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>You have to sweat through six months of weird error messages and missing semicolons before you get to the point where it feels like you're actually building things and making progress.

Computers are rude and honest and humans prefer a pretty lie to an ugly truth. Programmers must appreciate the ugly truth in their day-to-day lives more than any other profession. (Physical engineering and construction workers and repairers also need this virtue, but less often since their feedback cycles are slower.)

More than doctors? Feedback cycles in the OR and ICU get pretty fucking short.

I do think the overall premise is silly, programming isn’t that special in this regard in my opinion. Most professions are like this, they just might not be the most visible ones like politics, journalism, show biz.

Software developer have more to learn from other professions than they often think (the old engineering professions understand this a bit better)

Honestly I think its a step back. This is like saying google translate has made everyone fluent in Spanish. At the end of the day you still need to do some vetting and understanding how code works to effectively use chatgpt. the actual writing of the code was never the hard part of software development. If this thing is only speeding up developers by six months time, then thats kind of a waste of compute compared to just offering computer science classes in schools imo, plus you'd get a much stronger generation of engineers from the latter.

> At the end of the day you still need to do some vetting and understanding how code works to effectively use chatgpt. the actual writing of the code was never the hard part of software development

I completely agree with you on that. Most of being a good software engineer is skills that ChatGPT won't help you with.

But you can't even start to learn those skills if you quit in the first six months because of the vertical learning curve tied to all of that syntax trivia.

At the same time, you can't build those skills without spending time understanding how the syntax works. Its much easier to plan projects when you know how they might actually be built. Otherwise you are faffing in the dark and will probably need someone who actually knows these things to hold your hand through the project.

Definitely. And think about all the other ways LLMs can improve quality of life!

In any complex software project with lots of users there is guaranteed to be an effectively endless backlog of bug tickets that are, in effect, abandoned. I think a few months ago some bug got fixed in Firefox that was ~25 years old. In most compilers and frameworks there's going to be a pile of tickets of the form, "improve error message when X happens" that just never floats to the top because programmer time is too expensive to justify working on it. Over time the difference between a senior engineer and a junior becomes not so much intelligence or even actual experience but just the accumulated scar tissue of all the crap we have to wade through to make anything work, thanks to the giant backlogs of bugs and stupid usability problems that never get solved before the product reaches EoL anyway.

For AI to fully replace programmers is going to require quite a few more major breakthroughs, but setting one loose on a bug tracker and asking it to churn out trivial fixes all day is well within reach. That will both make human programming more fun, and easier to learn.

> I think LLMs dramatically impact that initial learning curve. I love the idea that many more people will be able to learn basic programming - I think every human being deserves to be able to use computers to automate tedious repetitive tasks in their lives.

This honestly made me feel so happy. I'm reminded of the average person who is bound by the limitations of the apps they use, the popularity of "How to Automate Using Python" books...

With this new tech, people are no longer bound by that limitation. I think that's pretty cool.

It is the same messy tedious thing with LLMs though. You still have the complex brittle artefact that is code.

LLMs writing code is the beginning, but low or no code is more ideal for most people. With LLM assistance.

Until the LLMs get better.

I just asked ChatGPT a thing, and then on a hunch I asked if there wasn't a built-in function that does the same, and it indeed remembered there is such a function.

What if that second question had been automatically and transparently asked? What if there is a finite list of such "quiet reflecting" questions that dramatically increases the value and utility of the LLM output?

Yes. Thats like a langchain. The only issue then is latency as it talks to itself.