Build faster with AI peers you can measure.
Code Mower makes it easy to create a peer programmer and reviewer model with top AI coding systems, then benchmark which builders and reviewers deliver the best quality, cost, and velocity on your actual product.
Reviewer value snapshot
A compact version of the answer CodeMower.com helps teams build.
Useful signal
82%
False positives
9%
Avg latency
71s
| Lane | Lens | Signal | Cost | Next |
|---|---|---|---|---|
| codex-audit | base | Strong | $ | Merge-gating candidate |
| claude-audit | quality | Useful | $$ | Selective trigger |
| experimental | operability | Noisy | $ | Informational |
The full dashboard keeps this operational data out of the landing page: uploads, provenance, reports, repository rollups, events, and productivity modeling live behind the demo and signed-in product.
Create an AI peer-review loop
Coordinate Codex, Claude, Gitar, Gemini/Antigravity, and other reviewers as explicit lanes instead of one-off chat transcripts.
Measure quality on your codebase
Compare useful findings, misses, false positives, cost, and latency against the product code you actually ship.
Move faster without blind trust
Promote lanes only when evidence says they help. Keep experimental reviewers informational until the signal is real.
The loop is simple.
Code Mower keeps the source of truth in your repo. The optional cloud layer turns sanitized audit metadata into a living answer to the question every AI-assisted team eventually asks: what should we trust?
Install
Add Code Mower to a repo and run doctor.
Run
Ask peer reviewers to audit real PRs.
Measure
Upload sanitized metadata, not source.
Decide
See which lanes should be enabled next.
Use more AI without lowering the bar.
Code Mower separates authoring velocity from review confidence. Builders can move quickly, while independent reviewer lanes produce auditable evidence before a PR graduates into your merge policy.
Peer programmers
Route work through multiple AI systems without losing the PR as the shared artifact.
Reviewer lanes
Keep automated audits structured, head-bound, and separate from advisory prose review.
Measured signal
Decide lane policy from observed usefulness, noise, cost, and latency.