Most “AI agents in production” talks skip the part where you have to turn distributed operational knowledge into something an agent can execute safely. This is that part: a practitioner report from a global logistics case-processing project at Maersk, focused on SOPs-as-code, evaluation UX, guardrails, replay-based testing, and SME refinement loops.

The talk covers why versioned, country-aware SOPs beat prompt engineering at scale; how SME corrections become safe workflow changes; why classifier routing and SOP execution must stay separate; where agents under-deliver against demos; and why most of the engineering effort goes into evaluation, replay, and guardrails rather than model prompting.