Why You're Doing Context Engineering Wrong
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Context engineering — the practice of feeding AI agents the right data at the right time — is widely misunderstood. Common mistakes include stuffing large context windows with raw data (causing context confusion, poisoning, distraction, and clash), ignoring latency budgets, and failing to keep vector metadata fresh. The real
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How we are doing context engineering wrongThe right way to do context engineeringMaterialize: Live data architecture for AI context engineeringNext stepsSort: