compact-memory-implementation

A developer guide for building compact memory into an Agent: detect when to compress, fork a compactor sub-agent, produce a structured summary, and restore it in the next session.

Step 1 — Understand the setup

Before designing anything, clarify:

• SDK / language: Claude Agent SDK? Direct Anthropic API? Python or TypeScript?
• Agent architecture: single-agent loop, multi-agent, tool-calling?
• Session model: one long-running session or multiple short sessions?
• What must survive compaction: task state, decisions, tool results, conversation history?

This determines which pattern fits.

Step 2 — When to trigger compact