Operationalizing AI Features

AI becomes valuable only when it behaves consistently under real-world conditions.

This playbook treats AI as a system rather than a feature. Acceptable failure modes must be defined upfront, predictability must be measured alongside accuracy, and UX must set the right expectations.

In production environments, the most important AI questions are often not about performance, but about control: when the system should not act, how it fails, and how users recover.

Trust in AI is built through clarity, not confidence.