{ "schemaVersion": "deck-intelligence.v1", "id": "019dd923-5e88-73ef-bd5d-6e331a5623a1", "slug": "e228a35ad9610ecc", "title": "2016 Benedict Evans 2016 Mobile is Eating the World", "subtitle": "Benedict Evans", "author": "Benedict Evans", "pageCount": 78, "kind": "consulting-deck", "orientation": "landscape", "aspectRatio": 1.777, "document": { "id": "019dd923-5e88-73ef-bd5d-6e331a5623a1", "slug": "e228a35ad9610ecc", "title": "2016 Benedict Evans 2016 Mobile is Eating the World", "rawTitle": "2016 Benedict Evans 2016 Mobile is Eating the World", "authorId": "BenedictEvans", "authorName": "Benedict Evans", "authorDisplay": "Benedict Evans", "kind": { "slug": "consulting-deck", "label": "Consulting deck" }, "sourceType": { "slug": "independent_analyst", "label": "Independent analyst" }, "fileName": "2016-Benedict-Evans-2016-Mobile-is-Eating-the-World.pdf", "sourceUrl": "http://www.ben-evans.com", "sourceDate": "2016-11-01 00:00:00", "presentationDate": null, "ingestedAt": "2026-04-25 11:55:49+00", "status": "ready", "pageCount": 78, "orientation": "landscape", "aspectRatio": 1.777, "targetCompany": null, "targetTicker": null, "metadata": { "local_root": "/tmp/legacy-images/e228a35ad9610ecc", "origin_corpus": "consulting" } }, "coverage": { "pageCount": 78, "pagesIndexed": 78, "pagesWithImages": 78, "pagesWithMetadata": 78, "imageCoveragePct": 100, "metadataCoveragePct": 100, "componentCount": 374, "chartCount": 22, "metricSlides": 0, "toolMatches": 219, "documentToolMatches": 0, "frameworkMatches": 30, "arcMatches": 2, "beatMatches": 10, "loopMatches": 10, "patternMatches": 0, "storymakersMatch": true, "scoreAvailable": true, "reviewAvailable": true, "activistThesisAvailable": false, "pitchdeckMetadataAvailable": false, "pitchdeckProfileAvailable": false }, "blocks": [], "matches": { "arcs": [ { "arc": { "name": "The Onion", "slug": "onion", "status": "active", "bestFor": "Root cause analysis, diagnostics", "canonId": "019dd956-627f-76b1-b286-0c575846d572", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Surface Observation -> First Layer -> Deeper Layer -> Core Insight -> Implications", "description": null, "familyLabel": null, "categoryName": "Analysis & Information", "categorySlug": "analysis-information" }, "matchId": "019dd95a-0543-7581-99b3-3488347b0c4f", "evidence": "Deck peels progressively deeper: mobile scale (p.4-8) -> GAFA scale (p.9-21) -> ML emergence (p.22-35) -> new computing model (p.36-48) -> industry implications (p.49-77).", "isPrimary": true, "confidence": 78, "extraction": { "at": "2026-04-29 13:07:28.977035+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null } }, { "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null, "categoryName": "Narrative & Transformation", "categorySlug": "narrative-transformation" }, "matchId": "019dd95a-0543-7581-99b3-3ac1efa6d607", "evidence": "Constant oscillation between What-Is (PC/Wintel/ICE cars/old retail) and What-Could-Be (mobile/GAFA/electric+autonomy/aggregator retail) across every section.", "isPrimary": false, "confidence": 55, "extraction": { "at": "2026-04-29 13:07:28.977035+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null } } ], "beats": [ { "to": 8, "arc": { "name": "The Onion", "slug": "onion", "status": "active", "bestFor": "Root cause analysis, diagnostics", "canonId": "019dd956-627f-76b1-b286-0c575846d572", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Surface Observation -> First Layer -> Deeper Layer -> Core Insight -> Implications", "description": null, "familyLabel": null, "categoryName": "Analysis & Information", "categorySlug": "analysis-information" }, "from": 4, "name": "Surface Observation", "beatId": "019dd95a-07a7-7579-bd64-81f214886d60", "matchId": "019dd95a-0543-7581-99b3-3488347b0c4f", "beatType": { "name": "Surface Observation", "slug": "onion-surface-observation", "status": "active", "canonId": "019dd9b8-0b39-73c0-b415-6c4cf34cc343", "version": 1, "description": null }, "evidence": "halfway-connected, S-curve passing PC, deployment phase framing", "position": 1, "isPrimaryArc": true, "parentBeatType": { "name": "Setup", "slug": "setup", "status": "active", "canonId": "019dd9b8-020e-7505-af9b-d9b9a4679bcc", "version": 1, "description": "Where the deck grounds the reader before doing anything else. 