The biggest unresolved problem in multi-agent workflows is not reasoning. It is execution safety.
Most teams building with LLMs today have not encountered this problem yet — because they have not scaled yet. This article is for the ones who are about to.
The Core Tension
LLMs are probabilistic by nature. Every output is a sample from a probability distribution. There is no guarantee that the same prompt produces the same output twice. That is not a bug — it is the fundamental property that makes language models useful.
Production backend systems are deterministic by requirement. The same input must always produce the same state change, traceably, verifiably, with an audit log that can be reconstructed after the fact.
