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The End of Front-End Development

joshwcomeau.com

51–60 of 111 posts

Re: The End of Front-End Development

#51

Yet another blog post about how LLM can't replace people for X task. I wish there was less noise about this and more discussions on how we will (all) benefit from LLM replacing people. Like UBI, paying people to pursue their passions, etc. I personally would be fine if LLM replaced my $DAYJOB if it meant I could work on learning violin, gardening, or creating videogames.

> I personally would be fine if LLM replaced my $DAYJOB if it meant I could work on learning violin, gardening, or creating videogames.

But let's be realistic -- that's not at all what it would mean.

Re: The End of Front-End Development

#53
post #20

> A small JS app like this blog has ~65k lines of code, across 900+ files. That doesn't include the written content, only the JavaScript and TypeScript. More or less sums up why I think FE dev has reached peak ridiculous. Good luck ChatGPT.

Posting a comment without reading the entire article more or less sums up why I think HN comments aren’t worth reading.

Re: The End of Front-End Development

#54

With a decade of experience as a front end dev in this industry, I have to agree with the premise, although not for the reasons stated. AI is, and will be, hugely disruptive for all fields of programming. But it won't be taking jobs any time soon. The reason front end development as a skillset is coming to an end is that we've solved all of the problems that front end devs were responsible for. Front end used to be a…

Yeah, this is all great and lots of words, but I just spent all morning centering a radio button in a td lol

Re: The End of Front-End Development

#55
post #21

> "Fundamentally, LLMs are super-powerful text predictors. Given a prompt, they use machine learning to try and come up with the most likely set of characters that follow the prompt." I've heard this tossed around and in the old days it used to be true. BUT in the process of learning to predict text, just like with CNNs that learned to predict image types, it seems GPT learned some very interesting functions that bri…

> Given a prompt, they use machine learning to try and come up with the most likely set of characters that follow the prompt. Funnily enough this is almost exactly how human children work when they're learning to talk

It doesn't really matter how we learn the features that we learn; I've heard numerous times that ML models tend to learn architectures/neurons that biological neurons do; I've seen convincing evidence about image recognition back in the day that this is the case.

I read that animals dream in the woumb partially to pre-train their nervous system, including vision stuff.

But I'm convinced GPT-3/4 did learn a lot of features/generalization/reasoning, even if part of a "text prediction".

Sure, it's predicting text... but to do so it learnt some calculus and quantum mechanics -- it's just an example, I don't know the cognitive building blocks to explain how humans/future AI do their reasoning.

Re: The End of Front-End Development

#56

"augmenting, not replacing" has been my go-to line for people who are anxious. There is no real meaningful discussion taking place about replacing people, it's just about augmenting people.

If you have a team of twenty people, and you augment them well enough that they can all work more efficiently, the team can go two directions: it can stay the same size and do more, or it can shrink and do the same amount of work.

Some organizations are going to take the first approach, and some will take the second. Neither is right; some organizations can expand on what they do. Others have a narrower scope, and would be better off getting leaner.

There's always been a tension between an organization's needs and an individual's needs. I'm pretty sure these tools are going to increase that tension for a while.

Re: The End of Front-End Development

#58

There seems like a disconnect between the breathless AI hype and reality. I tend to be on team-LLM (having exposure to it in my daily work), and my stance is that it's going to revolutionize some narrow domains and features of products, but the idea that it will replace white collar labor generally seems poorly substantiated by what we know so far. What we see ChatGPT being good at is largely boilerplate . The folks…

I find an engineer's value is in creating things have not been created before. As the author of the article says, there's already lots of great tools for making simple sites. So far, I've found that LLMs are not good at making novel software, it's basically a glorified stackoverflow. But that's still quite useful… for a programmer!

That's exactly it. Ultimately programming is just telling the computer what you want it to do - something that a LLM is unable to do. There may be a future where an AI is smart enough and demonstrates enough analytical, cognition, and deduction ability that it can take over specifying what a computer should do - but it's not today and it's not immediately at-hand. Nor is anything that can do so likely to emerge from LLMs, as opposed to a fundamentally different architecture of AI.

For most of our industry's history telling a computer what to do involved a lot of very painful and boring things that aren't really related to what you actually want from the computer. Moving registers around. Assigning variables. Managing memory.

But the entire time we've also been converging on doing less and less of this rote busywork. Advances in frameworks and programming languages has, in each iteration, gotten us closer and closer to simply telling the computer what you want, reducing the need for this rote busywork.

So now we have an AI that is quite good (though again: far from good enough to be unsupervised) at this busywork. For people whose jobs are largely consisted of this busywork this may be highly impactful - but your job as a programmer is to minimize this busywork to the maximum extent possible anyway.

Re: The End of Front-End Development

#59
post #21

> "Fundamentally, LLMs are super-powerful text predictors. Given a prompt, they use machine learning to try and come up with the most likely set of characters that follow the prompt." I've heard this tossed around and in the old days it used to be true. BUT in the process of learning to predict text, just like with CNNs that learned to predict image types, it seems GPT learned some very interesting functions that bri…

My mothe-in-law is almost deaf. However, as you said, she is a good example of a "super-powerful text predictor". She almost always predicts what you're talking about even not hearing a single word. And most of the time she offers meaningful answers just as GPT does. But not always (same as GPT) I don't expect, however, that she will program front ends any time soon

> I don't expect, however, that she will program front ends any time soon

Liar :) If she wrote/scored as good as Chat GPT-4 does, you'd be worried she's going to steal your job :).

I mean, I know I'm lucky my wife doesn't know programming, lest she'd know more about anything that I do.

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