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Required in 19/20 arcs. The exception (Sparkline) ends with new bliss which is functionally a resolution." }, "alignedBlockIds": null, "matchConfidence": 55 } ], "loops": [ { "to": 7, "from": 4, "loop": { "name": "15_why_now", "slug": "15-why-now", "status": "active", "bestFor": "Sales pitches, fundraising, requesting immediate budget approval", "canonId": "019dd956-6c00-70cd-bd42-6bacc4af726f", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Context (Trends) -> The Trigger Event -> The Window of Opportunity", "description": "Create temporal urgency by proving that the window of opportunity is opening or closing", "familyLabel": null, "categoryName": "Urgency", "categorySlug": "urgency" }, "matchId": "019dd95a-08f8-7619-ac2d-d8ea0863a4e5", "evidence": "Trend (5bn mobiles), trigger (S-curve passing PC), opportunity window framed at 2.5bn smartphones.", "position": 1, "objective": "Establish that mobile is shifting from creation to deployment phase", "confidence": 75, 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"extraction": { "at": "2026-04-29 13:07:29.779839+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null } }, { "to": 29, "from": 23, "loop": { "name": "03_aha_moment", "slug": "03-aha-moment", "status": "active", "bestFor": "Data-heavy sections, research findings, analytical arguments", "canonId": "019dd956-66f4-7668-ab25-cec9c996c0bc", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Problem/Question -> What the Data Shows -> The Insight", "description": "Establish a tension, present data, then deliver the insight that changes everything", "familyLabel": null, "categoryName": "Narrative", "categorySlug": "narrative" }, "matchId": "019dd95a-08f8-7619-ac2d-e6e83775481e", "evidence": "Question (dog in picture) -> data (error rates collapsing) -> insight (data not rules, AI-first).", "position": 4, "objective": "Reveal that ML has crossed an accuracy threshold and generalises", "confidence": 78, "extraction": { "at": 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13:07:29.779839+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null } }, { "to": 48, "from": 37, "loop": { "name": "21_before_after", "slug": "21-before-after", "status": "active", "bestFor": "Product demos, process improvements, ROI justification", "canonId": "019dd956-6e68-73fd-a295-fe90145c2da8", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Old Way (Pain) -> The Moment of Change -> The New Way (Glory) -> The Measurable Delta", "description": "Show the dramatic contrast between the old way and the new way through side-by-side comparison", "familyLabel": null, "categoryName": "Comparison", "categorySlug": "comparison" }, "matchId": "019dd95a-08f8-7619-ac2d-ef21c35704af", "evidence": "Apps win mobile -> new computing model -> frictionless -> direct-physical interaction (delta is the title verbatim).", "position": 6, "objective": "Show shift from old PC computing to new mobile-native, frictionless paradigm", "confidence": 78, "extraction": { "at": "2026-04-29 13:07:29.779839+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null } }, { "to": 54, "from": 50, "loop": { "name": "10_iceberg", "slug": "10-iceberg", "status": "active", "bestFor": "Consulting, complex problem solving, organizational change", "canonId": "019dd956-69f4-738c-852a-643798da0899", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Symptom (Visible) -> The System (Hidden) -> The Root Cause", "description": "Reveal that the visible problem is merely a symptom of a deeper root cause", "familyLabel": null, "categoryName": "Analysis", "categorySlug": "analysis" }, "matchId": "019dd95a-08f8-7619-ac2d-f2ac3c6334c3", "evidence": "Symptom (retailers as newspapers) -> system (logistics works, demand-gen doesn't) -> root ('lets you buy, not shop').", "position": 7, "objective": "Diagnose retail's surface struggle down to the demand-generation root cause", "confidence": 72, "extraction": { "at": "2026-04-29 13:07:29.779839+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null } }, { "to": 63, "from": 55, "loop": { "name": "09_precedent", "slug": "09-precedent", "status": "active", "bestFor": "Risk mitigation, strategy validation, building confidence in new approaches", "canonId": "019dd956-695f-7615-8f82-39d919918314", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Precedent Case -> What Happened -> The Parallel -> Applied Learning", "description": "Use historical or external examples to validate your approach", "familyLabel": null, "categoryName": "Validation", "categorySlug": "validation" }, "matchId": "019dd95a-08f8-7619-ac2d-f64e0e3bc356", "evidence": "$1tr ad spend -> ML curation -> Walmart precedent -> $22tr future sectors.", "position": 8, "objective": "Use Walmart's tech-led retail disruption as precedent for ML-driven demand generation", "confidence": 68, "extraction": { "at": "2026-04-29 13:07:29.779839+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null } }, { "to": 72, "from": 65, "loop": { "name": "08_analogy", "slug": "08-analogy", "status": "active", "bestFor": "Complex concepts, new markets, technical explanations for non-experts", "canonId": "019dd956-6901-7032-ba44-96eaed94c949", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Familiar Domain -> Key Parallel -> Applied to Our Situation -> Insight", "description": "Explain the unfamiliar through a well-understood parallel domain", "familyLabel": null, "categoryName": "Explanation", "categorySlug": "explanation" }, "matchId": "019dd95a-08f8-7619-ac2d-f81c27bdff28", "evidence": "Cars-as-phones (p.65) -> two paths (p.66) -> battery curve -> 'precedent - unbundling phones' (p.69) -> moat questions.", "position": 9, "objective": "Apply phones-unbundling analogy to predict cars disruption", "confidence": 80, "extraction": { "at": "2026-04-29 13:07:29.779839+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null } }, { "to": 77, "from": 73, "loop": { "name": "26_ripple_effect", "slug": "26-ripple-effect", "status": "active", "bestFor": "Change management, scaling initiatives, demonstrating broad value", "canonId": "019dd956-7075-7564-a134-cbde706dcfe0", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "Individual Impact -> Team Impact -> Organizational Impact -> Market/Industry Impact", "description": "Show how impact spreads from individual to team to organization to market", "familyLabel": null, "categoryName": "Causation", "categorySlug": "causation" }, "matchId": "019dd95a-08f8-7619-ac2d-ffd2ba88f8d8", "evidence": "Self-driving = horseless carriage -> obvious impact (oil/safety) -> second-order x2 -> biggest changes unknowable.", "position": 10, "objective": "Cascade autonomy's effects from obvious safety to unknowable 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a question opening a section transition.", "confidence": 75 }, { "id": 109, "slug": "information-gap-theory", "layer": "Loop", "evidence": "Open question creates curiosity for what follows.", "confidence": 70 } ], "page_number": 33 }, { "tools": [ { "id": 118, "slug": "action-titles", "layer": "Slide", "evidence": "Title names a framework: 'Complexity and abstraction'.", "confidence": 75 } ], "page_number": 34 }, { "tools": [ { "id": 118, "slug": "action-titles", "layer": "Slide", "evidence": "Title 'machine learning S-Curve' is the insight.", "confidence": 90 }, { "id": 121, "slug": "metaphor-analogy", "layer": "Slide", "evidence": "Same Carlota-Perez S-curve template, applied to ML.", "confidence": 90 }, { "id": 98, "slug": "callback", "layer": "Loop", "evidence": "Reuses the exact mobile S-curve graphic from p.6 for ML - explicit callback.", "confidence": 85 } ], "page_number": 35 }, { "tools": [ { "id": 118, "slug": "action-titles", "layer": "Slide", "evidence": "Title 'apps have 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"confidence": 70 } ], "page_number": 51 }, { "tools": [ { "id": 118, "slug": "action-titles", "layer": "Slide", "evidence": "Title 'mostly, what you already know you want' is the diagnosis.", "confidence": 80 }, { "id": 154, "slug": "concrete-language", "layer": "Slide", "evidence": "12% online share figure.", "confidence": 70 } ], "page_number": 52 }, { "tools": [ { "id": 118, "slug": "action-titles", "layer": "Slide", "evidence": "Title 'People will buy online if they know about it'.", "confidence": 85 }, { "id": 158, "slug": "von-restorff-effect", "layer": "Slide", "evidence": "Surprising reframe: Amazon as 4th-largest apparel retailer.", "confidence": 70 } ], "page_number": 53 }, { "tools": [ { "id": 118, "slug": "action-titles", "layer": "Slide", "evidence": "Title is the pivotal question: 'But how do you know what to buy?'