Record a Successful Agent Run Once, Then Replay the Tool Trace With Zero Inference

Turns K per-step LLM calls into one recording plus K-1 zero-inference replays on deterministic repeated jobs; reported ~93% fewer tokens on daily tasks and near-total on high-frequency ones, but zero benefit on one-off or branchy work Advanced 2 min read

A scheduled agent re-plans the same fixed workflow every run, paying the model to re-decide a tool sequence it already decided. Record the trace of one successful run, template the params that vary, and replay the steps deterministically without calling the LLM.

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