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Comment by redox99

1 day ago

Sorry just woke up, I wasn't being clear.

There's two thresholds.

1. Tasks models can do. 2. Tasks models can do with enough reliability that you can YOLO merge without looking at the code.

Most models can do most of 1. That's no longer the interesting part.

2. is quickly expand. I can trust opus 5.5 enough with easy to medium tasks that I can YOLO merge them. For open models, I can only trust them with easy tasks if I want to YOLO merge.

I'd love to have a stronger model that I can trust to YOLO merge hard tasks.

I think this is where we may have to agree to disagree, because this not something that I'd do outside of toy projects. Not necessarily because I'm worried about the correctness of a single MR (in fact, it may very well be more likely to be correct than a human-authored and -reviewed one), but because I'm concerned about the accrual of technical debt. Even if each individual MR is correct, the trajectory for code quality can trend downwards.

The recent update to SlopCodeBench that includes Astra and Opus 5.5 (including the insight that higher reasoning levels may not improve the situation) seems to match my intuition. [1]

[1] https://github.com/humanlayer/advanced-context-engineering-f...

I am genuinely curious, at what point did you find yourself comfortable “YOLO merging without looking at the code”?

I struggle to find myself ever feeling comfortable doing this in a production environment at my day job.

  • Probably around GPT 5.6 Sol.

    These days your average Opus 5.5 PR with multiple passes of review by Opus 5.5 and Sol 6.1 agents is much less likely to contain bugs than your pre-AI PR.