Collaborator turns code review into the training loop. The comments you already write become durable lessons your agents inherit — so you stop re-explaining the same conventions every session.
You correct the same mistake you corrected last week. The model has no memory that you ever did.
Your conventions — error handling, naming, which library you standardized on — get re-typed into the prompt for the hundredth time.
Architectural decisions the team argued through months ago get quietly reopened, because nothing carried them forward.
The review comment you wrote last Tuesday is gone. Your team keeps paying interest on knowledge it already earned.
A human and an AI agent work the same pull request, side by side. They talk it through the way teammates do — inline comments and chat, right on the diff — and every word is kept, forever. Every action carries its effort and its cost, attributed all the way up.
A human and an AI agent work the same pull request, side by side — symmetric workers on one branch. There's no separate lane for "the AI's code"; it's reviewed like anyone's.
They communicate the way people already do — inline comments on the exact lines, and chat right on the diff. The whole conversation lives with the code it's about.
Comment, reply, chat, commit, approval — each is stored permanently in an immutable record. You can replay exactly what was said and decided, for an audit or for onboarding the next engineer.
From that conversation, durable org-scoped lessons are distilled and carried into every future task — each traceable back to the exchange that produced it. Your team's decisions stop evaporating. They compound.
Every AI action is metered individually and attributed up the chain — from the comment that triggered it, to the task, the pull request, and the milestone. Effort accumulates into a real record, so predicted velocity gets sharper every sprint and you can watch cost per unit of shipped work move over time.
Every action writes to an immutable ledger. That's what lets Collaborator trust its own history — and lets you stop watching the boring parts.
Distilled from real review comments, ranked by votes, scoped to your org. Every closed task can leave the next one a little smarter.
People and AI agents are the same kind of worker: they open branches, push diffs, and get reviewed identically. No separate lane for "the AI code."
An inline review comment can hand the fix straight to an agent. The thread stays where the context is — on the exact lines you were reading.
Every diff block is content-hashed. If an approved block changes later, it automatically resurfaces for re-approval — nothing slips through silently.
Coverage and tests run at merge time, not as advisory noise. A failing gate can hard-block a bad merge outright — the rule is the wall.
Untrusted code — including anything an agent generates — runs in sealed, single-use containers. Nothing it does reaches back into your infrastructure.
Test and coverage instrumentation spans thirteen language ecosystems, so the gates mean the same thing in your polyglot monorepo as in a single service.
Every action — comment, approval, merge, agent run — is an append-only event. You can replay exactly who or what changed a line, and why.
Isolation is enforced in the database with per-org Postgres row-level security — not just in application code you have to trust to get it right every time.
Because every comment, chat, approval and agent action is tracked, Collaborator knows which parts of your repo have had real human attention — and which quietly shipped without it. Those get flagged for audit.
This settles serially with no transaction boundary. If it dies halfway we've partially reconciled and there's no record of where it stopped.
src/billing/reconcile.ts:143Agreed — wrapped the loop in a single transaction and made each settle idempotent on the ledger row id, so a retry can't double-apply.
src/billing/reconcile.ts:143Batch financial writes are transactional and idempotent per row — never a bare loop. Filed as a core principle for the payments surface.
audit · payments-service · closedAgent-heavy code with a thin review trail surfaces on its own — no one has to remember to go looking for it.
An audit is scheduled work, not a drive-by: engineers read the flagged code as a group and decide what it should actually be.
Fix it yourselves or hand the work to an agent — either way it lands as a reviewed PR on the same record as everything else.
Every audit closes by producing core principles and lessons for the agents — and, just as much, real understanding for the people who sat in it.
This is how a codebase avoids becoming a black box no one understands — a pile of plausible code that works until it doesn't. Someone on your team has read every important line, and the agents carry what they concluded.
More shipped, less re-explaining. Not because anyone typed faster — because the review you were already doing stopped evaporating.
Engineers spend their attention on the decisions that matter. The boring code writes itself.
Bring Collaborator to your repo and let review start compounding. Early access is rolling out to engineering teams now.