Context engineering is the practice of managing everything an AI model sees when it generates a response — instructions, memory, retrieved documents, and tool outputs — not just the prompt itself. As AI agents take on longer, multi-step tasks, deciding what enters the context window, and what stays out, has become as important as the model’s underlying capabilities. This hub covers the techniques, tools, and tradeoffs behind building reliable AI systems this way.
Context engineering is the practice of managing everything an AI model sees — instructions, memory, tools, retrieved data — not just the prompt. Here's what it means and why it matters for AI agents.
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