Engineering Enablement by DX
Driving enterprise-wide AI tool adoption
· Summarized
Key takeaways
- Cultural change is as important as technological change for successful AI adoption.
- Targeted education and support increase developer confidence and engagement with AI tools.
- Centralizing procurement processes can alleviate blockers for tool experimentation.
- Measuring impact requires both qualitative and quantitative metrics.
- Enhanced communication and collaboration can foster a supportive community for AI usage.
- Future goals involve ensuring widespread everyday use of AI tools among developers.
Summary
Introduction to AI Culture at Booking.com
In the podcast, Laura Tacho hosts Bruno Passos, Product Lead for Developer Experience at Booking.com, who discusses the importance of embracing AI as a cultural accelerator for change within the organization. He outlines how just making AI tools available is not enough; there needed to be a shift in mindset and culture for AI to be accepted and utilized effectively by developers.
The Role of Education in Adoption
The initial adoption of AI tools like Cody was noticeably low. Bruno explains that education and targeted enablement were crucial in turning hesitant developers into regular users. Training programs, learning paths, and dedicated workshops helped demystify AI and its applications, fostering a supportive community.
Addressing Barriers to AI Adoption
Bruno discusses the barriers faced during the initial rollout of AI tools, including knowledge gaps and procurement hurdles. Key interventions included creating centralized procurement processes, running hackathon-style workshops for hands-on experimentation, and establishing Slack communities for ongoing support and education.
Measuring Impact and Success
An in-depth discussion on measuring the impact of AI adoption reveals how Booking.com utilized various metrics to evaluate the effectiveness of Gen AI in code development. Bruno emphasizes the ongoing need to refine these measures to ensure they align with their core business goals and foster an innovative environment.
Community and Collaboration as Catalysts
The cultural shift encouraged collaboration across business units, leading to shared learning experiences and problem-solving sessions. By working together, teams could tackle real business issues using AI, ultimately leading to faster tool adoption across the organization.
Future of AI at Booking.com
Looking ahead, the aim is to ensure that every developer uses Gen AI regularly. This involves continuing to address gaps in knowledge and adoption, refining tools, and emphasizing the importance of AI in improving developer experience and overall productivity.
Sponsors
- GetDX · I'm excited to share the AI Measurement Framework, which offers research-based metrics for tracking AI adoption, measuring real impact, and making smarter investment decisions. To learn more about the AI measurement framework and how to use it, head over to getdx.com slash AI hyphen framework.
- Sourcegraph · Sourcegraph Search is pivotal for navigating legacy code and enabled experimentation with Gen AI.
- Cody · Cody – AI coding assistant from Sourcegraph helped Booking.com leverage AI to enhance developer productivity.
Show notes
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: https://www.linkedin.com/in/brpassos/
• X: https://x.com/brunopassos
Where to find Laura Tacho:
• LinkedIn: https://www.linkedin.com/in/lauratacho/
• Website: https://lauratacho.com/
• Laura’s course (Measuring Engineering Performance and AI Impact) https://lauratacho.com/developer-productivity-metrics-course
In this episode, we cover:
(00:00) Intro
(01:09) Bruno’s role at Booking.com and an overview of the business
(02:19) Booking.com’s goals when introducing AI tooling
(03:26) Why Booking.com made such an ambitious innovation ratio goal
(06:46) The beginning of Booking.com’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 plan
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