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Demand-Driven Context: A Methodology for Coherent Knowledge Bases Through Agent Failure

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youtube.com
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AI Engineer
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Context

An 's failed attempt can help identify which organizational knowledge needs documenting. This workshop proposes giving agents real problems, examining where missing information blocks them, and adding that knowledge to a shared base.

The published description calls for growing the collection problem by problem and storing it in Markdown, with agents of different roles using the same shared material. The intended benefit is a closer connection between documentation effort and questions that arise in actual work: each addition addresses a demonstrated information gap.

Terms in this piece · Glossary
  • AI agent — An AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.
  • context window — The maximum amount of text a model can consider at once — its working memory for the current conversation or task.
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