Comment by 0xbadcafebee
11 hours ago
Both of these are not really the right way to use AI to code with. There are two basic ways to code with AI that work:
1. Autocomplete. Pretty simple; you only accept auto-completes you actually want, as you manually write code.
2. Software engineering design and implementation workflow. The AI makes a plan, with tasks. It commits those plans to files. It starts sub-agents to tackle the tasks. The subagents create tests to validate the code, then writes code to pass the tests. The subagents finish their tasks, and the AI agent does a review of the work to see if it's accurate. Multiple passes find more bugs and fix them in a loop, until there is nothing left to fix.
I'm amazed that nobody thinks the latter is a real thing that works, when Claude fucking Code has been produced this way for like 6 months. There's tens of thousands of people using this completely vibe-coded software. It's not a hoax.
#2 does not negate my steering suggestion, so I'm not sure how you can conclude nobody thinks it's a real thing that works
also Claude Code is notoriously poorly built, so I wouldn't tout it as SOTA
I have worked at companies from startups to fortune 500. They all have garbage code. Who cares? It works anyway. The world is held together with duct tape, and it's unreasonably effective. I don't believe "code quality" can be measured by how it looks. The only meaningful measure of its quality is whether it runs and solves a user's problem.
Get the best programmer in the world. Have them write the most perfect source code in the world. In 10 years, it has to be completely rewritten. Why? The designer chose some advanced design that is conceptually superior, but did not survive the normal and constant churn of advancing technology. Compare that to some junior sysadmin writing a solution in Perl 5.x. It works 30 years later. Everyone would say the Perl solution was of inferior quality, yet it provides 3x more value.
I hear you about "it just works" mattering infinitely more than some arbitrary code quality metric
but I'm not judging Claude Code by how it looks. I kinda like the aesthetics. I'm talking about how slow, resource hungry and finnicky/flickery it is. it's objectively sloppy
> when Claude fucking Code has been produced this way for like 6 months
And people can look at the results (illegally) because that whole bunch of code has been leaked. Let's just say it's not looking good. These are the folks who actually made and trained Claude to begin with, they know the model more than anyone else, and the code is still absolute garbage tier by sensible human-written code quality standards.
Yet it works anyway. What does that say about human code quality standards?
Human code quality standards are built around the knowledge that humans prefer polished products that work consistently. You can get away without code quality in the short term, especially if you have no real competitors - to a lot of people, there just aren't any models other than Anthropic's which are particularly useful for software development. But in the long term it gets you into a poor quality trap that's often impossible to escape without starting over from scratch.
(Anthropic, of course, believes that advances in AI capability over the next few years will so radically reshape society that there's no point worrying about the long term.)