Lesson 890 of 1596
Setting Context-Window Budget Policies for Long-Running Agents
How to keep an agent's context window from filling with noise mid-run.
Creators · Agentic AI · ~24 min read
The premise
Long-running agents drown in their own scratchpad — explicit pruning rules outperform 'just use a bigger model'.
What AI does well here
- Summarize the last N turns into a structured digest each time
- Drop tool outputs that are no longer referenced
- Pin the user goal and key constraints at the top, immune to pruning
- Track context-window utilization as a first-class metric
What AI cannot do
- Recover a fact pruned out without re-fetching its source
- Summarize losslessly — pruning is always lossy
- Decide what's important without a stated objective
Key terms in this lesson
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