You will be able to
- Place information in internal knowledge, short-term memory (the context) or long-term memory by how often it's needed.
- Explain why a growing context fails twice: by overflowing the window, and by being used less reliably as it grows.
- Show why dropping the oldest messages can drop the task itself.
- Pin what must stay in the context and summarise (compact) the rest, testing what the summary keeps.
- Keep exact or structured information as harness state outside the context, and load details just in time.
- Write handoffs to sub-agents or later sessions that carry the goal, inputs, limits and gaps.
- Add, merge, replace and delete memories, and choose how to resolve contradictions.
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AI Engineering · Chip Huyen, 2025
Chip Huyen. O'Reilly. Used: Ch. 6 "RAG and Agents": "Memory".
Effective context engineering for AI agents · Anthropic, 2025
Anthropic. Used: Context rot, compaction, structured note-taking, sub-agent architectures, just-in-time context (fetched 2026-10-23). Open source