Perception vs. reality
19% slower
Experienced developers using AI tools took 19% longer on real tasks from their own repositories — while estimating they had been about 20% faster.
METR randomized controlled trial, 2025 — 16 developers, 246 tasks
Measure AI impact
Is AI actually helping your team?
Six months of AI tools, and the honest answer is still a shrug. Releezy Guardian measures every contributor — your humans and every AI agent — on one ruler, computed from your own git history. Trust built with data, not with adoption charts.
the measurement gap
Everyone feels faster. The evidence disagrees.
Picture the last leadership meeting where someone asked whether the AI budget is paying off. Adoption went up. Enthusiasm went up. And the question still had no answer, because a feeling is not a measurement.
In a randomized controlled trial by METR (2025), 16 experienced open-source developers worked on 246 real tasks from their own repositories. With AI assistance, they took 19% longer — while estimating they had been about 20% faster. The distance between perceived impact and measured impact is not a rounding error. It is the whole question.
Developers feel it too. In the 2025 Stack Overflow Developer Survey, with more than 49,000 respondents, 46% said they actively distrust the accuracy of AI tools — more than the 33% who trust it. When the people closest to the code do not trust the output, leadership needs an instrument, not another opinion.
Developer trust
46% vs 33%
More developers actively distrust the accuracy of AI tools than trust it. The people closest to the code are asking the same question you are.
Stack Overflow Developer Survey, 2025 — 49,000+ respondents
how releezy helps
One honest ruler for humans and AI agents.
You do not need another activity dashboard. You need a fixed reference point — and every contributor, human or agent, measured against it.
01
Your team sets the baseline
Releezy Guardian reads your git repository history and computes how often your best human reviewers' comments lead to real code changes — around 90% on the teams we have observed. That number becomes your ruler. It comes from your people, not from a vendor benchmark.
02
Every agent on the same scoreboard
Copilot, Cursor, CodeRabbit, the agents your team runs through Releezy Loop — every contributor lands next to your humans, measured the same way. No vendor dashboard grading its own homework. One scoreboard, one standard.
03
A standard that never bends
Releezy Reviewer is judged by the same Guardian metric as every human on your team. If our own agent scores below your baseline, you see the number. The ruler does not soften for any tool — including ours.
outcomes
What changes when you can measure.
Renewal conversations backed by evidence
When the AI tool budget comes up, you answer with your own data: which tools improve the code, which ones create review work, and where the gap is closing.
A team that trusts the transition
Engineers stop debating anecdotes. The scoreboard shows humans and agents on the same scale, so the conversation moves from "I feel" to "here is the number".
Improvement you can watch, week over week
The measurement is longitudinal. You see each tool's effectiveness move as your team calibrates it — and you know exactly where to invest next.
Questions engineering leaders ask us
How is this different from the dashboards my AI tools already give me?
Vendor dashboards measure activity: suggestions accepted, lines generated, minutes saved. Releezy Guardian measures outcomes in your git history — whether contributions and review comments actually improve the code — with the same metric applied to every tool and every human. No vendor grades its own homework here.
Do you need access to our code?
Releezy Guardian reads your git repository's pull request history, review comments, and code changes. Read-only. Your code never leaves your repository.
How long until we see a meaningful measurement?
Your baseline is computed from history you already have. Guardian reads your existing pull requests, so you see your ruler on day one — and it sharpens with every week of new data.
What if the numbers show our AI tools are not helping?
Then you have learned something most teams never get to see — and you can act on it. Guardian shows you where the gap is so you can calibrate, retire, or replace tools with confidence. The goal is growth, not punishment: the same data tells you exactly where each tool improves.
See what AI is really doing for your team.
A 30-minute demo on your repository. Your humans and your AI agents, on one ruler, from day one.