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  "documentTitle": "Eximius Ventures Just an Agent Away An AI Thesis",
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  "notes": "Includes a visual comparison of compute allocation across pre-training, post-training, and inference phases for standard LLMs vs. reasoning models.",
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      "text": "However, this added compute significantly raises costs and can cause latency to spike—sometimes by factors of 10 or more. Tests indicate a multiple-fold jump in expenses compared to standard models, so the trade-off is substantial.",
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      "text": "In agentic architectures, o1’s benefits become especially clear at higher planning and decision-making levels. Traditional AI agents typically orchestrate multiple specialised models—one for conversation, another for domain-specific retrieval, and so on.",
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