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Stop squashing your commits. You're squashing your AI too

5 points by jannesblobel ↗ HN
Everyone keeps saying “keep your Git history clean.” Squash, rebase, linearize. It looks neat in the git log.

But here’s the thing: in 2025 our biggest collaborators aren’t just humans, they’re AI tools. And those tools need the messy history: the failed attempts, the typos, the bad refactors. That’s the context they learn from.

When we squash everything into a perfect history, we’re deleting the very breadcrumbs that could help an agent explain a bug, trace a regression, or warn us we’re about to repeat an old mistake.

“Clean history” makes reviewers happy today. But it’s technical debt for tomorrow’s AI-assisted development

5 comments

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Hackbraten
I’m finding it difficult to agree with you without a concrete example.

How exactly would it help to have a commit that introduces a problem and then another one that fixes it? How does leaving in a bad refactor, failed attempt, or typo help the AI tool with anything?

raw_anon_1111
LLMs are so bad with going off the rails when it comes to coding, I purposefully arrange my sessions so it doesn’t have to digest too much at once.

I recently had it go off the rails on some greenfield work where I was clearly using MySQL with Python and in the middle of the session it started generating Postgres code using the Postgres driver and doing Postgres style upserts.

ManlyBread
It's as easy to say that this will poison the context and produce worse results. Do you have any actual examples? Without any sort of an example this sounds like some software voodoo.
bjourne
I don't think the AI argument has merit, but I agree with your general sentiment. Squashing commits destroys part of the signal and makes software archaeology more difficult. There is huge value in a commit history that reflects how the software actually was made.
arman_nocapro
Great analysis, but I think you're missing the forest for the trees here. The real issue isn't about "understanding project history" - it's about signal-to-noise ratio, plain and simple.

`raw_anon_1111` nailed it with the context rot reference. After working with LLMs daily for the past year, I've found that garbage in = garbage out, consistently. It's like working with that brilliant junior dev who can't see the big picture through all the implementation details.

You wouldn't dump your entire git history into a code review, would you? So why would you feed it to an LLM? `ManlyBread`'s "poison the context" is exactly right. Every token spent on explaining dead ends or reverted commits is a token wasted.

The solution isn't more data - it's better data. What we need are tools that create concise, high-signal context packages. Architecture diagrams, clean code, and clear requirements. Not the messy sausage-making that got us there.

This isn't just theory - I cut API costs by 40% when I started curating prompts instead of just dumping everything into context. The attention window is precious - use it wisely.