.", "confidence": 90 }, { "id": 67, "slug": "curiosity-gap", "layer": "Block", "evidence": "Lets-you-buy-not-shop reframes shopping as the unmet job.", "confidence": 80 }, { "id": 78, "slug": "contrast-pairs", "layer": "Slide", "evidence": "buy <-> shop contrast in the callout.", "confidence": 75 } ], "page_number": 54 }, { "tools": [ { "id": 118, "slug": "action-titles", "layer": "Slide", "evidence": "Title 'Digital demand generation, step 1: spend $1tr'.", "confidence": 85 }, { "id": 154, "slug": "concrete-language", "layer": "Slide", "evidence": "$1tr / $500bn ad+marketing figures.", "confidence": 85 }, { "id": 158, "slug": "von-restorff-effect", "layer": "Slide", "evidence": "Trillion-dollar number sized to shock.", "confidence": 65 }, { "id": 9, "slug": "precedent", "layer": "Loop", "evidence": "Loop opens by sizing the demand-gen prize before invoking the Walmart precedent.", "confidence": 60 } ], "page_number": 55 }, { "tools": [ { "id": 155, "slug": "credibility-transfer", "layer": "Slide", "evidence": "Bezos-style quote 'Your margin is my opportunity' borrows authority.", "confidence": 80 }, { "id": 169, "slug": 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"evidence": "Specific $22,000bn figure.", "confidence": 80 } ], "page_number": 63 }, { "tools": [ { "id": 118, "slug": "action-titles", "layer": "Slide", "evidence": "Title 'Cars as phones' is the analogy/thesis.", "confidence": 90 }, { "id": 121, "slug": "metaphor-analogy", "layer": "Slide", "evidence": "Direct analogy cars<->phones.", "confidence": 90 }, { "id": 8, "slug": "argument-from-analogy", "layer": "Loop", "evidence": "Whole loop runs on the phones-precedent template.", "confidence": 85 } ], "page_number": 65 }, { "tools": [ { "id": 118, "slug": "action-titles", "layer": "Slide", "evidence": "Title 'Two paths for disrupting cars'.", "confidence": 85 }, { "id": 78, "slug": "contrast-pairs", "layer": "Slide", "evidence": "Two-column layout: Electric vs Autonomy with chevron divider.", "confidence": 90 }, { "id": 161, "slug": "law-of-similarity", "layer": "Slide", "evidence": "Identical bullet styling on both columns groups them as parallel paths.", "confidence": 70 } ], "page_number": 66 }, { "tools": [ { "id": 118, "slug": "action-titles", "layer": "Slide", "evidence": "Title 'Going electric: riding the battery cost curve'.", "confidence": 85 }, { "id": 121, "slug": "metaphor-analogy", "layer": "Slide", "evidence": "'Riding the cost curve' as wave-metaphor.", "confidence": 70 } ], "page_number": 67 }, { "tools": [ { "id": 118, "slug": "action-titles", "layer": "Slide", "evidence": "Title 'Electric unbundles cars'.", "confidence": 85 }, { "id": 86, "slug": "causal-chain", "layer": "Slide", "evidence": "Electric -> fewer parts -> commoditisation chain.", "confidence": 70 } ], "page_number": 68 }, { "tools": [ { "id": 118, "slug": "action-titles", "layer": "Slide", "evidence": "Title 'Precedent - unbundling phones' names the device.", "confidence": 90 }, { "id": 8, "slug": "argument-from-analogy", "layer": "Slide", "evidence": "GSM/phones unbundling applied to cars.", "confidence": 80 } ], "page_number": 69 }, { "tools": [ { "id": 118, "slug": "action-titles", "layer": "Slide", "evidence": "Title '(Unfair but relevant - capex scale)' frames the comparison.", "confidence": 80 }, { "id": 154, "slug": "concrete-language", "layer": "Slide", "evidence": "$14.6bn capex figure.", "confidence": 80 }, { "id": 159, "slug": "contrast-principle", "layer": "Slide", "evidence": "Tech capex vs auto-OEM capex compared.", "confidence": 75 } ], "page_number": 70 }, { "tools": [ { "id": 118, "slug": "action-titles", "layer": "Slide", "evidence": "Title 'Meanwhile, progress to autonomy'.", "confidence": 80 } ], "page_number": 71 }, { "tools": [ { "id": 118, "slug": "action-titles", "layer": "Slide", "evidence": "Title is the question 'Where is the competitive moat in cars?'