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Designing what information enters, stays in, or leaves the model context so the agent has the right facts at the right time.
Context engineering is more than prompt writing: it covers retrieval, summaries, tool results, memory, ordering, and pruning. Good context makes the relevant facts cheap and visible; bad context hides signal inside stale logs and giant documents. Example: putting current task constraints near the end, cached docs up front, and noisy tool output behind a summary.
Plainly
Think of Context Engineering as a simple recipe for doing the work better. Designing what information enters, stays in, or leaves the model context so the agent has the right facts at the right time.
In practice
Use it when you need a repeatable method instead of guessing from vibes. In practice, define the owner, input, output, and failure mode before you rely on it.