Engineering visibility
AI agents now open pull requests, review code, and ship features alongside your engineers. Releezy Guardian puts every contributor — human or agent — on one scoreboard, so the picture you act on is one you can trust.
the visibility gap
Picture your last leadership meeting. Pull requests are up, commits are up, the AI line in the budget is up — and when someone asks how the team is actually shipping since AI joined, the room goes quiet. Eighty-four percent of developers now use or plan to use AI coding tools, yet 46% do not trust the accuracy of what those tools produce (Stack Overflow 2025 Developer Survey, more than 49,000 respondents). The activity is visible everywhere. The truth is visible nowhere.
Perception makes it worse. In a controlled study by METR with 16 experienced open-source developers, participants were 19% slower when using AI assistance while believing they were 20% faster. When the people doing the work misread their own speed by nearly 40 points, dashboards built on activity counts inherit the same distortion.
And the work itself is changing shape faster than the instruments watching it. LinearB analyzed 8.1 million pull requests across 4,800 engineering teams and found AI-generated PRs accepted 32.7% of the time, against 84.4% for human-written ones. Faros AI telemetry across 22,000 developers registered a 31.3% rise in merges with no review at all. First the code changed. Then the review changed. Your visibility needs to catch up to both.
how releezy helps
Releezy Guardian reads your git history and turns it into a single view of how the whole team ships — humans and agents on the same ruler.
Releezy Guardian
Guardian connects to your git repository and measures every contributor by the same standard — your engineers, Copilot, CodeRabbit, and every agent you run. No separate dashboard for the AI half of your team. One scoreboard, one truth.
Releezy Guardian
For each contributor and reviewer, Guardian shows whether their work actually improves the code: which review comments lead to real changes and which get ignored. Your best human reviewers set the baseline — around 90% in the teams we observe — and everyone else is measured against it.
Releezy Loop + Releezy Reviewer
When you run coding agents through Releezy Loop, or reviews through Releezy Reviewer, every run lands on the same scoreboard your humans live on. The ruler never bends to flatter our own modules — if an agent falls below your baseline, you see it first.
what changes
01
When the board asks whether AI is helping, you answer with a number from your own git history — not an anecdote, not a vendor slide.
02
You know which reviews change code and which are rubber stamps, for every reviewer — human or agent — before quality slips into production.
03
Effectiveness per contributor shows exactly where coaching, better context, or a different tool will pay off. Growth over punishment, guided by data.
faq
No. Guardian exists for growth, not punishment. There are no ranking leaderboards and no 'worst developer' scores. The scoreboard shows effectiveness so each contributor — and the team as a whole — can see where to improve, the same way strong teams already use retrospectives.
Yes — that is exactly what makes the number meaningful. Your best human reviewers set the baseline, and every other contributor is measured against it. Separate dashboards for humans and AI would let each side hide behind its own metric. One ruler keeps everyone honest, including us.
Nothing. Guardian works from your existing git repository — no changes to your CI pipeline, no plugins for developers to install, no new rituals. Your team keeps working exactly as it does today; the scoreboard fills in from the history you already have.
Most dashboards count activity: PRs opened, commits merged, cycle time. Guardian measures effectiveness: whether each contributor and reviewer actually improves the code, with humans and AI agents on the same ruler. Activity tells you the team is busy. Effectiveness tells you whether to trust what ships.
A 30-minute demo on your own repositories. You leave seeing how your team really ships — humans and agents, one ruler, no guesswork.