TheAgeOfSuperboredom comments on Astral to Join OpenAI

submitted 7 months ago by galaxy_nova@lemmy.world to c/technology@lemmy.world

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Today, AI is rapidly changing the way we build software, and the pace of that change is only accelerating. If our goal is to make programming more productive, then building at the frontier of AI and software feels like the highest-leverage thing we can do.

It is increasingly clear to me that Codex is that frontier. And by bringing Astral’s tooling and expertise to OpenAI, we’re putting ourselves in a position to push it forward. After joining the Codex team, we’ll continue building our open source tools, explore ways they can work more seamlessly with Codex, and expand our reach to think more broadly about the future of software development.

[–] TheAgeOfSuperboredom@lemmy.ca 16 points 7 months ago (4 children)

I find that Python requires a fair bit of discipline to keep it readable, and I've seen some very unreadable code written by people. Vibe coding with Python's dynamic nature seems like a match made in hell.

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[–] galaxy_nova@lemmy.world [S] 6 points 7 months ago* (last edited 7 months ago) (1 child)

This is true although that’s what enforcing strict type checking and good linting is supposed to help with. I think it’s partially an issue that you can kinda just type what you think and not everyone thinks efficiently/ programmer-y

Edited for clarity

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[–] TheAgeOfSuperboredom@lemmy.ca 2 points 7 months ago

Agreed! I think both linting and type checking are extremely important to Python, but it's also an extra step that far too many people just don't take. And honestly, I used to get tripped up sometimes with setting up Python tooling before I started using uv.

Unfortunately I also have to work with the occasional Python script that someone just slapped together, and that's something far too easy to do in Python. It does kind of remind me of vibe coding. Initial velocity seems high, but if you're not thinking about it, long term maintenance tanks.

That's not to say Python is bad, and there is certainly a lot of good Python code out there too. But it's a language that does make it easy to make a mess, which will probably be compounded by LLMs.

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[–] eager_eagle@lemmy.world 1 point 7 months ago (1 child)

It's manageable if you pass along these rules to the LLM. I've actually had more success asking the LLM than giving code reviews to some interns, and even someone who coded professionally before.

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[+] badgermurphy@lemmy.world 1 point 7 months ago (1 child)

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[–] eager_eagle@lemmy.world 2 points 7 months ago

Ok, I'm not suggesting replacing humans with AI and I despise companies trying to do this unsustainable practice.

With that out of the way, I'll restate that LLMs follow some rules more reliably than humans today. It's also easier to give feedback when you don't have to worry about coming across as a pedantic prick for pointing out the smaller things.

On your point that LLMs are not improving; well, agents and tooling are definitely improving. 6 months ago I would need to babysit an agent to implement a moderately complex feature that touches a handful of files. Nowadays, not as much. It might get some things wrong, but usually because it lacks context rather than ability. They can write tests, run them, and iterate until it passes, then I can just look at the diff to make sure the tests and solution makes sense. Again, something that would fail to yield decent results just in the last year.