Insights on Developer Experience, DX² methodology, and measuring what matters
DORA metrics revolutionized how we measure software delivery. But after a decade of research, we're learning they're just the tip of the iceberg. Here's what they measure, what they miss, and why modern engineering teams need more.
AI coding tools cut development time in half. But if reviews stack up, delivery doesn't get faster. Here's how to identify and fix the bottlenecks that neutralize your AI productivity gains.
How to actually measure developer productivity using SPACE. Real implementation examples, common pitfalls, and lessons from teams who've done it.
Hard metrics tell you what happened. Qualitative data tells you why. You need both—here's why most teams get this wrong.
65% of engineers experienced burnout last year. Your DORA metrics look great. These two facts aren't contradictory—they reveal a dangerous blind spot in how we measure engineering performance.
Other platforms track whether developers use AI tools. We track whether AI actually makes them more productive. Here's the difference—and why it matters.
Most engineering KPI lists focus only on output. Here's a curated set that includes discovery, developer experience, and team health—because shipping fast means nothing if you're shipping the wrong things.
Traditional DX platforms measure how fast you ship. But they completely miss whether you're shipping the right things. Here's what they're missing—and why it matters.
Most DX platforms only measure delivery. Here's why that's a problem—and how measuring both Discovery and Delivery gives you the complete picture.