Most companies have bought AI coding tools. Far fewer have gotten their engineers to actually use them, and fewer still can prove it moved the needle. This talk is a practical, field-tested playbook for taking generative-AI and LLM tooling from a handful of early adopters to full-team adoption, drawn from scaling GenAI usage from 5% to 100% across an engineering organization in under a single quarter.

We'll cover the real blockers (trust, workflow fit, and 'I tried it once' fatigue), the rollout tactics that actually work versus the ones that stall, how to set guardrails without killing momentum, and, critically, how to measure genuine productivity gains rather than vanity usage numbers. Attendees leave with a concrete adoption roadmap they can run inside their own org, whether they lead a team of five or an organization of hundreds.

Aimed at engineering leaders, platform and developer-experience teams, and anyone accountable for making an AI investment actually pay off.