It's Beej from the guides! I really appreciated the perspective you put forward here: https://beej.us/guide/bglcs/html/split/use-of-ai.html#ai-and....

> It's still not hard to have more skill than an AI.

Eh, today, maybe, and within specific domains. It's far from certain that this will remain true 5 or 10 years from now. The capability of these tools has improved greatly even compared to a year ago, so it's not far fetched to imagine that they will continue to gain ground.

> Of course AI can solve all the dumbbell problems you get in school. They're just there to build muscle. Robots can lift weights better than you, too, but that doesn't mean there's no value in you doing it.

That's a strange analogy. Technology, by definition, exists to facilitate human work. Relying on it has the opposite effect of "building muscle". "Muscles", in fact, atrophy the more we rely on technology.

Doing the work without technology can certainly be valuable. But it's a personal value appreciated at most by a niche community of people. The actual market value of the work collapses once the product becomes a commodity. This is the effect of "AI" tools on software. The quality of the fast and cheap version of the product is still inferior to the artisan product, but a) this can only improve, and b) most of the market can't tell the difference.

It's so strange. I do all the things you mention and it works brilliantly well 10 times out of 11.

> and found its capabilities to be significantly inferior to that of a human, at least when it came to coding.

I think we should step back and ask: do we really want that? What does that imply? Until recently nobody would use a tool and think, yuck, that was inferior of a human.

I experimented with GPT-5 recently

GPT-5 what? The GPT-5 models range from goofily stupid to brilliant. If you let it select the model automatically, which is the case by default, it will tend to lean towards the former.

I came to the same conclusion after 40+ years of programming: better if you come to that realisation earlier. Still love coding though, but I leave the paid work to my colleagues and llms: I just code for fun these days. I also write for fun and find it pretty similar, feeling and satisfaction wise.

There definitely are times that I lose the "joy of coding" and it has nothing to do with any illusions, it has everything to do with the kind of programming tasks I have to work on. Greenfield projects are the best, tech debt is the worst. Working on fun stuff is just fun.

While there's truth in what you say, I don't think anyone should ever lose feeling for an act of creation.

It is never everything, but it should also never be nothing.

if you not special without it then so be it

This is wise

Code generation tools of today are pretty good at writing the boring boilerplate. I think the author is aware of this.

But what happens when they get really good at generating the not-so-boring bits? They're much better at this than they were a year or two ago, so it's not unthinkable that they will continue to improve.

I'm a firm "AI" skeptic, and don't buy into the hype. It's clear that the brute force approach of throwing more data and compute at the problem has reached diminishing returns. And yet there is ample room for improvement by applying solid engineering alone. Most of what we've seen in the past year is based on this: MCP, "agents", "skills", etc.

> I would code even if I didn't get paid for it.

That's great, but once the market value of your work diminishes, it's no longer a career—it's a hobby. Which doesn't mean there won't be demand for artisanal programming, but it won't power the world anymore. It will be a niche skill we rely on for very specific tasks, while our jobs will be relegated to steer and assist the "AI" into producing reliable software. At least in the short-term. It's doubtful whether the current path will get us to a place where these tools are fully self-sufficient, and it's arguable whether that's something worth aiming for anyway.

This is the bleak present and future the article is talking about. Being an assistant to code generation tools is far removed from the practice of programming. I personally find it tedious, unengaging, and extremely boring. There's little joy in the experience beyond ending up with a working product. The road to get there is not a journey of discovery, serendipity, learning, and dopamine hits. It is a slog of writing software specs, juggling contextual information and prompts, and coaxing a human facsimile into producing working software by using natural language. I dislike every part of this process. This is not the type of work that inspired me to do this professionally. Sure, every job has tasks we sometimes don't enjoy. But once you remove programming from the equation, there's not much joy in it left for me.

Okay I get the desire of not wanting to do repetitive stuff. It appears doing this with an llm scratches your itch. Before the same - focusing on the intrinsic complexity instead of the accidental - could be achieved by using libraries, toolkits, frameworks, better compiler (plugins), or “better” languages.

What plagues me about LLMs is that all that generated code is still around in the project making reviews harder as well s understanding the whole program source. What is in there that makes you prefer this mechanism instead of the abstractions that have been increasingly available since forever?

I've seen a lot change. I used to have a seemingly bottomless list of things we are doing wrong and about half of them have dropped off in the last twenty years. Did they all turn out as well as we hoped they would? No. I don't think a single one did. We are half-assing a lot of things that we used to laugh off entirely. In most of these cases some is better than none, but could be a lot better.

What I worry about is that my list has gotten shorter not because everything is as it should be but because I have slowed down.

Quite a lot of things on that list were of the "The future is here but it's not evenly distributed" sort. XP was about a bunch of relatively simple actions that were force multipliers with a small multiple on them. What was important was that they composed. So the benefit of doing eight of them was more than twice the benefit of doing four. Which means there's a lot of headroom still from adding a few more things.

That's certainly a more positive way to look at this. Working software has always relied on having people who grok the code, and this happens by spending a lot of time thinking about the code while writing it. And it's undocumented, because the nature of it is something you cannot really document.

If AI is writing all the code, how do we keep the quality good? It's so obvious with the current GenAI tools that they're getting great at producing code, but they don't really understand the code.

We don't really know how this story unfolds, so it's good to keep a positive mindset.

What if your boss says you'll be fired if you don't use the LLM for the "fun stuff" too?

What if you go back and discover every path you could have taken is a bait-and-switch?

For most jobs in any field, having a degree is more important than what the degree is in. University is not a jobs training program, it’s a way to build a foundation. Understanding how systems work together can be applied in many areas of business, not just coding.

"If you find coding boring, explore the frontiers. You will find a lot of coding wilderness where no AI has trod."

this, AI is nothing without data set

so if you working in bleeding edge technology where your tools is only have 3 contributor and a way to access them via IRC channel once a day, things get interesting

> AI mostly doesn’t produce adequate quality or correctness for the type of code I enjoy writing.

This assumes that companies care about "code quality" and customers care about bugs.

> If you find coding boring, explore the frontiers. You will find a lot of coding wilderness where no AI has trod.

There are a lot of software engineers and not a lot of frontier.

If you read a story someone else wrote, do you care about writing?

Similar to running a program written by AI, not by you.

The whole promise of AI is that you are not problem solving. A machine is solving problems with as little input and understanding from you as possible. That's the entire promise of AI.

I fail to see how those two are disconnected.

If you are selling "just do it using AI", not that you are wrong, but you fail to understand the loss of years of investment in one self, wiped away one prompt at a time. Not literally, just feels like that.

Problem solving and having the problem solved for you aren't the same thing.