January 16, 2026
Bot wars in the code review
Building a better Bugbot
AI code cop levels up; devs ask who's boss
TLDR: Bugbot claims a big upgrade: it now catches more real issues, with a reported fix rate over 70% and more bugs resolved per change. Commenters worry less about mistakes and more about power, warning that junior devs may treat bot feedback as gospel—raising fresh questions about trust and accountability.
Bugbot just leveled up, and the internet has feelings. The team behind the AI “code reviewer” says it now catches more real problems before they hit production, boosting its resolution rate (how many flagged issues actually get fixed) from 52% to over 70% in their post. They hill‑climbed there with parallel checks, majority voting, and a dashboard that spotlights results. Cool numbers… until the comments rolled in.
The mood? Spicy. Skeptics see a future where devs argue with a robot in a pull request (PR—basically a code change waiting for approval). One user groaned about “reviewing the mediocre code written by an overconfident LLM” (large language model—an AI that writes text), dubbing the back‑and‑forth with bots PR court. Another warned the real problem isn’t mistakes, it’s authority: younger engineers treating bot comments as gospel. Cue the new office meme: bot‑splaining.
Still, some folks loved the data flex. An AI‑driven metric that focuses on fixes feels more honest than fuzzy vibes, and the system’s got practical upgrades like faster repo access and custom rules for team‑specific no‑nos. The split is clear: metrics‑heads say let the numbers speak; culture‑watchers say power dynamics matter. Bugbot caught more bugs—now it has to dodge blame.
Key Points
- •Bugbot is an AI code review agent that analyzes pull requests for logic, performance, and security issues and was released after internal success.
- •Quality was improved through parallel bug-finding passes with randomized diff ordering and majority voting, plus validation and deduplication.
- •Productionizing required rebuilding Git integration in Rust, minimizing data fetched, and adding rate-limit monitoring, request batching, and proxy infrastructure for GitHub.
- •Customizable Bugbot rules allow teams to encode codebase-specific invariants, such as unsafe migrations and internal API usage checks.
- •A resolution rate metric using AI at PR merge time enabled measurement; 40 experiments raised resolution rate from 52% to over 70% and doubled resolved bugs per PR.