.", "confidence": 85 }, { "id": 67, "slug": "curiosity-gap", "layer": "Block", "evidence": "Open question + 'lots of unanswered questions' callout.", "confidence": 75 }, { "id": 131, "slug": "gestalt-principles", "layer": "Slide", "evidence": "Three enclosed circles + arrows 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"anaphora", "layer": "Loop", "evidence": "Repeats 'But' opening with p.76.", "confidence": 65 } ], "page_number": 75 }, { "tools": [ { "id": 118, "slug": "action-titles", "layer": "Slide", "evidence": "Title repeats p.75 verbatim with extended callout.", "confidence": 75 }, { "id": 113, "slug": "mere-exposure-effect", "layer": "Loop", "evidence": "Repeated title reinforces the second-order-effects message.", "confidence": 60 } ], "page_number": 76 }, { "tools": [ { "id": 118, "slug": "action-titles", "layer": "Slide", "evidence": "Title '...And the biggest changes are unknowable'.", "confidence": 80 }, { "id": 124, "slug": "closing-techniques", "layer": "Slide", "evidence": "Memorable closing line opens up to mystery.", "confidence": 75 } ], "page_number": 77 }, { "tools": [ { "id": 124, "slug": "closing-techniques", "layer": "Slide", "evidence": "Final 'Thank you' slide.", "confidence": 60 } ], "page_number": 78 } ], "slides_seen": 78, "deck_summary": "Strong slide-level Storymakers alignment - every page uses action titles, recurring metaphors (S-curve, cars-as-phones, retailers-as-newspapers), and concrete numerals - but the macro shape is exploratory analyst narrative (Onion / Sparkline) rather than a recommendation arc; there is no client, no ask, and no Now-What.", "secondary_arcs": [ { "id": 7, "slug": "sparkline", "beats": [ { "name": "What Is", "end_page": 8, "evidence": "PC era + mobile passing it", "position": 1, "start_page": 4 }, { "name": "What Could Be", "end_page": 21, "evidence": "GAFA scale beyond Wintel", "position": 2, "start_page": 10 }, { "name": "What Is", "end_page": 38, "evidence": "current computing/ML state", "position": 3, "start_page": 22 }, { "name": "What Could Be", "end_page": 63, "evidence": "new computing model + retail transformation", "position": 4, "start_page": 39 }, { "name": "New Bliss", "end_page": 77, "evidence": "future of cars and cities reshaped", "position": 5, "start_page": 64 } ], "evidence": "Constant oscillation between What-Is (PC/Wintel/ICE cars/old retail) and What-Could-Be (mobile/GAFA/electric+autonomy/aggregator retail) across every section.", "confidence": 55 } ], "images_inspected": 7, "slide_frameworks": [ { "frameworks": [ { "name": "Technology Adoption S-Curve", "slug": "s-curve", "evidence": "Title names 'S-Curve'; chart shows mobile vs PC adoption curves.", "confidence": 85 } ], "page_number": 5 }, { "frameworks": [ { "name": "Carlota Perez S-Curve (Creation/Deployment)", "slug": "carlota-perez-s-curve", "evidence": "Phases labelled Crazy idea -> Frenzy -> Scaling -> Maturity, with Creation/Deployment bands.", "confidence": 85 } ], "page_number": 6 }, { "frameworks": [ { "name": "Carlota Perez S-Curve (Creation/Deployment)", "slug": "carlota-perez-s-curve", "evidence": "Same labelled S-curve template, with ML positioned at 'Crazy idea/Creation'.", "confidence": 85 } ], "page_number": 35 }, { "frameworks": [ { "name": "Two-Path Comparison", "slug": "two-column-comparison", "evidence": "Side-by-side Electric vs Autonomy columns with chevron divider.", "confidence": 70 } ], "page_number": 66 } ] }, "matchedAt": "2026-04-27 09:07:25+00", "slidesSeen": 78, "deckSummary": "Strong slide-level Storymakers alignment - every page uses action titles, recurring metaphors (S-curve, cars-as-phones, retailers-as-newspapers), and concrete numerals - but the macro shape is exploratory analyst narrative (Onion / Sparkline) rather than a recommendation arc; there is no client, no ask, and no Now-What.", "imagesInspected": 7, "extractionSeconds": 558.7177 }, "score": { "backend": "codex", "scoredAt": "2026-05-02 