There are already a dozen AI code-review products. We're shipping another one because every existing tool fails at the same thing: trust.
A "review" you can't trust is worse than no review at all. It teaches the team to ignore the bot. Within two sprints, the bot is muted in Slack, the PR comments are scrolled past, and the seat cost shows up in next quarter's cancellations.
So before we wrote a single specialist pass, we wrote down the bar:
Every finding answers what is wrong, where it is, and why it matters, in a sentence a senior engineer would actually write.
That third one is the differentiator. It's also the easiest thing to fake with a model that's good at prose, which is why we ship a deterministic validator and a localized verifier before the classifier ever sees a finding. If the model can't quote the line it's claiming is broken, the finding is dropped. If the cited line isn't within twenty lines of the evidence, the finding is dropped.
The result is a review that's quieter than the competition, fewer findings, more signal. That's the only metric that actually matters.
What's on the blog
This blog is a build log. Expect:
- Engineering posts, how a specific subsystem works, why we picked it, what we'd do differently.
- Product posts, pricing decisions, what we're hearing from teams in early access, where the roadmap is heading.
- Postmortems, when we ship something broken (we will), the writeup goes here.
No content marketing, no thought leadership. Just the work.
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