Context engineering

Plain English. Deciding what goes into a model's context window at each step: which files, which history, which tool results. Includes fighting "context rot" — performance degrading as the window fills with stale material — and "compaction", summarising history to reclaim space. The successor discipline to prompt engineering.

Why it moves money. It is capability without new training, at software cost. OpenAI tripled its ARC-AGI-3 score — 13.3% to 38.3% under the official harness — by enabling two existing settings, retained reasoning and compaction. A research paper argues production agents fail less from weak reasoning than from unmanaged context. And providers are quietly sealing context state (encrypted reasoning, opaque compaction) into their platforms — a switching-cost play worth pricing.

What to watch. Whether context state stays portable across providers or hardens into provider-sealed lock-in; where compaction happens — in your harness or their API.

From the signals. Two API settings tripled OpenAI's ARC-AGI-3 score. A paper argues agents fail at context management, not reasoning. Provider-sealed state: the session you cannot take with you.

Further reading. Anthropic, "Effective context engineering for AI agents".