AutoGen excels at automated code review by orchestrating multiple AI agents that analyze code from different perspectives through structured conversation. Unlike single-pass AI code review tools, AutoGen creates a review crew where a Security Agent checks for vulnerabilities, a...
ZTABS builds code review automation with AutoGen — delivering production-grade solutions backed by 500+ projects and 10+ years of experience. AutoGen excels at automated code review by orchestrating multiple AI agents that analyze code from different perspectives through structured conversation. Unlike single-pass AI code review tools, AutoGen creates a review crew where a Security Agent checks for vulnerabilities, a Performance Agent identifies bottlenecks, a Style Agent enforces coding standards, and an Architecture Agent evaluates design patterns. Get a free consultation →
500+
Projects Delivered
4.9/5
Client Rating
10+
Years Experience
AutoGen is a proven choice for code review automation. Our team has delivered hundreds of code review automation projects with AutoGen, and the results speak for themselves.
AutoGen excels at automated code review by orchestrating multiple AI agents that analyze code from different perspectives through structured conversation. Unlike single-pass AI code review tools, AutoGen creates a review crew where a Security Agent checks for vulnerabilities, a Performance Agent identifies bottlenecks, a Style Agent enforces coding standards, and an Architecture Agent evaluates design patterns. These agents discuss findings, debate severity, and produce a consolidated review that is significantly more thorough than any single-agent approach. The built-in code execution sandbox lets agents run tests and verify their findings before reporting.
Security, performance, style, and architecture agents each review from their expertise. The combined review catches issues that single-perspective tools miss entirely.
Agents discuss and debate the severity of findings. A performance concern in a rarely-called function is downgraded, while a security issue in an authentication flow is escalated.
Agents can run tests, benchmarks, and static analysis in sandboxed environments to verify their findings before reporting. Fewer false positives, more actionable feedback.
Configure each agent with your team coding standards, security policies, and architectural guidelines. Reviews enforce your specific quality bar, not generic best practices.
Building code review automation with AutoGen?
Our team has delivered hundreds of AutoGen projects. Talk to a senior engineer today.
Schedule a CallConfigure the Style Agent with your actual codebase patterns, not generic style guides. Feed it 10-20 approved PRs as examples of your team standards — it will enforce consistency far more effectively than rule-based linters.
AutoGen has become the go-to choice for code review automation because it balances developer productivity with production performance. The ecosystem maturity means fewer custom solutions and faster time-to-market.
| Layer | Tool |
|---|---|
| Framework | AutoGen 0.4+ |
| LLM | Claude 3.5 Sonnet / GPT-4o |
| Code Execution | Docker sandbox |
| CI/CD | GitHub Actions |
| Static Analysis | ESLint / SonarQube integration |
| Backend | Python |
An AutoGen code review system triggers on pull request creation via GitHub webhook. The PR diff is distributed to specialized agents. The Security Agent scans for injection vulnerabilities, authentication flaws, exposed secrets, and insecure dependencies.
The Performance Agent identifies N+1 queries, unnecessary re-renders, memory leaks, and algorithmic inefficiencies. The Style Agent checks naming conventions, code organization, documentation, and adherence to team standards. The Architecture Agent evaluates design patterns, separation of concerns, and consistency with the existing codebase.
Agents discuss their findings in a structured conversation — the Security Agent might flag a database query, and the Performance Agent confirms it is also a bottleneck, increasing the priority. The code execution sandbox runs targeted tests and benchmarks to verify claims. A Summarizer Agent consolidates findings into a prioritized review with clear explanations, code suggestions, and severity ratings.
The review posts directly to the GitHub PR as structured comments.
Our senior AutoGen engineers have delivered 500+ projects. Get a free consultation with a technical architect.