[doodlesdev]

I don't think you want LLMs touching projects that cost over $800.000.000, even to assemble "documentation" (since the LLM can't really document in as much it's translating what it's reading, because documentation includes much more information than what's stored in the code itself).

It's a cool idea, though, I'd like to see this done as an experiment :)

[philipwhiuk]

> It's a cool idea, though, I'd like to see this done as an experiment :)

Since the Bun AI LLM 'exeriment' conversion got merged I'm a lot less trusting of 'experiments' with LLMs. They seem to get shipped

[gabbagool]

My thought on this is that LLMs should be allowed to touch high stakes projects, but they shouldn't be left completely unsupervised.

Here me out.

Would you let AI manage your investments/retirement savings/etc. completely autonomously and unsupervised? Or would that make you a little nervous?

What if you had to undergo a X-Ray or a MRI. Would you ONLY want AI reading the images? Would you ONLY want a human radiologist reading the images? This is an interesting one because I would want both. In fact, I would find it questionable if AI wasn't given the opportunity to look at the images.

[roflmaostc]

I am fully aware of the costs and so on. But i can certainly imagine that LLMs help with the process of understanding and editing old code.

And of course you need to test and debug before you ship to production.

[Rohansi]

> i can certainly imagine that LLMs help with the process of understanding and editing old code.

Can you trust it with assembly language for a custom-built CPU with its own instruction set? Even if you digitized all of the documentation you have no idea what was lost since 1977 (or earlier), or what was never written down to begin with.

[rvnx]

Anthropic / Google / Meta / Airbus / Boeing / ASML EUV machines, etc, etc... are all developed using LLMs and they are much more expensive than this

[doodlesdev]

Arguably, Anthropic and Boeing are NOT what you should use to determine whether your coding practices are reasonable. Software problems with Boeing have literally killed hundreds of people due to faulty code and Claude Code is know to be a pretty buggy CLI (although extremely useful, sure).

Though I agree with the expensive factor. Perhaps, what I actually believe is that LLMs shouldn't touch code that's as mission critical as what NASA works on, even though it might be great to develop user-facing frontend software and CRUD backend code for huge corporations and projects.