Nicole Forsgren
Nicole Forsgren created the most widely used frameworks for measuring developer productivity—DORA and SPACE. She wrote the foundational book Accelerate and is about to release her newest book, Frictionless , a practical guide for helping teams move faster in the AI era.
Episode
How to measure AI developer productivity in 2025 | Nicole Forsgren
Summary
Nicole Forsgren, creator of the DORA and SPACE frameworks, discusses how to measure developer productivity in the AI era — arguing the biggest challenge is not choosing metrics but failing to define what problem you're solving. She covers how AI changes inner-loop versus outer-loop work, why eliminating all friction is wrong, and how measurement programs fail when they become surveillance rather than improvement tools.
Key Takeaways
Before picking any metrics, get radically clear on the problem you're solving — 80% of teams haven't done this and are heading in completely different directions.
Measure outcomes at multiple levels simultaneously: individual satisfaction (SPACE), team delivery (DORA), and business value. Single-metric programs create perverse incentives.
AI accelerates the inner loop (coding, testing, debugging) before the outer loop (deployment, monitoring). DORA metrics may not move even when AI creates real gains — measure inner-loop friction separately.
DevOps is not a toolchain you buy — it's a set of capabilities that predict speed and stability. Marketing teams labeled products "DevOps"; buying them isn't a strategy.
Some friction is intentional: code review and design review encode quality and knowledge transfer. Eliminate waste friction while preserving load-bearing friction.
Notable Quotes
“Number of pull requests, number of commits. And I was like, "These are all activity metrics." And so finally I pulled a few of my friends together and I was like, "Let's come up with a framework to help people think about it." And so there are five broad categories, pick three because that will help force you through the mental exercise of, "What could I possibly pick?" You don't need all five, right. This isn't... We're not playing-”
“Okay, so SPACE is a way to measure, we say productivity, developer productivity, but it's a little bit more than that. SPACE is a good way to measure any type of complex creative work. Now, how do they relate? Let's say you go through the quick check. It points out four things, and you decide you want to improve continuous integration and culture, right. Well, now you're like, "Cool, but how am I going to actually measure them?" This is where SPACE comes in because SPACE helps you figure out SPACE gives you a framework to pick the right metrics.”
“You can get a relatively quickly. But as you kind of transition through this measurement journey, you'll get more and more data from your systems because it's scalable. It can be engineered. You can be doing much more with it. And also, you should be thinking about, "Don't let the perfect be the enemy of the good." So how do we think about this very, very strategically? How do we transition through this? How do we think about what each piece of data is for?”