Context Engineering
Context engineering is deliberately assembling the information an AI model needs — instructions, constraints, decisions — and keeping it true over time.
Context engineering is the discipline of getting the right information in front of an AI model at the right time — and keeping it true as reality changes. For coding agents, the highest-value context is often the set of approved decisions the agent would otherwise never see.
Why it beats prompt engineering alone
You can phrase a prompt perfectly and still get wrong output if the model lacks a constraint the team agreed on last week. Context engineering treats that constraint as a first-class input — delivered via MCP, retrieval, or memory — not an afterthought.
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- Is context engineering the same as prompt engineering?
- No. Prompt engineering is about how you phrase an instruction. Context engineering is broader: it's about what information reaches the model — retrieval, memory, tool results, injected decisions — and keeping it accurate over time.
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