15:28:19.089+00", "subScores": { "scqa_arc": 72, "action_titles": 68, "mece_structure": 64, "closing_strength": 42, "evidence_quality": 80, "clarity_of_thesis": 86, "production_quality": 80, "visual_storytelling": 85 }, "totalScore": 72, "coveragePct": 100, "explanations": { "scqa_arc": "The deck has a loose SCQA shape from mobile deployment context in slides 4-8 to implication answers in later sections, but it reads more like a thought-leadership essay than a tightly resolved consulting argument.", "action_titles": "Many titles are insight-bearing, but the deck also relies on labels or questions; a strong example is slide 12, \"... But GAFA has 10x the scale.\"", "mece_structure": "The section flow is coherent but not MECE, because blocks such as machine learning, new kinds of computer, ecommerce, and cars overlap as examples of mobile-era disruption rather than forming an exhaustive structure.", "closing_strength": "The close lands on a philosophical synthesis in slide 77 and a thank-you slide in slide 78, but it does not provide a clear recommendation, call to action, or next steps.", "evidence_quality": "Major claims are often backed by charts and metrics, especially slides 10-15, 52-55, 61, 67, and 70, though some future-looking implications remain asserted or analogy-led.", "clarity_of_thesis": "The thesis is identifiable immediately in slides 1-5: \"Mobile is eating the world\" is reinforced by slides 4-5 on global mobile penetration and the smartphone S-curve passing the PC.", "production_quality": "Production is clean and consistent with strong whitespace, branded section dividers, chart footnotes on data-heavy slides, and 62 action-title fields across 78 slides, though headline discipline is uneven.", "visual_storytelling": "The deck usually matches message to medium well, using Marimekko and S-curve charts in slides 4-6, quote slides for pivots such as slide 29, and visual analogies in slides 50 and 73." }, "slidesAnalyzed": 78 }, "review": { "backend": null, "verdict": "This is a high-quality independent analyst thought-leadership deck with strong insight titles and evidence, but it is only a mid-to-strong Storymakers exemplar because the pillars and close are not recommendation-grade.", "reviewedAt": "2026-05-01 22:48:27.793+00", "slidesSeen": 78, "suggestions": [ "Add an executive synthesis after slide 2 or before slide 3 that states the full answer: mobile deployment has created global scale, AI is the next interface, and retail and cars are the clearest disruption arenas.", "Rewrite section dividers as claims, e.g. Mobile deployment changes the basis of competition, Machine learning makes sensors actionable, Retail shifts from logistics to demand generation, and Cars become software networks.", "Replace or precede slide 78 with a one-slide close that names 3 actions for investors or operators: follow demand-generation platforms, track AI-enabled interfaces, and map second-order industry effects." ], "closingScore": 58, "openingScore": 82, "topStrengths": [ "Slides 4-7 establish context with a tight progression: penetration, S-curve, lifecycle stage, and implications.", "Slides 10-16 build a clear scale argument, using Wintel vs GAFA comparisons before summarizing the new character of scale on slide 16.", "The deck uses recurring analogies and pull-quotes to make abstract shifts concrete, e.g. retailers as newspapers on slide 50 and self-driving as horseless carriage on slide 73." ], "topWeaknesses": [ "The main thesis fragments after slide 22; ML, new computing, ecommerce, and cars are all relevant but not explicitly tied back into one answer.", "Several section dividers are topic labels rather than argument-bearing pillars, especially slides 36, 49, and 64.", "The close stops at uncertainty on slide 77 and thanks on slide 78, without a recommendation, implications map, or what-to-do-now message." ], "narrativeScore": 74, "pillarCritique": "The section dividers are partially MECE: Mobile deployment, A new kind of scale, machine learning, new kinds of computer, ecommerce, and cars cover distinct themes. They read more like a curated topic map than a mutually exclusive