AI measurement
Why DORA Metrics Can't Tell You If AI Is Working
Your DORA dashboard went green after rolling out Copilot, and your engineers say they feel slower. Here's why both can be true.
Published research
AI measurement
Measuring what AI assistants changed, and what can't be measured yet.
AI measurement
Technical Debt After AI Adoption: What the Data Actually Shows
Two large 2026 datasets on AI-assisted code and maintenance burden — what they found, what they don't prove, and how to read them before quoting them.
Published research
AI measurement
AI Code Attribution: The Approaches and Where Each One Breaks
Four ways to work out how much of your codebase came from AI assistants — IDE telemetry, heuristics, commit provenance and surveys — and the failure mode of each.
Published research
AI measurement
What to Tell the Board About AI ROI
You've been asked for a return figure on AI coding tools. Here's a defensible answer, why the confident version is worse than the honest one, and what to bring instead.
Published research
AI measurement
The Metrics That Stopped Working When AI Started Writing Code
Six measures that were reasonable proxies until assistants changed what they proxy for — and what still holds up.
Published research
AI measurement
Tools That Claim to Measure AI Impact: What Each Can Actually See
A new product category formed around one question boards are asking. Here's what the different architectures can and cannot establish.
Documentation & public sources
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