Don't you mean extinct?

I mostly like this article but

> Those who refuse to use an LLM will fall behind because they won't be able to produce as much

Seems like a silly and needlessly aggressive take.

Fall behind what? Able to produce "as much" what? I've never been evaluated on volume in my life. Nor have co workers who were severely "behind" ever feared for their jobs.

> Writing every line by hand is no longer the norm. Those who refuse to use an LLM will fall behind because they won't be able to produce as much

> It remains important to be able to read the code and understand the architecture. As a result, I reduce my velocity by iterating over my PR until it reaches the same level of quality I would have produced "by hand"

I do that too and when I do it I'm not sure anymore if I'm "producing as much more" than if I was doing it by hand. I need to spend time to read the code, break down the flow so that it clicks in my head and so that I'm 100% sure that I understand what is going on and what every line does. And then I still test it (executing it), because that's where you notice the edge cases anyways. Once I understand it and test it, the part where I iterate or fix small quirks and hallucinations is the smallest part of the job and is irrelevant if i do it by myself or ask the LLM to make the change.

I'm still not convinced that I'm faster with an LLM at all, since I add this new bottleneck (the time spent understanding every line). If I do it by hand it already clicks in my head, so it's faster for me to test it, find unaddressed edge cases and then confidently ship it. Maybe the LLMs gains are not in this at all and writing every line by hand will still be the norm for a long time.

Still, LLMs make me insanely faster in: finding something in the codebase, recostructing a flow and understanding the architecture, triaging a bug (sometimes it just solves it with a prompt), writing and updating tests, reviewing changes for potential issues. These days I have almost always 2/3 agents running doing something of the above. That saves me hours and you can pry an LLM from my dead hands, but I'm still not sold that it makes me faster at producing production grade code that I fully understand and follows my company architecture and standards.

Then sure, if I need to make a prototype or a small tool for myself or some novelty thing, an LLM can do it without me ever touching or reading the code. But I think that's not what the majority of software engineers are employed to do.

Did Tippett enjoy working on the Dinosaur Input Device as much as he did with his go-motion technique?

I see employability being discussed far more often than joy.

If your motivation was selling as many clothes as possible, then the industrial textile revolution was miraculous.

If you enjoyed knitting threads together, it was the crushing victory of mediocrity.

> I asked an LLM to write a Levenshtein distance function instead of adding a dependency to my project.

Which you likely failed to review thoroughly, so may be subtly wrong.

It's probably best to learn about LLMs, and then don't use them most of the time. It's much harder to justify not even knowing how the new thing works, than to justify not using it because the old thing is better.

With the improvements that AI has made in just the last year, it should be obvious to anyone that code written by an AI will at some point stop being "AI slop" and be better than the majority of coders are able to put out. Reduced to its basics, all code is just characters put into a sequence. Similar to chess or Go, both of which, it was claimed at one point or another, would be impossible for a computer to beat a human, until they did (chess 1997, go 2016), so computers will eventually produce better quality code than even a team of humans is capable of.

A genuine question : If an AI can reliably write code better than most coders, do it quicker, and produce code that runs efficiently which has less, or at least no more, bugs than human written code, why on earth would a company not use an AI to write all their code for most purposes?

And if they did, why is it important for that code to be 'elegant' or even human readable if the bug checking is also done by AI? (as seems to be the direction we are moving in)

I don't want to curate my own AGENTS file. I'd rather just copy someone else's verbatim similar to code formatting style.

Fabien, care to share your whole file? I'll plug it into my NixOS machine.

I joined VFX at the start of the 2000s, I rode the evolution of VFX from special effects, to fully digital, and back again (well not quite, "practical" effects are rarely practical, just really good VFX.)

I left in the late 2010s, Lots of competition meant that wages were kept down, and hours fucking long. It was fun, I loved being at the intersection of Art, infrastructure and programming.

I fear for the future.

I hope that I am ok, because I have experience of high scale that is not really in the training corpus. I've also been in ML for a reasonably long time, so have more experience of getting the dipshit machine to do useful things.

But thats pretty thin gruel.

I am rapidly approaching middle age, which means that no fucker is going to employ me as an apprentice if I want to re-train. My techincal and artistic skills are basically replaced. They are the equivalent of Linotype expert. Technically impressive but utterly fucking pointless for a world where newspapers are dead and so is analog printing. In 40 years I could possibly make a thin living as an artisan. But I plan on being dead by then.

I think this is a flawed analogy. In the past when we had a new way of doing something that obsoleted the old way, it replaced it because it was an obvious improvement. I mean, stop motion is cool, but obviously there are limitations.

The deal GenAI offers is: the result will be mediocre at best, on average it will be slop, but it will do it much faster. Ok, that's a fair value proposition in certain contexts. We've always had a need to prototype things fast, and the tradeoff with a prototype is always quality.

However, we're living in an age where we have WAY TOO MUCH in the way of information byproducts, even before AI. How many people do you meet that are like "God, I just wish I had more software in my life!" Most people don't want more software, they want less software that works better. They want more quality and less quantity. It's like this in almost everything digital now. I sign onto Netflix and I can't find anything to watch, even though there's more to watch than I could consume in a lifetime. I live in abundance but I don't want any of it.

GenAI offers us an abundance of stuff we don't want or need (lots of bad code, lots of bad writing, lots of bad illustrations, lots of bad videos) at a cost of stuff we do not have in abundance (energy, attention, natural resources, jobs). It strikes me as a bad trade: lets transform the stuff we need into stuff nobody wants, while decimating our culture in the process.

Anyway, FWIW I do agree with his point that the job has always been problem solving. I use LLMs to solve problems, I'm not extinct. But I'm not going to pretend that I think this is a net win.

"Ride the wave."

Or don't.

Most LLMs people are using to code are paywalled, and controlled by private, for-profit entities.

This is fundamentally different than the past, and diametrically opposed to the hacker.

If you're a hacker, which most of you are not (things have changed here over time), you will reject this.