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Most PRs that are generated by agents today get YOLO merged because its hard for human mind to comprehend when your agent just suddenly shows up with 230 file changes. This is an attempt to reduce the mental burden by classifying each change in a review to P0, P1, P2. Only P0 are shown by default. The priorities are configurable. The diffs are also show using a natural language. The original code is one toggle away.
You can tell it not to do this?
Something like:
"Plan out the change. Structure the plan so that it can be broken into individual PR's that each covers a single logical part of the change. Aim for less than 500 lines per PR unless the change is trivial and mechanical." (with a lower end model you need to be a lot more precise; with a frontier model you only really need to let it know you care about the PR size)
... in your prompts, coupled with gating PR creation on passing a stringent automated code review that also reviews it on whether or not it adheres to the rules you set regarding complexity of the PR, solves that problem without hiding the complexity.
If you have 230 file changes, that is a process failure unless they're purely obviously committing purely e.g. linter cleanups.
I yolo vibe develop, but how one end up with 210 files change commits? Unless one shooting a project, there is no way to end up with such scope? I really don't get it.
Not quite. Ironically, they get PR-reviewed by someone else's agent. The humans in between are meat-proxies, pressing OK buttons.
Nice idea. This could make large agent-generated PRs much easier to review.
I'm going back to writing code by hand. AI can assist with debugging and research. I've had enough of slop. I've had enough of dealing with people wielding slop machines.
In the end... I don't feel better off. More tooling hasn't been the answer. It has only resulted in more complexity, less happiness, and about the same velocity as before we did agenetic engineering.
I think your engineering process is fundamentally broken if you are generating PRs with 230 files changed so regularly that you need to bolt on more AI. You’re solving the wrong problem.
Welcome to 2026.
My dev branch got broken when I rebased to main after a week of drift.
I had to bisect over around a million commits to the monorepo to find the culprit.
This is bananas. I've seen 25 year old software systems that haven't broken the 100k commits barrier. It feels like that ought to be enough for entire product lifecycles. What's going on that isn't simply wheelspinning?
I can confirm that our code quality at work is regressing and we are shipping less product features than before with AI.
That really stood out.
Code is there to be read and understood by the human developers who come later.
The git history is a similar record, that's why the commits that make it to main (the squashed PRs) should cover one(ish) thing each and be self contained.
Something covering 230 files should be a mechanical change like running a linter or the AI is moving an API from one signature to another.
If an LLM generated a 230 file change they are also capable of going back and breaking it up.
One thing they are bad at is comments that are succinct since they almost only ever add words.
Tbf, once the codebase is slopped enough that becomes impossible and only LLM can come later.
Yeah, we should push back on this. We don't have to accept this outcome as if it's inevitable.
Have you been under a rock in the last two years?? Code is written solely by AI now, and hence it needs to be understood by AI only. Humans can still give some feedback on architecture and high level design to feel important, but even that has its days counted already.
Slop projects to solve slop
confidence score really feels like real machine learning project which we test to check the confusion matrix
I don't understand Jev. Its a generic classifier right? Like the classifiers we were building 15 years ago with random forrests and logistic regressions, but just generic. What's so revolutionary? And how can the accuracy be any better than a custom trained classifier that can be built in a day (an hour using Claude).
I don't understand the hype.
Because it's all "AI" now <insert Ancient Aliens meme>
Have you tried Jev and compared it against your alternative classifiers? Should take half an hour to do that, then you’ll have your answer (or someone who already did it can tell you here).
You don't need to train it, you can throw pretty much whatever at it and it'll work and it's extremely cheap. That's it.
I don’t think its much cheaper like luna is double the cost. and you can easily use luna to generate a training set and train your own model. I think the main things its faster so a lot of people go the Wow moment I can classify my whole db at once. Or this model decides so quickly. Speed is the key differentiator, it’s a strong one, always.
I have a better idea, what about stop spamming slop PRs to projects?