A coder considers the waning days of the craft

In general people are already working at their limits, tooling can help a bit but the real limitation to handling complexity is human intelligence and that appears to be mostly innate. The people this replaces can’t exactly skill up to escape the replacement, and the AI will keep improving so the proportion being replaced will only increase. As someone near the top end of the skill level my hope is that I’ll be one of the last to go, I’ll hopefully make enough money in that time to afford a well stocked bunker.

I don't really know what "value" means in a post scarcity world. We're probably going to have to rethink it.

It made a lot of sense when we were all worried about the same things, e.g. not starving. In such a world, anything you could trade for food was objectively valuable because you could use it to fend off starvation--and so could everybody else.

But if efficiencies improve to a point where we can easily meet everybody's basic needs, then the question of whether progress towards a particular goal counts as value becomes less clear, especially if it's a controversial goal.

I imagine that whether we write the code or not will have more to do with how we feel about that goal and less to do with how many shiny pebbles we're given in exchange.

I’ve spent a long time in the public sector digitalisation in Denmark and where every other “no-code/low-code” or whatever you call the tools that claim to not require programmers have failed miserably GPT is succeeding. Yes, yes, I know some of you sell these tools and some of you have even been very successful in that effort but in my anecdotal experience from 98 municipalities, it’s never once worked, not for long anyway.

By contrast we now have digitally inclined employees creating and automating things with the help of CharGPT. Much of it is terrible in terms of longevity the same way the previous RPA or workflow tools were, but unlike those, people can now also maintain them. At least as long as you keep the digitally inclined employees onboard, because they’re still not software developers and things like scaling, resource usage, documentation, error handling and so on isn’t being done. But it could be, at least for around 90% of it which will frankly never really matter enough to warrant an actual software developer anyway because it mostly “frees” a few hours a month through its automation.

But with this ability, and the improvements in things like SharePoint online (and likely it’s competition that I don’t know about) a lot of the stuff you’d need either staffed software developers or external consultants to handle, can be handled internally.

This isn’t the death of software engineering as such. Like I said, it doesn’t scale and it’s also going to create a bunch of issues in the long term as more and more of this “amateur” architecture needs to function together, but at the same time, if you need to Google how to get some random lines of text from a dictionary, then I’m not sure you aren’t in danger either. And I really don’t say this to be elitist, but everything you google program can be handled fairly easily by GPT and “good enough” that it’s simply going to happen more and more in our industry.

If you look into my history you’ll see that I’m both impressed and unimpressed by LLMs (well GPT, let’s be honest the others all suck). This is because it really hasn’t been able to help us develop anything in our daily work. It writes most of our documentation, and it’s scary good at it. It also does a lot of code-generation, like auto-generating types/classes/whatever you call them from Excel data mapping sheets + CRUD functionality. Sure, we did that before by writing some short CLI scripts, but now GPT does it for the most part. So it’s not like we don’t use it, but for actual well designed code that handles business logic in a way that needs efficiency? Yeah, it’s outright terrible. Maybe that will change over time, so far it’s not improved in the slightest.

But look at our industry as a whole. I know a lot of HN users work in American Tech or startups, but in the European non-tech Enterprise industry and the massive IT and consultant industry supporting it, there are a lot of developers who basically do what GPT excels at, and as these tools get better, we’re frankly just going to need a lot fewer software developers in general. Most of those people will likely transition into other jobs, like using GPT, but many won’t as other professions start doing their coding themselves.

What worries me the most, however, is that we still teach a lot of CS students exactly what GPT is good at. I’m an external examiner for CS students at academy level, and GPT can basically ace all of their curriculum because it’s mainly focused on producing a lot of “easy” code for businesses. I’m scared a lot of those students are going to have a rough time once LLMs really pick up, unless the curriculum changes. It won’t change in time though, because it’s already been sort of “outdated” for a decade because of how slowly our higher educations adapt to the real world here in Denmark.

The need for software far outpaces supply, I agree that improving coder productivity with AI can only be a good thing.

A lot of this article and many of the comments here don't really comport with my experience programming and designing programs. Many or all of the examples in the article seem like toy programs meant to do something relatively straightforward/simple with loose constraints, but in a domain or using tools unfamiliar to the programmer. However, many programmers find themselves in the opposite situation: using tools they're familiar with to solve complex problems with hard constraints. It's in that kind of situation where I've found that GPTs aren't much of a game changer.

Many of the top comments voice a hated of programming--that programming gets in the way of creating. For a certain set of problems I completely agree (like why is making a website so damn complex), but for many of the problems I work on there are a wealth of good, helpful tools and APIs such that the writing of the code melts away and I'm left with the intellectual challenge of organizing my thoughts and thinking creatively. To me, the article and some of the top comments tell me more about the problems they choose to tackle than the act of programming itself.