How I built a 2-agent code review loop for local Ollama workflows

When running code reviews with local LLMs, a single model can either hallucinate non-existent bugs or generate generic advice you end up ignoring.

To make local AI code review more useful, I built a closed Reviewer vs. Verifier loop for local Ollama workflows.

The Architecture: Two Local Agents, One Loop

Instead of trusting one model's output, the workflow splits the job into two roles:

Agent 1 (Reviewer): Reads the git diff or file changes. It searches specifically for logical flaws, security vulnerabilities, edge cases, or missing unit tests.

How I built a 2-agent code review loop for local Ollama workflows

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