One thing that has always worried me about AI coding is the loss of practice. To me, writing the code by hand (including the boilerplate and things I've done hundreds of times) is the equivalent of Mr. Miyagi's paint-the-fence. Each iteration gets it deeper into your brain and having these patterns as a part of you makes you much more effective at making higher-level design decisions.

A retort you often hear is that prior technologies, like writing or the printing press, may have stunted our calligraphy or rhetorical skills, but they did not stunt our capacity to think. If anything, they magnified it! Basically, the whole Steve Jobs' bicycle-for-the-mind idea.

My issue with applying this reasoning to AI is that prior technologies addressed bottlenecks in distribution, whereas this more directly attacks the creative process itself. Stratechery has a great post on this, where he argues that AI is attempting to remove the "substantiation" bottleneck in idea generation.

Doing this for creative tasks is fine ONLY IF it does not inhibit your own creative development. Humans only have so much self-control/self-awareness

There are many time when I’ll mull over a problem in my head at night or in the shower. I kind of “write the code” in my head. I find it very useful sometimes. I don’t think it would be possible if I didn’t have the language constructs ingrained in my head.

Many analog to this IRL:

1) I can't remember the last time I write something meaningfully long with an actual pen/pencil. My handwriting is beyond horrible.

2) I can't no longer find my way driving without a GPS. Reading a map? lol

Soldering transistors by hand was a thing too, once. But these days, i am not sure, if people wanna keep up anymore. Many trillions of transistors later. :)

I like this zooming in and zooming out, mentally. At some point i can zoom out another level. I miss coding. While i still code a lot.

"Every augmentation is an amputation" -- Marshall McLuhan

Generalize this to: what's it going to look like in ten years when the majority of our society has outsourced general thinking and creativity rather than practicing it?

They want you to become an expert at the new thing: knowing how to set up the context with perfect information. Which is arguably as much if not more work than just programming the damn thing.

Which theoretically could actually be a benefit someday: if your company does many similar customer deployments, you will eventually be more efficient. But if you are doing custom code meant just for your company... there may never be efficiency increase

Especially concerning in light of that METR study in which developers overestimated the impact of AI on their own productivity (even if it doesn't turn out to be negative) https://metr.org/blog/2025-07-10-early-2025-ai-experienced-o...

I still do a lot of refactoring by hand. With vim bindings it’s often quicker than trying to explain to a clumsy LLM how to do it.

For me, refactoring is really the essence of coding. Getting the initial version of a solution that barely works —- that’s necessary but less interesting to me. What’s interesting is the process of shaping that v1 into something that’s elegant and fits into the existing architecture. Sanding down the rough edges, reducing misfit, etc. It’s often too nitpicky for an LLM to get right.

What worries me more is the steep decline in code quality. The python and javascript output I've seen the supposed best LLM's generate is inefficient, overly verbose and needlessly commented at best, and simply full of bugs at worst. In the best case they're glaringly obvious bugs, in the worst case they're subtle ones that will wreak havoc for a long time before they're eventually discovered, but by then the grasp of the developers on the codebase will have slipped away far enough to prevent them from being compete t enough to solve the bugs.

There is no doubt in my mind that software quality has taken a nosedive everywhere AI has been introduced. Our entire industry is hallucinating its way into a bottomless pit.

My LLM-generated code has so many bugs in it, that I end up knowing it better since I have to spend more time debugging/figuring out small errors. This might even be better: you learn something more thoroughly when you not only practice the right answers, but know how to fix the wrong answers.

Doesn't worry me. I believed AI would replace developers and I still do to some degree. But AI is going to lack context, not just in business domain but how it would intersect with the tech side. Experienced developers will be needed. The vibe coders are going to get worse and will need experienced developers to come fix the mess. So no worries, the only thing that would suck would be if the vibe coders earn more money and experienced hand crafting devs are left to pick up the crumbs to survive.

Tangent, there was this obnoxious effect for typing in editors the characters would explode, makes me think of a typewriter as you're banging away every character for some piece of code.

