I wrote twice as much code last quarter, and it was better. I use Claude Code daily via Steve Molitor’s claude-code.el and monet.el integration for Emacs. Once a review is ready, CodeRabbit handles it. My daily AI usage really kicked into high gear back in October 2025, when we got a large amount of Claude Code credit grants and I could use it as much as I wanted.
The graph below is the number of lines of code changed (added and deleted) in my merge requests (MR), summed monthly, on our main application repository; a Next.js application with 200KLoC — not something an agent can easily get into. I authored 773 merge requests on this project alone which runs in production to serve our clients — just to emphasize the value of the sample-size:
You can see a clear 2x increase when I started to use Claude Code daily around October 2025. Like most folks, I found Claude Code to be amazing when working as a pair programmer to write the code or review my changes in short feedback loops, to explore greenfield projects or to strengthen tests on brownfield projects.
Around that time, I felt the quality of my code improving too. Below is the number of normalized comments \(N\) in each of the MRs: or the number of comments \(C\) divided by the sum of lines of code added \(A\) and deleted \(D\):
\begin{equation} N = \frac{C}{(A + D)} \end{equation}
Back in April 2025, we rolled out CodeRabbit which picked up over 70% of the reviewing work for everyone. Most team members do not perform code reviews anymore, except for myself — I’ll probably explain why in another post. Thus, on the changes I author, over 95% of the comments are just done by CodeRabbit from that time onwards.
Normalized comments is an interesting metric since it reflects the quality of my work with Claude Code, prior to review by others and CodeRabbit. If the value decreased there, it could be that:
- We got lazy about reviewing, but CodeRabbit is pretty much the only reviewer of my work;
- We output a lot more code or the quality of the code increased;
- The work we do is a lot easier, so there’s just fewer issues with it.
AI certainly had an impact on point 2, given the top graph. You can also see a dip soon after October 2025 when I started to use Claude Code, but then a bump appears again in January 2026. That bump is due to the fact that I had to tackle a challenging issue that spanned several MRs. It’s quite visible when looking at the histogram of independent values:
There are other common proxies for code quality: such as unit tests. This is the raw number of unit tests on the main project branch, over time and it went up nearly 5x in the last 4 months:
Additionally, we have not had production rollbacks or outages in the last 4 months, consistent with the past year (We only ever had to perform production rollbacks twice). So agent usage is not called into question in our team.
The stats in this post were extracted using a tool written by Claude Code.