Prompt vs Context
A prompt is a one-shot instruction. Context is state that gets reworked continuously.
A good prompt gets the model to understand the task. Keeping it performing across many turns is context engineering.
Three moves in context engineering
1. Select
Before each turn, decide:
- Which parts of the system prompt stay?
- Which history messages can be folded into a summary?
- Which tool results can be dropped?
More is not better. Push 50K noise tokens into the window and the signal gets diluted.
2. Inject
Actively put the facts the model needs right now into the window:
- Current time
- User preferences and a summary of the session so far
- Which relevant tools are available and in what state
- What has already been tried
The model has no way to know any of this. You have to inject it explicitly.
3. Isolate
Subtasks get their own context. Split a long task into research → draft → proofread, and the proofreading step doesn’t need to see all the raw research material. It only needs the draft.
One simple rule
The context window is the model’s working memory, not its long-term memory.
Move meeting notes, user preferences, and stale information out of working memory, and leave only what this one step actually needs. That’s all context engineering is.