I used to dread Monday mornings. Not because of the work itself, but because of the pull request backlog. By 9:30 AM, I would have fifteen open PRs staring at me. Half were trivial style fixes. The other half were complex logic changes that required actual brain power. I spent hours nitpicking variable names and missing semicolons. It was exhausting and unproductive. In March 2026, I decided enough was enough. I built a local AI agent to handle the first pass of code reviews. The result? I saved about six hours every week. More importantly, my actual review quality improved because I was focusing on architecture, not syntax. Here is exactly how I set it up, what broke, and why you should probably do this too. The Problem With Human Reviewers Let’s look at the data from my team’s GitHub repo in Q1 2026. We averaged 45 PRs per week. Each PR took me roughly 15 minutes to review initially. That is 11.25 hours of pure review time. But here is the kicker.…