An AI agent can remember a 30-page conversation and still perform the same action twice. It sends a...
AI agent memory alone fails to prevent duplicate actions—receipts solve it: atomic operation state tracking (submitted→succeeded/outcome_unknown) must be recorded before request transmission. Timeout remains ambiguous: server may have already committed, so receipts+reconciliation are mandatory to prevent duplicate emails, publications, and costly production failures.
An AI agent can remember a 30-page conversation and still perform the same action twice.
It sends a request. The connection times out. The agent remembers the goal, the plan, and the tool
call—but not whether the outside system changed. So it tries again.
That is not a vector-memory problem. It is an action-receipt problem.
The missing memory layer
Most AI Agent Memory discussions start from the same assumption: If the agent forgets, give it more...
Most AI agent systems start with a simple idea: "Let's give the Agent Memory". At first, this...
Most AI agents have a memory problem disguised as a prompting problem. We keep adding conversation...
Notes from building a memory layer that forgets on purpose. Most "memory-enabled" agents don't...
Understanding different memory architectures for AI agents and when persistent, episodic, or vector memory actually pays off in…
AI agents can't remember past conversations. They must constantly reload or retrieve context, which grows less efficient as tasks…
