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Developer Experience at Capital One with Catherine McGarvey

41 min episode · 2 min read
·
Catherine Mcgarvey

Episode

41 min

Read time

2 min

Topics

Productivity, Investing, Fundraising & VC

AI-Generated Summary

Key Takeaways

  • Make compliance easy: Capital One defaults developers to pre-approved, secure tools and databases rather than requiring manual security reviews for each choice. Teams can request exceptions when needed, but the default path is both fastest and most secure, reducing friction while maintaining controls.
  • Measure outcomes, not output: Track time between deployments and user satisfaction scores rather than lines of code or PR counts. Focus on whether tools actually solve developer problems and enable continuous deployment. Metrics like time-to-first-commit for onboarding reveal if teams have what they need to contribute quickly.
  • AI coding assistants provide asymmetric value: Junior developers gain the most lift from AI tools for understanding codebases, learning new languages, and getting unbiased answers. Senior developers see more value in automated migrations, test generation, and eliminating low-value tasks like dependency updates rather than core development work.
  • Standardize selectively for leverage: Only standardize tools when multiple teams adopt similar solutions or when open standards exist. In rapidly evolving areas like LLMs, use abstraction layers and consistent evaluation criteria across pilots rather than locking into one vendor, enabling teams to switch models as technology improves.

What It Covers

Catherine McGarvey, SVP of Developer Experience at Capital One, explains how the company enables 14,000 technologists to move faster while maintaining security and compliance through standardization, AI-powered coding assistants, and continuous deployment practices.

Key Questions Answered

  • Make compliance easy: Capital One defaults developers to pre-approved, secure tools and databases rather than requiring manual security reviews for each choice. Teams can request exceptions when needed, but the default path is both fastest and most secure, reducing friction while maintaining controls.
  • Measure outcomes, not output: Track time between deployments and user satisfaction scores rather than lines of code or PR counts. Focus on whether tools actually solve developer problems and enable continuous deployment. Metrics like time-to-first-commit for onboarding reveal if teams have what they need to contribute quickly.
  • AI coding assistants provide asymmetric value: Junior developers gain the most lift from AI tools for understanding codebases, learning new languages, and getting unbiased answers. Senior developers see more value in automated migrations, test generation, and eliminating low-value tasks like dependency updates rather than core development work.
  • Standardize selectively for leverage: Only standardize tools when multiple teams adopt similar solutions or when open standards exist. In rapidly evolving areas like LLMs, use abstraction layers and consistent evaluation criteria across pilots rather than locking into one vendor, enabling teams to switch models as technology improves.

Notable Moment

McGarvey compares resisting AI tools to taking an open-book test but choosing not to use the book. She argues engineers who fear these changes likely enjoy tasks that automation now handles, and should find roles aligned with their preferences rather than missing productivity gains.

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Episode Transcript

Modern software development is evolving rapidly. New tools, processes, and AI powered systems are reshaping how teams collaborate and how engineers find satisfaction in their craft. At the same time, developer experience has become a critical function for helping organizations balance agility, security, and scale while maintaining the creativity and flow that make top tier engineering possible. Capital One is continuously transforming its developer culture with a focus on faster development cycles, reducing operational overhead, and boosting productivity across the organization. Catherine McGarvey is the SVP of developer experience at Capital One. She joins the podcast with Sean Falconer to talk about what developer enablement means at enterprise scale, measuring developer productivity, being agile in a regulated environment, AI and enterprise development, the future for developers, and much more. This episode is hosted by Sean Falconer. Check the show notes for more information on Sean's work and where to find him. Catherine, welcome to the show. Thanks, Sean. Great to be here. Yeah. Absolutely. It's good to have you on the show. So, you know, I was looking into your background. You have a pretty fascinating background where you've you spent some time in startups. You've done some defense consulting. Now you're leading a developer experience for, like, 14,000 technologists at Capital One. Like, how does that diverse experience across this wide spectrum of from fast moving startup world to a large financial institution shape the way that you think about tackling things like developer enablement at such a massive scale? Yeah. I've been super, super fortunate in my career to have these kind of pivots or these opportunities to approach different domains and different sizes. And I think what's really nice about that is you learn a couple of things that often there's not one way to do something and that you've really got to think about what matters in how you're doing software development to the consumer and to the business to really spark down the path of, well, what do you have to standardize on and what can you leave flexibility around? And that's been really great. You know, with the consulting side of startups, I got to be involved in the early days from zero to one and one to a 100 users. And it was amazing to think through long term architectural design matters a lot less when you're just trying to confirm that you can survive and you can get those first couple of customers and how much that pivots when you're talking about b to b selling or b to c, where I am sort of now really thinking through how do we make sure what we deliver is resilient to customers and is set up. But at the same point, how do you keep it agile so that you are adapting to their feedback back and able to make changes? So it's been nice to draw on different parts of my career to date to really look to how do you bring …

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