AI, Knowledge & Understanding
How to reason about model performance, automation, memory, explanation and the boundary between fluent output and justified knowledge.
ESSENTIAL READING
A useful sequence, not an endless feed.
Build an Assumption Register Before a Plan Hardens
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Ten Links Can Still Be One Source
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How to Separate a Claim, the Evidence, and the Inference Between Them
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Intelligence Is Not Evidence of Consciousness
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How to Learn AI Without Chasing Every Model Release
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A Model Can Be Right for the Wrong Reason
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AI and the End of Knowing Who Made What
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The Feeling of Understanding Is Not Understanding
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Automation Does Not Remove Responsibility
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An AI Explanation Is Not the Mechanism
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A Dataset Is Not the World
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A Forecast Is Not the Future
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How to Write an AI Decision Record
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How to Compare Two AI Answers Without Voting by Vibe
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How to Build an Evidence Ledger for AI-Assisted Work
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How to Audit an AI Workflow Before You Automate It
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What AI Chatbots Remember: ChatGPT vs Claude vs Gemini Memory Controls
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Local AI Without the Hype: Ollama vs LM Studio—and When Cloud Is Better
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The Best Books to Understand AI Without the Hype
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HOW TO USE THIS PATH
Move from claim to evidence to practice.
01Begin with the framing.Identify the claim before accepting the metaphor.
02Inspect the evidence.Separate observation, inference and speculation.
03Run the practice.Keep what improves judgment or agency.