Jake Broekhuizen distinguishes stored traces from memory an agentAI agent memory is stored information that an agent can retrieve and use across steps, sessions, or changing contexts. can use on a future run. Semantic memory covers facts and preferences, episodic memoryEpisodic memory in AI stores records of specific past interactions or events so a system can retrieve experience associated with a particular situation. covers examples and experiences, and procedural memory covers instructions and skills. Working context is temporary, while long-term context guides later behavior.
Jake Broekhuizen describes a read-write cycle: load relevant context, capture an agent's trajectory, filter the evidence for useful signal, then update durable contextContext engineering designs the information, instructions, memory, and tool state an AI receives so it can perform a task reliably.. A financial-services assistant that slips from measured guidance into directive language illustrates why observation alone does not correct future behavior.
Jake Broekhuizen maps the loop onto LangSmith observabilityAI agent observability makes an agent's state, actions, tool use, failures, resource use, and outcomes visible enough to understand and operate it., background analysis and a context hub. Most trace data should remain history or evaluation data rather than become memory. He warns that stale runtime caches can hide updates and recommends human review before changing high-impact instructions or policies.
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