Can “Predictable Delivery” be measured?
Five statistical techniques for turning delivery history into forecasting confidence.
Engineering Enablement
Research and perspectives on developer productivity.
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Is there a relationship between cycle time and PR throughput?
There’s a closer relationship between the two in high-throughput organizations. In low-throughput organizations, there are other variables at play.
AI in engineering: Q2 2026 benchmarks & research readout
Brian Houck and Justin Reock unpack DX’s latest AI Impact Report, exploring where AI is improving engineering velocity and where those gains are failing to translate into better outcomes.
“Your benchmarks don't apply to us"
Why benchmark trends matter more than you think.
DX Annual 2027: San Francisco and London
Next year DX Annual is returning to San Francisco and heading to London for the first time. Here's what to expect and how to register your interest.
How Microsoft sees engineering bottlenecks changing with AI
Tim Bozarth, Microsoft CoreAI CVP, explains how AI is changing engineering productivity, why outcomes matter more than output, and what engineering leaders should measure instead.
What are code reviews even for?
AI didn't break code review. It just made the parts we'd been ignoring impossible to ignore.
The unexpected things developer metrics can measure
We built metrics to evaluate developer tools. They turned out to explain everything from office design to Daylight Saving Time.
Measuring the impact of AI coding tools: Capacity, not horsepower
Separate what to measure from how, then measure across dimensions.
Research briefing with Brian Houck: Measuring AI agents and revisiting the Core 4
Justin Reock and Brian Houck explore how AI coding agents are reshaping engineering metrics and what leaders need to measure in the age of AI.
The State of AI Impact in Engineering: Q2 2026
Data from 500+ teams reveals that AI is delivering measurable velocity gains, but velocity alone isn't the story.