I imagine people can start making code (probably already are) where functions/modules are just boxes as a UI and the code is not visible, test it with in/out, join it to something else.

When I'm tasked to make some CRUD UI I plan out the chunks of work to be done in order and I already feel the rote-ness of it, doing it over and over. I guess that is where AI can come in.

But I do enjoy the process of making something even like a POSh camera GUI/OS by hand..

Do you write a lot assembler, to make your note effective at higher level design?

I'm concerned about this also. Even just reading about AI coding, I can almost feel my programming skills start to atrophy.

If AI tools continue to improve, there will be less and less need for humans to write code. But -- perhaps depending on the application -- I think there will still be need to review code, and thus still need to understand how to write code, even if you aren't doing the writing yourself.

I imagine the only way we will retain these skills is be deliberately choosing to do so. Perhaps not unlike choosing to read books even if not required to do so, or choosing to exercise even if not required to do so.

Along the same lines, its probably little more than that. When it comes to software development, every iteration of execution/design is supposedly either faster or better based on the prior learnings for things that you have done by urself or observed very carefully.

I’m concerned about becoming over reliant on GPT for code reviews for this reason (as I learn Rust).

My practice in writing assembly is so lost by now that it's not much different than if I never learned it. Yet, it's not really a problem.

What is different about LLM-created code is that compilers work. Reliably and universally. I can just outsource the job of writing the assembly to them and don't need to think about it again. (That is, unless you are in one of those niches that require hyper-optimized software. Compilers can't reliably give you that last 2x speed-up.)

LLMs by their turn will never be reliable. Their entire goal is opposite to reliability. IMO, the losses are still way higher than the gains, and it's questionable if this is an architectural premise that will never change.

The "paint-the-fence" analogy is spot-on, but AI can be the spotter rather than replacement - use it for scaffolding while deliberately practicing core patterns that strengthen your mental models.

I don't get this with boilerplate. To me boilerplate code is the code that you have to write to satisfy some predefined conditions that has little to do with the semantics of the code I am actually writing. I'm fine with AI writing this stuff for me if it does it reliably, or if the scale is small enough that I can easily spot and fix the errors. I don't see that aspect of coding to be much more than typing.

On the other hand I do a lot more fundamental coding than the median. I do quite a few game jams, and I am frequently the only one in the room who is not using a game engine.

Doing things like this I have written so many GUI toolkits from scratch now that It's easy enough for me to make something anew in the middle of a jam.

For example https://nws92.itch.io/dodgy-rocket In my experience it would have been much harder to figure out how to style scrollbars to be transparent with in-theme markings using an existing toolkit than writing a toolkit from scratch. This of course changes as soon as you need a text entry field. I have made those as well, but they are subtle and quick to anger.

I do physics engines the same way, predominantly 2d, (I did a 3d physics game in a jam once but it has since departed to the Flash afterlife). They are one of those things that seem magical until you've done it a few times, then seem remarkably simple. I believe John Carmack experienced that with writing 3d engines where he once mentioned quickly writing several engines from scratch to test out some speculative ideas.

I'm not sure if AI presents an inhibiter here any more than using an engine or a framework. They both put some distance between the programmer and the result, and as a consequence the programmer starts thinking in terms of the interface through which they communicate instead of how the result is achieved.

On the other hand I am currently using AI to help me write a DMA chaining process. I initially got the AI to write the entire thing. The final code will use none of that emitted output, but it was sufficient for me to see what actually needed to be done. I'm not sure if I could have done this on my own, AI certainly couldn't have done it on it's own. Now that I have (almost (I hope)) done it once in collaboration with AI, I think I could now write it from scratch myself should I need to do it again.

I think AI, Game Engines, and Frameworks all work against you if you are trying to do something abnormal. I'm a little amazed that Monument Valley got made using an engine. I feel like they must have fought the geometry all the way.

I think this jam game I made https://lerc.itch.io/gyralight would be a nightmare to try and implement in an engine. Similarly I'm not sure if an AI would manage the idea of what is happening here.