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Re:Sonnet 5.5 by gchamonlive on Monday September 28, 2026 @10:12PM (#49887252)
Maybe, it'll be exciting to see, and I'm all about accessibility, but in this case I also don't think it's about model capability or intelligence, it's the low information to noise ratio in the codebase. There just won't be enough information in the code itself to know what to fix. Fix how? What should it do? I'm really not sure you can reconstruct intention from a codebase created unsupervised.
Re:Sonnet 5.5 by noisy_boy on Tuesday September 29, 2026 @12:25AM (#49888269)
1. Implement feature and write tests for the code

2. Make sure tests pass

3. <Every now and then> Review code for quality and fix - make sure tests pass.

4. Go to #1

Overly simplistic? Yes. But I would wager that this can go a long way, even for vibe coders.

Re:Sonnet 5.5 by gbalduzzi on Tuesday September 29, 2026 @02:10AM (#49888897)
I keep seeing this but I'm not sure it is effective in the long run *if unsupervised*.

"Review quality and fix" doesn't mean a lot without context.

Does it mean to remove unused features and simplify the underlaying code? Does it mean changing the data structures to better support future development? Does it mean improving performance because of bottlenecks?

You are supposed to tell an LLM what your codebase needs, but if you just vibe code without knowing the code, "review quality and fix" will have unexpected results

Re:Sonnet 5.5 by gchamonlive on Tuesday September 29, 2026 @07:05AM (#49891196)
It's glaring to see who's still buying the positivists AI hype and who's done actual work with it.

AI is amazing, but people need to realise meaning and intention can't exist in a vacuum.

Re:Sonnet 5.5 by alexytsu on Tuesday September 29, 2026 @01:58AM (#49888806)
Commit the intention as specs. If tokens/intelligence become that much cheaper over time, then "throwing away the code" to start again becomes feasible.
Re:Sonnet 5.5 by gchamonlive on Tuesday September 29, 2026 @07:01AM (#49891154)
Yeah, but not quite. I've done this with a project of mine, wrote it in python so it's easy and quick to read and debug, saved every work item and decision, done everything through agents so there was logs to go back to, and when I tried reimplementing in elixir everything fell apart.

Even after documenting decision and specs you need somehow to replay these in the correct sequence after you've validated these specs are still updated. Imagine you spec a feature, it works well, but in an edge case while doing a separate work you see something wrong, will you stop, fix and update the related spec? You will trust the AI will do this, and you guessed right, the counter-probability of success also has effect here, so eventually you will do undocumented changed in the codebase that won't reflect in the spec.

Now imagine all this but in the hands of someone that is an expert in their field but has zero notion what we are talking about here. Just look at the state of packages in R, the programming language, you'll see that technical competency and intelligence don't translate immediately to efficiency in a programming role.

Re:Sonnet 5.5 by flir on Tuesday September 29, 2026 @07:33AM (#49891459)
A few days ago somebody linked to their own project: https://ljtn.github.io/epiq/

I haven't had time to dive into it yet, but I think it might structure things in the way you want.

Re:Sonnet 5.5 by gchamonlive on Tuesday September 29, 2026 @07:46AM (#49891583)
Thanks! Will look into it.

This is something I didn't think about. Have a tech illiterate friendly harness that will keep asking technical questions the mainstream user won't be aware they needed be addressed, until there is enough evidence to either start an implementation or outright reject the project with suggestions where the user might look into to better prepare for another session.