Context Engineering
The craft of choosing what goes into an AI's context window, the stretch of text it reads before answering. That space is limited: fill it with everything « just in case » and the AI drowns and answers worse. Context engineering is deciding what to put in, in what order, and when to clear it, so every word earns its place.
Strengths
- Puts a clear name on a fuzzy skill, so you can discuss it as a team and pass it on
- A public benchmark to lean on: Anthropic cut over 80% of Claude Code system prompt with no degradation, evidence that a shorter context can beat an exhaustive one
- Goes hand in hand with two sibling ideas: keeping memory across sessions, and tending the tooling around the AI
Limitations
- Young topic: no reliable tool yet to measure whether your context is well-dosed, it stays judgment
Best for
- Devs, PMs and POs who want to structure how they prompt instead of guessing