Many, many posts of people looking for help fixing AI-generated code because the AI got it wrong and they have no idea what the code even does. Much of the time the problem is simply an invented method name that doesn’t exist, a problem that is trivially solved by the error message and documentation. But they say they’ve spent several days or whatever going back and forth with the AI trying to fix it.

It’s almost a little sad. If they just take the time to actually learn what they’re doing they’ll be able to accomplish so much more.

Now of course people learning the traditional way have these same problems, but they’re debugging code they wrote, not gobbledygook from an AI. It’s also easier to explain the solution to them because they wrote the code, so it tends to be simpler. Several times I’ve pitied someone asking for help with AI code and even when I explained the solution they still didn’t understand it, and I had to just give up on them - I’m not getting paid to help them.

That's really the money shot, right there.

CEOs have this dream of firing all their "obnoxious" engineers, and "vibe-coding" their own products. That's not something new. People have been selling this dream to gullible C-suiters since I first started coding in Machine Code (1980s).

The future will belong to the engineers that can leverage AI. Engineering is a lot more involved than "HAL, write me a Facebook," which is the C-suite dream.

It's just that engineering will move another level up, as it has, for hundreds of years.

The same applies to software development. If you lack the fundamentals - how memory, I/O, networking, and databases work - you’re at risk of building something fragile that will break under real-world conditions. But for those who understand the moving parts, tools like Cursor supercharge efficiency, allowing them to focus on high-level problem-solving rather than boilerplate coding.

Technology evolves, but the need for deep knowledge remains. Those who invest in learning the craft will always have the advantage.

In this context, AI is just one of many resources you can use - books, websites, SO, etc - to improve your coding. The big differentiator is that you can have a realtime conversation with AI, whereas when talking to other people - be it on SO, IRC, Github, forums etc - you may or may not get a response and it may or may not be helpful. AI tools are a bit more predictable that way.

I'm of the opinion that AI will not replace developers but will be another tool in their arsenal. And part of the skillset of (some) developers will be working with an AI tool effectively. I don't have that yet, but then, I don't know much about Docker / K8S, cloud providers, low level memory management, pure functional coding, Rust, graphics programming etc etc either.

Since AGI does not seem around the corner, coders will be required as ever.

But I would not ignore AI to learn to code. Its great for asking endles stupid beginner questions. And yeah, some answers will be wrong, but my human tutors also taught me some very wrong concepts. But some coding without any help, is likely beneficial for learning.

Because if a lot, I predict that as more published code is generated, we will find ourselves locked in a certain point in history in terms of versions of dependencies.

If its novel code, it's not in its training set.

What LLMs don't suck as much is writing semi readable docs and commit messages.

On the one side, people should write good MR titles for this reason. On the other, sometimes you just don't know, and people's brains are already overflowing with all of the tasks they need to do in order to do their job properly.

But also, finally, it's just a suggestion; we don't have AIs writing our changelog yet, except ironically to make them worse / cringe.