answer tree because ML, new computing, retail, and cars overlap as consequences of the same mobile deployment thesis.", "closingCritique": "The last 5 slides avoid appendix sprawl and have a memorable philosophical close on slide 77. However, slides 74-78 do not convert the insight into a call to action; slide 78 is only a thank-you slide.", "openingCritique": "The first 5 slides are strong: slides 1-2 state the thesis in the title, slide 4 quantifies global penetration, and slide 5 gives the PC-to-mobile transition. The only drag is duplicate covers plus a divider before the proof.", "extractionSeconds": 88.552, "narrativeCritique": "The deck has a recognizable setup -> tension -> analysis -> resolution arc: slides 1-8 establish mobile deployment, slides 10-21 show the new scale, slides 22-76 analyze implications through ML, computing, ecommerce, and cars, and slide 77 resolves with uncertainty. 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Aligns with how readers actually consume decks — Heath & Heath's Find the Core, the journalist's nut graf, and Minto's governing thought all converge on the same cognitive economics.", "antipattern": "Topic titles disguised as core messages (Customer satisfaction, no verb, no stake); multi-thesis sentences stapled with and; hedged sentences (may show signs of possible softening); chart-caption titles (Revenue fell 4%) that restate what the chart already shows instead of naming the so-what; meta-commentary (this slide explores...) that describes the slide rather than concluding it.", "cardinality": null, "narrativePurpose": "Forces the slide author to do the interpretive work before the slide ships, so the audience does not have to do it during the meeting. Wins the WYSIATI battle on purpose — the loudest fragment on the page becomes the author's chosen sentence rather than whichever chart label happens to be largest." }, { "tool": { "name": "Thesis archetype", "slug": "thesis-archetype", "status": "active", "bestFor": null, "canonId": "019dd9e1-4b0b-7428-9b26-f171d1e753fb", "version": 1, "bodyDocId": null, "description": "A canonical investment / activist thesis shape (breakup, fraud, governance).", "familyLabel": null, "categoryName": null, "categorySlug": null }, "agent": null, "layer": "slide", "agents": null, "matchId": "99473f1c-92b8-488b-83e5-80adcb5bd764", "evidence": "The channel is the product", "pageRefs": null, "priority": null, "whenToUse": null, "confidence": 0.7, "extraction": { "at": "2026-07-16 21:58:43.623704+00", "model": "or:meta-llama/llama-4-scout", "runId": null, "seconds": null, "promptVersion": null }, "pageNumber": 57, "whyItWorks": null, "antipattern": null, "cardinality": "optional", "narrativePurpose": null } ], "frameworks": [], "arcBeats": [ { "to": 77, "arc": { "name": "The Onion", "slug": "onion", "status": "active", "bestFor": "Root cause analysis, diagnostics", "canonId": "019dd956-627f-76b1-b286-0c575846d572", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "Surface Observation -> First Layer -> Deeper Layer -> Core Insight -> Implications", "description": null, "familyLabel": null }, "from": 49, "name": "Implications", "beatId": "019dd95a-07a7-7579-bd64-9089dcf59100", "matchId": "019dd95a-0543-7581-99b3-3488347b0c4f", "beatType": { "name": "Implications", "slug": "onion-implications", "status": "active", "canonId": "019dd9b8-0dda-7730-893d-deaac7e9c295", "version": 1, "description": null }, "evidence": "ecommerce (retailers as newspapers) and cars (as phones) sections illustrate the consequences", "position": 5, "isPrimaryArc": true, "parentBeatType": { "name": "Reflection", "slug": "reflection", "status": "active", "canonId": "019dd9b8-0510-73fd-8d00-1c7e45f7bc98", "version": 1, "description": "The \"so what\" beat. Used by analytical arcs (Triple-take, Onion) and learning arcs (Voyage-return, Tragedy)." }, "alignedBlockIds": null, "matchConfidence": 78 }, { "to": 63, "arc": { "name": "The Sparkline", "slug": "sparkline", "status": "active", "bestFor": "Keynotes, TED-style talks", "canonId": "019dd956-606e-720c-905a-42607ac0bf50", "version": 1, "bodyDocId": "019df22a-2356-73eb-8061-d8c81dc0aa49", "structure": "What