Can we make AI reasoning systems reliable enough for safety-critical decisions?

LLMs increasingly attempt formal reasoning tasks, but they hallucinate symbol transitions, apply theorems incorrectly, and offer no reliability guarantees. ReasonOps adapts DevOps principles to reasoning: treating it as a continuous, monitored process that combines autoformalization, symbolic checking, theorem proving, and adaptive correction in a unified lifecycle. The authors demonstrate the approach on an autonomous braking system, arguing operational reasoning frameworks are necessary infrastructure for trustworthy AI in safety-critical domains.