⏳ How I save 10 swe days/year with LLMs

Bogdan Stanga — Sat, 23 Nov 2024 10:27:43 +0000

Over the last year, I’ve reviewed more than 1000 code changes. Most of the time was spent catching obvious mistakes rather than debating complex design decisions. If we estimate ~10 minutes per review, that’s 160+ hours spent reviewing code in just one year.

So I thought: could I get some of that time back using LLMs?

That's why I spent the last few weekends building Presubmit.ai, an open-source AI reviewer that runs as a Github Action right when you open a Pull Request. The results so far are promising: I estimate it can reduce the review time by 50%, which in my case would mean I save 80hours (~10 working days) per year.

Unlike similar SaaS solutions, the goal is not to replace the human reviewer but to highlight obvious mistakes early, spot security vulnerabilities and give more context about the change. I like to think of it as a “pre-reviewer”.

Some of its features are:

Line-by-line comments
PR summarization
Title generation on request
Responds to review comments

It supports all major LLMs, but I’ve found Anthropic's Claude works best for this use case.

Check out the code here:

DEV Community: Bogdan Stanga

⏳ How I save 10 swe days/year with LLMs