Side quests at GitHub Universe: who owns AI proof now?
What we heard at GitHub Universe 2026: DevEx teams and AI adoption leads now own the question of whether AI is paying off across engineering orgs.
Engineering leadership
Team productivity, ROI of engineering, scaling culture, mentoring, and making data-driven decisions. How to lead with clarity instead of guesswork.
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Is it worth it to DIY engineering intelligence in the age of AI?
A DIY engineering intelligence dashboard takes a day or two to build. Trusting it with a board-level answer takes much more. Here’s where DIY breaks down.
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LDX3 New York: every AI conversation came back to proof
What engineering leaders at LDX3 New York asked about AI impact, DORA metrics, review debt, and software factories.
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The AI bet is real; can you prove it’s paying off?
Most engineering leaders can’t prove their AI investment is paying off. See the five blind spots standing in the way, and how to close them.
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Your org chart can’t show how your engineering team actually works
An org chart is great at describing reporting lines, but how is the work actually getting done or who’s making it possible to move forward?
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How to implement DORA metrics: a practical guide for engineering leaders
A 90-day DORA metrics implementation plan, with benchmarks, common pitfalls, and how AI changes what these metrics mean.
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AI solved the code creation problem; now we have a visibility problem
AI solved the code creation problem. Visibility is where engineering leaders win or lose next.
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The signals senior engineers read that juniors don’t (yet)
Ramping in a new codebase is about reading the right signals—where work is happening, what kind it is, and where things keep breaking.
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Engineering intelligence that delivers a pulse for every leadership role
Engineering intelligence for leadership roles: Get a pulse on your teams and scale visibility from Team Leads to VPs.