Is -> What Could Be -> What Is -> What Could Be -> New Bliss", "description": null, "familyLabel": null }, "from": 39, "name": "What Could Be", "beatId": "019dd95a-07a7-7579-bd64-a3d022fa4b81", "matchId": "019dd95a-0543-7581-99b3-3ac1efa6d607", "beatType": { "name": "What Could Be", "slug": "sparkline-what-could-be-4", "status": "active", "canonId": "019dd9b8-27e2-7569-ac66-6dc8c846d377", "version": 1, "description": null }, "evidence": "new computing model + retail transformation", "position": 4, "isPrimaryArc": false, "parentBeatType": { "name": "Turn", "slug": "turn", "status": "active", "canonId": "019dd9b8-0396-702b-ac2f-9901f8dd8b54", "version": 1, "description": "The pivot — solution proposed, catalyst introduced, decision made. Common (15/20 arcs) but not universal: Triple-take, AIDA, PAS, Voyage-return and Pixar substitute it with a strong reflection or development beat." }, "alignedBlockIds": null, "matchConfidence": 55 } ], "loops": [ { "to": 63, "from": 55, "loop": { "name": "09_precedent", "slug": "09-precedent", "status": "active", "bestFor": "Risk mitigation, strategy validation, building confidence in new approaches", "canonId": "019dd956-695f-7615-8f82-39d919918314", "version": 1, "bodyDocId": "019df22a-2420-77be-bc41-ded96d08cb21", "structure": "The Precedent Case -> What Happened -> The Parallel -> Applied Learning", "description": "Use historical or external examples to validate your approach", "familyLabel": null }, "matchId": "019dd95a-08f8-7619-ac2d-f64e0e3bc356", "evidence": "$1tr ad spend -> ML curation -> Walmart precedent -> $22tr future sectors.", "position": 8, "objective": "Use Walmart's tech-led retail disruption as precedent for ML-driven demand generation", "confidence": 68, "extraction": { "at": "2026-04-29 13:07:29.779839+00", "model": "claude-legacy", "runId": null, "seconds": null, "promptVersion": null } } ], "locked": true }, { "page": 58, "type": "tension", "title": "Uses a simple additive equation format to explain a complex AI value proposition.", "function": "frame_problem", "rawType": "problem_statement", "block": null, "metadata": { "slideType": "problem_statement", "slideTypeCanon": { "name": "Problem statement", "slug": "problem_statement", "status": "active", "canonId": "019de52d-0879-768d-bba8-8da8a5a121d4", "version": 1, "description": null }, "function": "frame_problem", "functionCanon": { "name": "Frame problem", "slug": "frame_problem", "status": "active", "canonId": "019de52d-13db-753e-ad70-e9b2d0dab398", "version": 1, "description": null }, "density": "balanced", "densityScore": 25, "componentCount": 4, "textChars": 388, "nDataPoints": 0, "notes": "Uses a simple additive equation format to explain a complex AI value proposition.", 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null, "subkind": { "name": "Process flow", "slug": "process", "status": "active", "canonId": "019de52d-039c-718f-ad3a-efe9c4b3c838", "version": 1, "description": null }, "framework": null }, "subkind": "process", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 17:42:43.015+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "24c4d14f-bcfd-49e0-9203-0eb8f3b0ec90", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.6, "x": 0.19, "y": 0.15 }, "kind": "paragraph", "text": "When can we infer taste and preference, without a purchase history or a salesperson?", "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", 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null, "extraction": { "at": "2026-05-02 17:42:43.015+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "d75a8389-fce3-4219-a4a0-d785616cd203", "parentComponentId": null } ], "metrics": [], "tools": [ { "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. 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(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": "Problem Statement Canvas", "slug": "problem-statement-canvas", "status": "active", "bestFor": null, "canonId": "019dd956-839d-744b-ad11-9bf3e3642a18", "version": 1, "bodyDocId": null, "description": "Structured definition of the problem: What? Who? Where? When? 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