"How will you prove the team made developers faster?" It sounds like a measurement question. Start one step earlier.
A team with real delivery pressure, and more work than it can finish, does not need to be convinced to use a tool that helps. It will grab the tool. And it will quietly drop a tool that does not help, whatever the launch announcement said.
So adoption under real pressure is itself evidence. If they keep coming back after the novelty wears off, something is working. And if nobody comes — that is also an answer, and a cheaper one than a survey.
This only works if "better" was defined together in advance. Write the acceptance tests with the teams who will use the thing; then the acceleration team is not grading its own homework, and the verdict does not rest on one side's numbers. (I keep a separate note on this: acceptance test-driven development, and why every eval result has to be auditable.)
But adoption has a catch. It only happens if people can actually get started — and users are surprisingly clumsy with a new tool. That is fair. Why should they be smart on my product?
So the unglamorous work matters as much as the machinery: step-by-step guided tours inside the product, and videos that show the thing being used. I even had to learn video pacing, so attention does not tire halfway through.
The version I like best is automated. An agent reads the Git history, strings the commits together into a feature, runs it end to end with screenshots and clips, and generates the feature video. The teams watch it, spot what is wrong, and feed the improvements back. The changelog stops being prose nobody reads and becomes something people can react to.
Choosing where to start follows the same evidence rule. Pick the team that is most willing to cooperate. First impressions decide a rollout: if the platform team comes across as "we know how to do your job better than you", the resistance becomes permanent. So look for a team with a real problem and a promising path to solving it — and a success that becomes a good story, because the story is what brings the next teams in.
And underneath all of it, one piece of discipline. Pick a single number the teams already produce — the time from starting a change to that change reaching production. Measure it before the rollout. Measure it after. No baseline, no proof.
Faster is not a feeling, and it is not a launch-week graph. It is people under pressure choosing the tool, week after week, and one honest number moving.