"Elite teams are shipping 12x more code with AI and getting it into production 5x faster. But they’re not just coding more. They’ve changed how they build."
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The annual DORA report used to be a quiet pulse check. Deployment frequency. Lead time. Change failure rate. Reliable metrics for engineering maturity.
Now, it reads more like a post-AI field manual.
In the 2025 edition, the signal is loud and clear: high-performing engineering teams have gone all in on AI. But the surprise isn’t how fast they’re moving, it’s how they’re moving.
Because the top teams aren’t just plugging in Copilot and calling it a day. They’re reorganizing around it. Process, pipelines, roles, review cycles, everything is being rethreaded through an AI-first lens.
And the productivity gap is exploding.
According to the report, elite teams are deploying 973 times more frequently than low performers. Code is moving to prod 5x faster. Incidents are down. Confidence is up. And in many cases, it’s the AI that’s steering that changes.
But here's the part most teams miss: AI doesn’t create performance, it amplifies structure.
The same report shows that the biggest delta isn’t just tooling, it’s culture. Elite teams trust each other more. They design better onboarding. They lean into trunk-based development. And they use AI to reinforce those strengths, not bypass them.
Contrast that with the bottom quartile. Same tools. Worse outcomes. These teams use AI like a faster intern: generate code, copy-paste, move on. But without strong feedback loops and tight CI/CD pipelines, they’re just shipping messes at speed.
Of course, AI isn’t doing this alone. The top-performing teams in the DORA report didn’t just scale with tools, they scaled with talent that knows how to use them. Many are blending senior engineers with AI-native workflows, often working across time zones but not across time lags. In fact, some of the smartest orgs are quietly staffing their velocity gains with AI-fluent engineers, people who can move fast, speak fluent English, and ship in real time. Turns out, the combination of aligned time zones and AI literacy is becoming a serious multiplier. Meet the engineers helping top teams turn AI into output.
It’s the old law of automation. If your process is broken, AI just helps you break things faster.
The DORA report also delivers another warning shot. Burnout is spiking in orgs where AI is rolled out without clear expectations or support. Developers feel pressure to perform like the machine. Senior engineers report fatigue from reviewing AI-generated pull requests. And some leaders, chasing metrics, are quietly replacing code quality with code volume.
None of that ends well.
If you’re leading an engineering org today, DORA 2025 offers both a blueprint and a caution sign.
Yes, the best teams are using AI in code review, test generation, release management, and more. Yes, they’re seeing speed gains that would’ve seemed absurd just two years ago. But they’re not outsourcing responsibility. They’re redesigning it.
The new elite team doesn’t just deploy faster. They deploy smarter. They use AI to enhance team rituals, not erode them. They automate the boring parts, but scrutinize the results. And they’ve built the organizational muscle to separate AI-generated code that works from code that lasts.
Speed, quality, stability. Pick three. That’s the new bar. And it’s only rising.
More to come…
– Gino Ferrand, Founder @ Tecla