In this episode of Engineering Enablement, host Laura Tacho talks with Bruno Passos, Product Lead for Developer Experience at Booking.com, about how the company is rolling out AI tools across a 3,000-person engineering team.Bruno shares how Booking.com set ambitious innovation goals, why cultural change mattered as much as technology, and the education practices that turned hesitant developers into daily users. He also reflects on the early barriers, from low adoption and knowledge gaps to procurement hurdles, and explains the interventions that worked, including learning paths, hackathon-style workshops, Slack communities, and centralized procurement. The result is that Booking.com now sits in the top 25 percent of companies for AI adoption.Where to find Bruno Passos:• LinkedIn: <a href="https://www.linkedin.com/in/brpassos/">https://www.linkedin.com/in/brpassos/</a>• X: <a href="https://x.com/brunopassos">https://x.com/brunopassos</a>Where to find Laura Tacho:• LinkedIn: <a href="https://www.linkedin.com/in/lauratacho/">https://www.linkedin.com/in/lauratacho/</a>• X: <a href="https://x.com/rhein_wein">https://x.com/rhein_wein</a>• Website: <a href="https://lauratacho.com/">https://lauratacho.com/</a>• Laura’s course (Measuring Engineering Performance and AI Impact) <a href="https://lauratacho.com/developer-productivity-metrics-course">https://lauratacho.com/developer-productivity-metrics-course</a>In this episode, we cover:(00:00) Intro(01:09) Bruno’s role at <a href="http://booking.com">Booking.com</a> and an overview of the business (02:19) <a href="http://booking.com">Booking.com</a>’s goals when introducing AI tooling(03:26) Why <a href="http://booking.com">Booking.com</a> made such an ambitious innovation ratio goal (06:46) The beginning of <a href="http://booking.com">Booking.com</a>’s journey with AI(08:54) Why the initial adoption of Cody was low(13:17) How education and enablement fueled adoption(15:48) The importance of a top-down cultural change for AI adoption(17:38) The ongoing journey of determining the right metrics(21:44) Measuring the longer-term impact of AI (27:04) How Booking.com solved internal bottlenecks to testing new tools(32:10) Booking.com’s framework for evaluating new tools(35:50) The state of adoption at Booking.com and efforts to expand AI use(37:07) What’s still undetermined about AI’s impact on PR/MR quality(39:48) How Booking.com is addressing lagging adoption and monitoring churn(43:24) How Booking.com’s Slack community lowers friction for questions and support(44:35) Closing thoughts on what’s next for Booking.com’s AI planReferenced:<ul><li><a href="https://getdx.com/research/measuring-ai-code-assistants-and-agents/?utm_source=podcast">Measuring AI code assistants and agents</a></li><li><a href="https://getdx.com/core-4-reporting/">DX Core 4 Framework</a></li><li><a href="https://www.booking.com/">Booking.com</a></li><li><a href="https://sourcegraph.com/search">Sourcegraph Search</a></li><li><a href="https://sourcegraph.com/cody">Cody | AI coding assistant from Sourcegraph</a></li><li><a href="https://www.linkedin.com/in/greysonjunggren/">Greyson Junggren - DX | LinkedIn</a></li></ul>

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