Deterministic simulation testing drives every fault, clock, and random choice from one seed — so a flaky, once-in-production agent bug becomes a reproducible artifact you can shrink to one line.
TL;DR: The worst agent bugs only appear under a specific interleaving of faults — a tool fails right after a side effect, a retry fires, and money moves twice. Happy-path tests miss it, and when it hits production you can't reproduce it. Deterministic simulation testing (DST) — the technique behind FoundationDB, TigerBeetle, and Antithesis — makes faults, timing, and randomness a pure function of one seed, so any failure replays exactly and can be shrunk to its minimal cause. In a runnable Python demo, the happy path passes, seeded fuzzing catches a double-charge, replays it identically, and shrinks a 4-fault schedule down to the single fault that matters.
Mental model: a flight simulator with a record button. Instead of waiting for a storm to hit a real plane, you conjure storms on demand — and when one crashes the plane, you can replay that exact storm frame-by-frame until you understand it, then strip it down to the one gust that did the damage.
The problem: the bugs that matter are the ones you can't reproduce
