How Context Compaction Works: Summarization That Shrinks Long Conversations Without Losing Key Points
blaizedsouza · x · 2026-09-24
Amit Shekhar (Outcome School) publishes a systematic explainer on context compaction in LLMs.
- Starts from next-token prediction and the context window, showing why long conversations overflow and why naive fixes fail
- Explains how summarization shrinks older messages while preserving key points
- Includes a step-by-step walkthrough, code examples, and where compaction sits in real AI agents
A solid intro for developers reasoning about agent memory management.
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