I Built a 10-Agent AI Code Review System with MiMo — Here's What I Learned

10 specialized AI agents review your code in parallel, 30 seconds to produce a risk report with inline comments on GitHub PRs. Here's the architecture and lessons

learned.

THE PROBLEM

Manual code review is slow. A typical PR takes 1-2 hours to review properly. Reviewers miss things when they're tired. "LGTM" becomes a rubber stamp.

I wanted to build something different: 10 domain experts reviewing simultaneously, each focused on their specialty, with a coordinator synthesizing the results.

THE ARCHITECTURE

The system uses LangGraph to orchestrate 9 parallel review agents, with a CoordinatorAgent that:

Semantic Deduplication (Jaccard similarity)

LLM Conflict Resolution

Risk Score Calculation (0-100)

Key Design Decisions:

Parallel, not sequential — LangGraph schedules all 9 agents simultaneously

Semantic deduplication — Different agents may report the same issue; Coordinator uses Jaccard similarity to merge

Conflict…