Every vendor promises their tool will make your team faster. Almost none can prove it — and neither can most teams that adopt them. This talk shows how to replace "it feels faster" with evidence, using DORA metrics (deployment frequency, lead time for changes, change-failure rate, and mean time to recovery) as an objective baseline for evaluating developer tools and AI assistants.

Drawing on establishing DORA baselines across an engineering organization to quantify the impact of new tooling and drive investment decisions, we'll cover how to instrument the four key metrics without a six-month project, how to run a before/after comparison that survives scrutiny, the traps that produce misleading numbers, and how to turn results into a clear decision: double down or cut the tool.

Attendees leave able to build a measurement framework that tells them, with data, which of their tools are actually worth the money. Vendor-neutral and practical, for engineering leaders, DevOps and platform engineers, and anyone accountable for tooling and AI ROI.