b5", "parentComponentId": null }, { "bbox": { "h": 0.06, "w": 0.88, "x": 0.06, "y": 0.16 }, "kind": "paragraph", "text": "Run select pre-built agents and tools from AWS Marketplace with AgentCore Runtime. Quickly allow your agents to securely connect to API-based agents and tools from AWS Marketplace with AgentCore Gateway.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:46.588+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "dce90a35-bfa7-4d7b-9e75-a1f1e0a75986", "parentComponentId": null }, { "bbox": { "h": 0.06, "w": 0.8, "x": 0.06, "y": 0.08 }, "kind": "title", "text": "Deploy agents and tools from AWS Marketplace on Amazon Bedrock AgentCore", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:46.588+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "44aaedf9-94d4-4cb4-809d-9c224875e955", "parentComponentId": null } ], "metrics": [], "tools": [ { "tool": { "name": "Mapping", "slug": "mapping", "status": "active", "bestFor": null, "canonId": "019dd956-d74b-74cd-b645-119646136d81", "version": 1, "bodyDocId": null, "description": "Relationship between controls and their effects - make it natural", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019de067-370e-73af-8fe8-87ee5b32ee83", "evidence": "diagram maps marketplace tools to AgentCore Runtime and Gateway", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 60, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 17, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Picture Superiority Effect", "slug": "picture-superiority-effect", "status": "active", "bestFor": null, "canonId": "019dd956-c201-7014-bb58-3e85e3e11dfd", "version": 1, "bodyDocId": null, "description": "Pictures remembered 6x better than words - prioritize visuals over text", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019de067-36bd-72e4-967a-825c8a50ff0c", "evidence": "architecture diagram dominates with partner logos and arrows", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 75, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 17, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Visual Anchors", "slug": "visual-anchors", "status": "active", "bestFor": null, "canonId": "019dd956-c264-7357-a791-89fa5f02a400", "version": 1, "bodyDocId": null, "description": "Design elements that guide users' eyes through the content intentionally", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019de067-36e5-733f-94a5-fea7eda0596b", "evidence": "arrows and central Your AWS account panel guide the eye", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 17, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [ { "matchId": "30694fbf-5d6d-4626-90d6-1abe5205326f", "evidence": "The diagram shows a central 'Your AWS account' box connecting to external Marketplace sources.", "framework": null, "confidence": 0.9, "extraction": { "at": "2026-05-02 17:43:46.588+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 17, "frameworkName": "hub-spoke" } ], "arcBeats": [ { "to": 17, "arc": { "name": "AIDA", "slug": "aida", "status": "active", "bestFor": "Marketing presentations, product launches, sales enablement", "canonId": "019dd956-5fb4-77aa-866d-f9bdd47803af", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Attention -> Interest -> Desire -> Action", "description": null, "familyLabel": null }, "from": 8, "name": "Desire", "beatId": "019de067-2e0e-73a0-a9c0-e2dabafb5391", "matchId": "019de067-2d91-7264-a72e-b60277f83dc2", "beatType": null, "evidence": "case studies, industries, AWS services, AgentCore stack", "position": 3, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 72 } ], "loops": [ { "to": 18, "from": 16, "loop": { "name": "33_build_up", "slug": "33-build-up", "status": "active", "bestFor": "Pricing justification, cost estimation, market sizing", "canonId": "019dd956-733a-746e-88fd-04b2e4b51b61", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Base -> Add Component A -> Add Component B -> Add Component C -> The Total", "description": "Start from zero and add components to arrive at a total", "familyLabel": null }, "matchId": "019de067-3016-7644-b28d-b82150ce5bd6", "evidence": "Catalog breadth (p16) + deployment architecture (p17) + three-pillar value prop (p18) builds Marketplace pitch.", "position": 4, "objective": "Position AWS Marketplace as the operational layer", "confidence": 65, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null } } ], "locked": true }, { "page": 18, "type": "setup", "function": "present_solution", "rawType": "key_messages", "block": null, "metadata": { "slideType": "key_messages", "slideTypeCanon": { "name": "Key messages", "slug": "key_messages", "status": "active", "canonId": "019de52d-0712-703f-89f5-bda6688faf3f", "version": 1, "description": null }, "function": "present_solution", "functionCanon": { "name": "Present solution", "slug": "present_solution", "status": "active", "canonId": "019de52d-15b8-71da-bd23-2b767850cbce", "version": 1, "description": null }, "density": "dense", "densityScore": 70, "componentCount": 7, "textChars": 1920, "nDataPoints": 0, "notes": null, "elementsJson": [ "headline_text", "paragraph", "icon_grid" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:43:47.643+00", "seconds": 3.542, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5c-b1fd37abc6e1/18", "deck": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1#slide-18", "deckJson": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1.json" }, "components": [ { "bbox": null, "kind": "callout", "text": "AWS Marketplace is your trusted source to discover, buy, deploy, and manage AI agents, tools, and solutions from AWS Partners.", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-25 11:59:01+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-41aa-7578-83cd-448945caf964", "parentComponentId": null }, { "bbox": { "h": 0.55, "w": 0.29, "x": 0.66, "y": 0.31 }, "kind": "list", "text": "Trusted marketplace: Backed by a decade of procurement excellence, AWS Marketplace extends its reliable curation to AI agent solutions and provides options for deploying on secure AWS infrastructure. Confidently purchase agent solutions through AWS Marketplace, where the product catalog is scanned regularly for vulnerabilities. As you scale, benefit from centralized billing and software license management on AWS.", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:47.643+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "0164078e-50a2-451a-bffe-33e157f2ca48", "parentComponentId": null }, { "bbox": { "h": 0.55, "w": 0.29, "x": 0.36, "y": 0.31 }, "kind": "list", "text": "Streamlined procurement and deployment: Add the latest agent solutions from AWS Partners to your stack fast. Try, subscribe, and scale with pay-as-you-go pricing, and negotiate custom pricing that meets your enterprise requirements. AWS Marketplace supports multiple deployment methods that help meet your security and technical requirements. Run agent solutions on trusted AWS services or in your AWS environment, where you maintain control over security and access. The API-based deployment method allows you to streamline integrations with data, tools, and agents that support model context protocol (MCP) and agent-to-agent (A2A) standard protocols.", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:47.643+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "b5b7370d-ddd4-4d74-9a98-42c2962b21d9", "parentComponentId": null }, { "bbox": { "h": 0.55, "w": 0.29, "x": 0.06, "y": 0.31 }, "kind": "list", "text": "Centralized catalog: Streamline your search in a centralized catalog of hundreds of AI agent solutions from Partners. Get started quickly with pre-built agents, build your own agents with tools, development solutions, and infrastructure, and get expert consultants to guide your journey - all in one place. Use the new AI-powered search to find the product that best fits your use case.", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:47.643+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "e9ee5eb1-7355-4fe7-ad17-0c2f924efc5a", "parentComponentId": null }, { "bbox": { "h": 0.08, "w": 0.88, "x": 0.06, "y": 0.16 }, "kind": "paragraph", "text": "The technical complexity of implementing AI agents requires careful consideration of tools, resources, and support systems. AWS Marketplace is your trusted source to discover, buy, deploy, and manage AI agents, tools, and solutions from AWS Partners.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:47.643+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "82e58590-a490-4413-838f-c65a73a92ce2", "parentComponentId": null }, { "bbox": { "h": 0.02, "w": 0.38, "x": 0.06, "y": 0.04 }, "kind": "title", "text": "AI AGENTS AND TOOLS IN AWS MARKETPLACE", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:47.643+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "e9656211-5226-44de-b1c0-030084bceef6", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.88, "x": 0.06, "y": 0.08 }, "kind": "title", "text": "Accelerate AI agent innovation with AWS Marketplace", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:47.643+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "ea509b05-d01b-4608-bd06-5f3fa4632e89", "parentComponentId": null } ], "metrics": [], "tools": [ { "tool": { "name": "The Rule of Three", "slug": "the-rule-of-three", "status": "active", "bestFor": null, "canonId": "019dd956-8962-75cf-b4f8-9394501a6f33", "version": 1, "bodyDocId": null, "description": "Ideas presented in threes are more memorable and satisfying", "familyLabel": null, "categoryName": "Block", "categorySlug": "block" }, "agent": "Storyteller", "layer": "block", "agents": [ "Storyteller" ], "matchId": "019de067-3737-735b-bce1-6e403f6e8c3b", "evidence": "three columns: Centralized catalog, Streamlined procurement, Trusted marketplace", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 85, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 18, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Action Titles", "slug": "action-titles", "status": "active", "bestFor": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "canonId": "019dd956-ac70-700b-a608-ba58e78f5dcc", "version": 1, "bodyDocId": "816dad3c-9983-41c1-a86e-978ebd582841", "description": "The McKinsey-bred discipline of writing every slide title as a complete declarative sentence with a verb and an insight, not a topic label. Each title is a sub-claim that ladders up to the deck's governing thought; read in sequence, the titles reconstruct the executive summary.", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Architect", "layer": "slide", "agents": [ "Architect" ], "matchId": "019de067-37a3-74dd-80d3-a124fb5fbb6e", "evidence": "title Accelerate AI agent innovation with AWS Marketplace states the value", "pageRefs": null, "priority": "Core", "whenToUse": "Any decision-grade deliverable — strategy recommendation, board update, investment memo, M&A review, post-mortem — where the reader is being asked to agree, decide, or act and will skim the title bar at speed.", "confidence": 75, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 18, "whyItWorks": "Solves two failure modes at once. (1) The buried claim: action titles place the conclusion on the page before any analysis is read, so a busy reader doesn't reverse-engineer it from the chart. (2) The spineless deck: because each title is a claim, slides have to ladder up to the governing thought; logical gaps become visible as topic-shaped titles in a sequence that no longer reads as a story.", "antipattern": "Topic labels disguised as titles — Volume by quarter, Key findings, Pricing strategy, Margins have been impacted. No verb, or a passive verb with no agent, or a fact (Revenue grew 12%) without the so-what. Also: titles that overreach the chart's evidence, multi-claim X-grew-but-Y-fell welded titles, and mechanical repetition of the same X-drove-Y template across the deck.", "cardinality": null, "narrativePurpose": "Forces the deck to carry its argument in the title bar so a senior reader can extract the recommendation without opening a single slide; converts a binder of topics into a navigable pyramid where every slide is a node defending the apex." }, { "tool": { "name": "Law of Similarity", "slug": "law-of-similarity", "status": "active", "bestFor": null, "canonId": "019dd956-c025-70d9-a411-8efa41ae179b", "version": 1, "bodyDocId": null, "description": "Similar-looking elements perceived as related - consistent styling for related concepts", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Designer" ], "matchId": "019de067-37cf-771d-9a96-cae2ed4d028a", "evidence": "three identical card layouts read as parallel pillars", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 70, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 18, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "List presentation", "slug": "list-presentation", "status": "active", "bestFor": null, "canonId": "019dd9e1-4ef7-777d-ba68-9074c2b3bcf1", "version": 1, "bodyDocId": null, "description": "Bulleted, numbered, or checklist enumerations.", "familyLabel": null, "categoryName": null, "categorySlug": null }, "agent": null, "layer": "slide", "agents": null, "matchId": "362accb8-f61e-4f14-90e9-af8c4884b0d6", "evidence": "The slide contains a list of bullet points.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.9, "extraction": { "at": "2026-07-16 21:56:03.967184+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 18, "whyItWorks": null, "antipattern": null, "cardinality": "common", "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 19, "arc": { "name": "AIDA", "slug": "aida", "status": "active", "bestFor": "Marketing presentations, product launches, sales enablement", "canonId": "019dd956-5fb4-77aa-866d-f9bdd47803af", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Attention -> Interest -> Desire -> Action", "description": null, "familyLabel": null }, "from": 18, "name": "Action", "beatId": "019de067-2e3b-713c-b0d7-a0b5435c3588", "matchId": "019de067-2d91-7264-a72e-b60277f83dc2", "beatType": null, "evidence": "Marketplace value prop and conclusion CTAs", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 72 }, { "to": 19, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null }, "from": 18, "name": "Impact & Next Steps", "beatId": "019de067-2f70-72a7-86fa-6ab4de4ac5bb", "matchId": "019de067-2e65-73ce-8e5b-7d2ab9a39fa9", "beatType": null, "evidence": "Marketplace value prop and CTA links", "position": 5, "isPrimaryArc": false, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 48 } ], "loops": [ { "to": 18, "from": 16, "loop": { "name": "33_build_up", "slug": "33-build-up", "status": "active", "bestFor": "Pricing justification, cost estimation, market sizing", "canonId": "019dd956-733a-746e-88fd-04b2e4b51b61", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Base -> Add Component A -> Add Component B -> Add Component C -> The Total", "description": "Start from zero and add components to arrive at a total", "familyLabel": null }, "matchId": "019de067-3016-7644-b28d-b82150ce5bd6", "evidence": "Catalog breadth (p16) + deployment architecture (p17) + three-pillar value prop (p18) builds Marketplace pitch.", "position": 4, "objective": "Position AWS Marketplace as the operational layer", "confidence": 65, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null } } ], "locked": true }, { "page": 19, "type": "setup", "function": "state_next_steps", "rawType": "closing_ask", "block": null, "metadata": { "slideType": "closing_ask", "slideTypeCanon": { "name": "Closing ask", "slug": "closing_ask", "status": "active", "canonId": "019de52d-0aa4-750f-8aa1-8d622dd99f5c", "version": 1, "description": null }, "function": "state_next_steps", "functionCanon": { "name": "State next steps", "slug": "state_next_steps", "status": "active", "canonId": "019de52d-14ca-70ac-b534-971f458cdf29", "version": 1, "description": null }, "density": "balanced", "densityScore": 47, "componentCount": 5, "textChars": 889, "nDataPoints": 0, "notes": null, "elementsJson": [ "headline_text", "paragraph", "icon_grid" ], "confidence": 1, "extraction": { "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "at": "2026-05-02 17:43:46.304+00", "seconds": 2.185, "promptVersion": "v2-canon-conditioned" } }, "links": { "slide": "/slides/019dd923-5e88-73ef-bd5c-b1fd37abc6e1/19", "deck": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1", "deckAnchor": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1#slide-19", "deckJson": "/decks/019dd923-5e88-73ef-bd5c-b1fd37abc6e1.json" }, "components": [ { "bbox": { "h": 0.03, "w": 0.25, "x": 0.68, "y": 0.18 }, "kind": "callout", "text": "Key resources to get started", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": null, "subkind": { "name": "Primary callout", "slug": "primary", "status": "active", "canonId": "019de52c-fbd1-70eb-a9ce-8997f8674c1d", "version": 1, "description": null }, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:46.304+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "63e3528a-187a-4a76-82f1-6da3fa026154", "parentComponentId": null }, { "bbox": null, "kind": "callout", "text": "Whether you're just getting started or moving quickly to adopt solutions to improve operations, drive sales, or increase employee efficiency, AWS is here to help.", "attrs": null, "canon": { "kind": { "name": "Callout", "slug": "callout", "status": "active", "canonId": "019de52c-f8d3-761a-8953-7d37080de5e2", "version": 1, "description": "Highlighted callout box." }, "tool": { "name": "Visual emphasis", "slug": "visual-emphasis", "status": "active", "bestFor": null, "canonId": "019dd9e1-474b-736b-a8eb-a794dd88241c", "version": 1, "bodyDocId": null, "description": "Drawing the eye to one element above the rest of the slide.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": null, "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-25 11:59:00+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd952-41aa-7578-83cc-6e07cb9731d9", "parentComponentId": null }, { "bbox": { "h": 0.35, "w": 0.25, "x": 0.68, "y": 0.25 }, "kind": "list", "text": "Explore agentic AI on AWS\nDiscover AI agents, tools, and solutions in AWS Marketplace\nLearn essential AI skills with AWS AI League", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:46.304+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "23121b49-ee12-4abb-bc98-f28538651fab", "parentComponentId": null }, { "bbox": { "h": 0.35, "w": 0.55, "x": 0.06, "y": 0.18 }, "kind": "paragraph", "text": "In this eBook, we shared how agentic AI is changing organizations along with real-world transformation paths taken by AWS customers across various industries. You can find resources that provide an overview of AWS agentic services and hands-on learning to upskill your workforce. Find agents, tools, and solutions to meet your organizational needs and implement them quickly with AWS Marketplace. Whether you’re just getting started or moving quickly to adopt solutions to improve operations, drive sales, or increase employee efficiency, AWS is here to help.", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:46.304+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "16fd87c5-cdfc-4e2d-9f26-89dab6ec91bb", "parentComponentId": null }, { "bbox": { "h": 0.04, "w": 0.15, "x": 0.06, "y": 0.08 }, "kind": "title", "text": "Conclusion", "attrs": null, "canon": { "kind": { "name": "Title", "slug": "title", "status": "active", "canonId": "019de52c-f7dd-76d9-b848-b1f12bd85cf4", "version": 1, "description": "Slide title or headline." }, "tool": null, "subkind": { "name": "Headline", "slug": "headline", "status": "active", "canonId": "019de52c-fae1-7463-9a7c-d60668eced0d", "version": 1, "description": null }, "framework": null }, "subkind": "headline", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:43:46.304+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "bda3cb2e-fc5f-4a9e-99c7-381cb284b4b6", "parentComponentId": null } ], "metrics": [], "tools": [ { "tool": { "name": "Closing Techniques", "slug": "closing-techniques", "status": "active", "bestFor": null, "canonId": "019dd956-af13-774b-a4fd-7db0a3a88d51", "version": 1, "bodyDocId": null, "description": "Strong endings: Callback, challenge, vision, clear CTA, memorable line", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Storyteller", "layer": "slide", "agents": [ "Storyteller" ], "matchId": "019de067-37fa-7482-b950-b6417770c1de", "evidence": "Conclusion slide with three explicit CTA links", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 80, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 19, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Nudge", "slug": "nudge", "status": "active", "bestFor": null, "canonId": "019dd956-c61a-72f9-920c-88acf4ecc336", "version": 1, "bodyDocId": null, "description": "Subtle hints can significantly affect decisions - strategic CTA placement", "familyLabel": null, "categoryName": "Slide", "categorySlug": "slide" }, "agent": "Designer", "layer": "slide", "agents": [ "Architect", "Designer" ], "matchId": "019de067-3824-7568-8f0b-00d0fa4ada47", "evidence": "purple sidebar surfaces next-step links prominently", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 55, "extraction": { "at": "2026-04-30 21:59:11.25834+00", "model": "claude-cli", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 19, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null }, { "tool": { "name": "Storytelling: the closing ask", "slug": "closing-ask", "status": "active", "bestFor": null, "canonId": "019df269-24e0-70ab-8dd9-983832c1c665", "version": 1, "bodyDocId": "019df269-24bc-7554-b88d-245127606b8d", "description": "The single most important slide in the deck — after the cover. The final", "familyLabel": "narrative-block", "categoryName": "Narrative & Transformation", "categorySlug": "narrative-transformation" }, "agent": "storyteller", "layer": "slide", "agents": [ "storyteller" ], "matchId": "a02443be-76f2-47de-96e6-e249b2039d63", "evidence": "The slide has a title 'Conclusion' and a callout with a primary key resource.", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.8, "extraction": { "at": "2026-07-16 21:56:04.039098+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 19, "whyItWorks": null, "antipattern": null, "cardinality": null, "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 19, "arc": { "name": "AIDA", "slug": "aida", "status": "active", "bestFor": "Marketing presentations, product launches, sales enablement", "canonId": "019dd956-5fb4-77aa-866d-f9bdd47803af", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Attention -> Interest -> Desire -> Action", "description": null, "familyLabel": null }, "from": 18, "name": "Action", "beatId": "019de067-2e3b-713c-b0d7-a0b5435c3588", "matchId": "019de067-2d91-7264-a72e-b60277f83dc2", "beatType": null, "evidence": "Marketplace value prop and conclusion CTAs", "position": 4, "isPrimaryArc": true, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 72 }, { "to": 19, "arc": { "name": "The Consultant's Gambit", "slug": "consultants-gambit", "status": "active", "bestFor": "Business cases, project proposals, strategic recommendations", "canonId": "019dd956-5e0a-73c8-b305-81c38c959e9c", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Situation & Context -> Problem & Complication -> Solution & Approach -> Evidence & Proof -> Impact & Next Steps", "description": null, "familyLabel": null }, "from": 18, "name": "Impact & Next Steps", "beatId": "019de067-2f70-72a7-86fa-6ab4de4ac5bb", "matchId": "019de067-2e65-73ce-8e5b-7d2ab9a39fa9", "beatType": null, "evidence": "Marketplace value prop and CTA links", "position": 5, "isPrimaryArc": false, "parentBeatType": null, "alignedBlockIds": null, "matchConfidence": 48 } ], "loops": [], "locked": true } ], "arcBeats": [ { "from": 1, "to": 3, "label": "Attention", "description": "cover, TOC and intro frame the topic" }, { "from": 4, "to": 7, "label": "Interest", "description": "maturity baseline, definitions, IDC adoption curve" }, { "from": 8, "to": 17, "label": "Desire", "description": "case studies, industries, AWS services, AgentCore stack" }, { "from": 18, "to": 19, "label": "Action", "description": "Marketplace value prop and conclusion CTAs" } ], "loops": [ { "from": 3, "to": 7, "label": "Zoom In", "description": "Establish what agentic AI is and where the market is going" }, { "from": 8, "to": 10, "label": "Pattern Hunter", "description": "Show real-world adoption proves agentic AI works" }, { "from": 11, "to": 15, "label": "Build Up", "description": "Build up the AWS agentic stack as a complete solution" }, { "from": 16, "to": 18, "label": "Build Up", "description": "Position AWS Marketplace as the operational layer" } ] }