PR Author
Implements fixes, resolves CI, and keeps the PR moving.
See the system that cleared a 1,400-PR review backlog
When agents wrote 100% of our code, review became the bottleneck: 1,400 open PRs and a 20 hour time to first comment. This 5-minute demo shows the multi-agent system we built to ship 3× the code, without lowering the bar.
- 3×
- More PRs shipped
- 67%
- Less median review time
- <1.5%
- Weekly revert rate
cosmos / code-review
The bottleneck
Every team that goes all-in on AI hits the same wall.
Agents write code faster than people can review it, so PRs pile up. More reviewers won’t catch you up. We hit this on our own codebase in January.
Peak queue
1,400
Open PRs, piling up faster than humans could clear them.
First human comment
20h
Median wait before an engineer even looked at your PR.
The queue only grows.
Six PRs ahead of yours, each 400 lines an agent wrote. A two-line change waits a full day at the bottom.
The real bottleneck is confidence.
To trust what ships, someone has to reason through every line. Faster tools don't fix that — they just comment sooner.
Rubber-stamping isn't an option.
Waving PRs through ships bugs and piles up tech debt. You need to review faster without lowering your standards.
What we built
A review workflow,
not another comment bot.
A set of agents handles the routine review work, from the first scan through the fix-up. Instead of a cold diff and a pile of comments, your engineers get a short brief on the decisions that need them.
Review lifecycle
PR Author
Implements fixes, resolves CI, and keeps the PR moving.
Risk Analyzer
Classifies risk and routes each change to the right path.
Deep Code Review
Checks the change against the codebase, not only the diff.
Pair Reviewer
Briefs engineers on decisions that require judgment.
Human
Owns architecture, product intent, and high-risk approval.
Comments posted · merged
Why it catches more
The first review pass is written for agents, not people.
Every other tool tunes its output for a human reader, so it only flags its top findings to avoid burying you in comments. Real bugs slip through in the gap. Here, agents read the first pass, so Cosmos optimizes for recall over precision: it surfaces every issue it finds, then routes only the ones that need a person to your engineers.
Precision
Built for a human reader
- Only flags its top findings
- Stays quiet, so real bugs slip through
- Limited to what a person will read
Recall
Built for an agent reader
- Flags every issue it finds
- Doesn't hold back to stay short
- Handles far more than a person could read
The results · measured on our own codebase
Merge time went from roughly three weeks to under one week.
3×
More code shipped
67%
Lower median merge time
<1.5%
Weekly revert threshold
The result: output tripled while merge time fell
5 month windowTrusted by LeadingEngineering Teams
“We can evaluate more agent-generated code without turning every senior engineer into a full-time reviewer.”
Platform Lead
Fintech
“In the first 30 days, we shipped 103 PRs and saw a 3x productivity gain across 60-70% of our developers.”
Director of Engineering
Large logistics company
“The review queue stopped growing with every AI-generated PR. Engineers now focus on the changes that actually need judgment.”
VP of Engineering
SaaS
The shift
A team of agents onevery PR — not anothercomment bot.
We rebuilt review on Cosmos as a set of agents, each with one job. They move the PR forward on their own — scanning, catching bugs, fixing routine issues — and pull your engineers in only where their judgment matters most. The 5-minute demo shows it on a real PR.
PR Risk Analyzer
Scores every PR and routes it. Low-risk changes are auto-approved with a reason; the rest are tagged with exactly what a human needs to check.
Deep Code Review
Reads the change line by line and catches most high- and medium-severity bugs before a person opens the diff.
Pair Reviewer
Walks a human through the decisions that matter (design, security, product intent) instead of a full line-by-line read, then posts the final comments back.
Memory Manager
Learns from every merged PR and human correction, saving it as per-repo knowledge the other agents read first, so reviews fit your team better over time.
Run it against the PRsyour reviewers struggle with.
Pick a representative repository, measure time-to-first-review, merge time, and reviewer overrides — then expand.
What teams askbefore a pilot.
Static analysis applies predefined rules to known patterns. Augment combines those deterministic checks with codebase-aware reasoning across the PR, related files, dependencies, repository guidance, and the linked ticket. It focuses on correctness, security, and cross-system behavior instead of style noise.
What's next, Alex?
All Experts
Mine
Pinned
Deep Code Reviewer
Reads a PR end-to-end — logic, edge cases, naming, security surface, and test completeness — then posts detailed inline comments with an approve / request-changes verdict.
CI Failure Investigator
Triggered on any failed GitHub Actions run — reads the log, identifies the root-cause step, and posts a plain-English diagnosis as a PR comment with a suggested fix.
PR Review Enforcer
Reviews every opened pull request against your team's coding standards, leaves inline comments, and requests changes when tests are missing.
Security Vulnerability Triager
Monitors Dependabot and Snyk alerts, scores exploitability using CVSS context, and files prioritized GitHub issues with remediation steps.
Dependency Upgrade Bot
Groups safe minor/patch bumps into a single PR per repo, runs the test suite, and only merges automatically when CI is green.
Incident Response Coordinator
On a PagerDuty alert, pages the on-call engineer via Slack, opens a war-room channel, attaches runbooks, and drafts a timeline doc updated every 15 min.
Routing
C
G
Prism (Claude + Gemini)
Auto-routes each turn for cost + quality
Single model
Claude Sonnet 4.6
Balanced speed + intelligence
Claude Opus 4
Highest capability
Gemini 2.5 Pro
Long context tasks