Giving AI agents more context degrades performance; curated memory beats long context

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Loading an AI agent with excessive context—old reports, past conversations, and edge cases—causes it to make unrequested decisions and more mistakes, so agents perform better with a curated map of where rules, memory, and examples live rather than maximal context.