Hallucinations in code are the least dangerous form of LLM mistakes

I do these things for this:

- keep the outline in my head: I don't give up the architect's seat. I decide which module does what and how it fits in the whole system, it's contract with other modules etc.

- review the code: this can be construed as negating the point of LLMs as this is time consuming but I think it is important to go through line by line and understand every line. You will absorb some of the LLM generated code in the process which will form an imperfect map in your head. That's essential for beginning troubleshooting next time things go wrong.

- last mile connectivity: several times the LLM takes you there but can't complete the last mile connectivity; instead of wasting time chasing it, do the final wiring yourself. This is a great shortcut to achieve the previous point.

The way you've written this comes across like the AI is influencing your writing style....

Three bullet points, each with three sentences (ok last one has a semicolon instead) is a dead giveaway

> This is a great shortcut to achieve the previous point.

How does doing the hard part provide a shortcut for reviewing all the LLVM code?

If anything it's a long cut, because now you have to understand the code and write it yourself. This isn't great, it's terrible.

Lots of people wrote like that before AI, AI writes like people its made to copy how people write. It wouldn't write like that if people didn't.

Yes, I prefer using lists myself, too, does not mean my writing is being influenced by AI. I have always liked bullet points long before AI was even a thing, it is for better organization and visual clarity.

In my experience you just don't keep as good a map of the codebase in your head when you have LLMs write a large part of your codebase as when you write everything yourself. Having a really good map of the codebase in your head is what brings you large productivity boosts when maintaining the code. So while LLMs do give me a 20-30% productivity boost for the initial implementation, they bring huge disadvantages after that, and that's why I still mostly write code myself and use LLMs only as a stackoverflow alternative.

thatistrue I us ed to write lik this b4 ai it has change my life

Sure whatever works for you; my approach works for me

But you don't explain how doing the hard part shortcuts needing to understand the LLVM code.

I feel like “looks like it’s written by AI” might become a critique of writing that’s very template-like, neutral, corporate. I don’t usually dislike it though, as long as the information is there.

Three bullet points AND three sentences?!! Get outta here...

The evolution of a codebase is an essential missing piece of our development processes. Barring detailed design docs that no one has time to write and then update, understanding that evolution is the key to understanding the design intent (the "why") of the codebase. Without that why, there will be no consistency, and less chance of success.

"Short cuts make long delays." --Tolkien

As someone pretty firmly in the anti-AI camp, I'm genuinely glad that you've personally found AI a useful tool to polish text and help you communicate.

I think that just because someone might be more or less eloquent than someone else, the value of their thoughts and contributions shouldn't be weighed any differently. In a way, AI formatting and grammar assistance could be a step towards a more equitable future, one where ideas are judged on inherent merits rather than superficial junk like spel;ng or idk typos n shi.t

However, I think what the parent commenter (and I) might be saying is that it seems you're relying on AI for more than just help expressing yourself—it seems you're relying on it to do the thinking too. I'd urge you to consider if that's what you really want from a tool you use. That said, I'm just some random preachy-judgy stranger on the internet, you don't owe me shit, lol

(Side notes I couldn't help but include: I think talking about AI and language is way more complicated (and fascinating) than just that aspect, including things I'm absolutely unqualified to comment on—discrimination against AAVE use, classism, and racism can't and shouldn't be addressed by a magic-wand spell-checker that "fixes" everyone's speech to be "correct" (as if a sole cultural hegemony or way of speech is somehow better than any other))

> As someone pretty firmly in the anti-AI camp, I'm genuinely glad that you've personally found AI a useful tool to polish text and help you communicate.

> I think that just because someone might be more or less eloquent than someone else, the value of their thoughts and contributions shouldn't be weighed any differently. In a way, AI formatting and grammar assistance could be a step towards a more equitable future, one where ideas are judged on inherent merits rather than superficial junk like spel;ng or idk typos n shi.t

I guess I must come clean that my reply was sarcasm which obviously fell flat and caused you to come to the defense of those who can't spell - I swear I don't have anything against them.

> However, I think what the parent commenter (and I) might be saying is that it seems you're relying on AI for more than just help expressing yourself—it seems you're relying on it to do the thinking too. I'd urge you to consider if that's what you really want from a tool you use. That said, I'm just some random preachy-judgy stranger on the internet, you don't owe me shit, lol

You and presumably the parent commenter have missed the main point of the retort - you are assuming I am relying on AI for my content or its style. It is neither - I like writing point-wise in a systematic manner, always have, always will - AI or no-AI be damned. It is the all-knowing veil-piercing eagle-eyed deduction of random preachy-judgy strangers on the internet about something being AI-generated/aided just because it follows structure, that is annoying.

It's funny that some folks seem to assume AI writing style just arrive out of thin air....

I have enough projects that I'm responsible for now (over 200 packages on PyPI, over 800 GitHub repositories) that I gave up on keeping a map of my codebases in my head a long time ago - occasionally I'll stumble across projects I released that I don't even remember existing!

My solution for this is documentation, automated tests and sticking to the same conventions and libraries (like using Click for command line argument parsing) across as many projects as possible. It's essential that I can revisit a project and ramp up my mental model of how it works as quickly as possible.

I talked a bit more about this approach here: https://simonwillison.net/2022/Nov/26/productivity/

You're an extreme outlier. Most programmers work with 1-3 codebases probably. Obviously you can't keep 800 codebases in your head, and you have to settle for your approach out of necessity. I find it hard to believe you get anywhere close to the productivity benefits of having a good mental map of a codebase with just good documentation and extensive test coverage. I don't have any data on this, but from experience I'd say that people who really know a codebase can be 10-50x as fast at fixing bugs than those with only a mediocre familiarity.

Maybe LLM generated text was their first-contact with structured and systematic writing.