Your harness, your memory
AI Summary
Chase's April 2026 argument that the agent harness — the code that orchestrates model calls, tools, and state — is inseparable from memory, and closed harnesses are a trap. If Anthropic or OpenAI holds your agent's memory inside their proprietary SDK, you don't own your agent. This is the clearest political statement in the field so far: memory format equals lock-in, and open-source harnesses like LangChain's Deep Agents are a hedge against it. Short, opinionated, landed hard in the AI engineering community.
Original excerpt
Agent harnesses are becoming the dominant way to build agents, and they are not going anywhere. These harnesses are intimately tied to agent memory. If you used a closed harness - especially if it’s behind a proprietary API - you are choosing to yield control of your agent’s memory to a third party. Memory is incredibly important to creating good and sticky agentic experiences. This creates incredible lock in. Memory - and therefor harnesses - should be open, so that you own your own memory
The “best” way to build agentic systems has changed dramatically over the past three years. When ChatGPT came out, all you could do were simple RAG chains (LangChain). Then the models got a little better,…
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