Agents Need a Black Box

Aircraft carry a flight recorder because when something goes wrong at altitude, nobody was watching the instruments. AI agents have the same problem. They run for minutes or hours, make hundreds of calls, and when one goes wrong the usual answer is a shrug and a log file that stopped mattering an hour ago. MYND Agent Replay is my answer: a black box flight recorder for agent execution.

The recorder captures every LLM call, every tool invocation and every state mutation as a frame with a timestamp. The backend is Fastify with BullMQ queues, PostgreSQL with TimescaleDB for the time-series workload, and Redis for caching. The debugger front end is SvelteKit, with a timeline, frame inspection, state diffs and charts for token usage, latency and error rates.

The engine is honest about scale

The replay engine does not write a database row per frame. It buffers frames in memory per trace and flushes when the buffer hits 100 frames or every five seconds, whichever comes first. Reads go through a Redis cache with an hour TTL, and cache entries are invalidated the moment a trace ends. These are small choices, but they are the difference between a recorder you can leave on in production and one you cannot.

State reconstruction is point-in-time: to answer what the agent believed at a given moment, the engine folds every state change up to that timestamp into one object. Time-travel debugging falls out of that primitive for free.

Behavior DNA

When a trace ends, the engine generates what I call a Behavior DNA fingerprint. It extracts features from the frames: counts of LLM calls, tool calls and state changes, the average interval between frames, which tools were used and how often, which models were called, and the entropy of the state transitions. Those features become a fixed-length vector, and the vector becomes a perceptual hash. Two runs of the same agent that behave alike produce similar fingerprints, which is exactly what you want for regression testing an agent across a model swap.

I think recording is about to become non-negotiable infrastructure for agents. You cannot fix what you cannot replay, and you cannot audit what you never captured.