Quote of the main point in the article:

    In other words, the hard part moves from recall (“How do I write this?”) to judgment (“Does this actually make sense?”)

This is very true. But to evaluate if it makes sense, you first need experience writing the code. I am glad I learned software development over 15 years ago, and not today. AI is a super power, but without the experience to guide it, it can go horribly wrong really quickly.

Definitely not my experience. No matter the model, if I'm working on something important (and there is little reason on working on something not important) I do care about correctness and understandability. While LLMs are great for throwaway one-time code (although that's also debatable), they cannot compete with code written by a seasoned professional. No matter how many times I've tried delegating writing code to LLMs I've always regretted it in a few months' time, because it is more buggy and I don't really know what is happening there.

The future is using LLMs for what they are good for. What that is still being found out. I've had great experience with LLMs reviewing the code (matches with Primagean's ~50% accuracy at finding bugs, which is really good) and for explaining unfamiliar concepts to me.

I firmly believe that the code itself needs to be 100% organic, and if it's not and you're relying on LLMs to generate tons of code, you haven't built enough abstraction to make it unnecessary.

It’s the same with writing: AI writing is coherent on the surface, but is impossible to edit because it’s built on no real insight.

Now the sharpening of a coherent point, challenging one’s assumptions, and editorial decisions of what (not) to include are super important because they’re no longer a byproduct of the writing process.

I am looking at the subtitle:

The future of software development will belong to those who can think clearly at scale, maintain durable mental models amid rapid change, and integrate machine-generated output into human-directed intent.

Wasn't this always the case? Maybe I just take this for granted because I am dumb Army guy and this is the only lens through which we dumb Army people see the world.

Whenever the subject of AI comes up in connection to programming it feels like the conversation always misses the human element. When you look at this only in terms of human behavior I am not seeing anything new with AI.

Maybe, its because I write in JavaScript and maybe its different in other areas of programming. In JavaScript it has always been a race to the bottom. The product is never the goal. The goal is always hiring and regarding code as a commodity that is designed to fail elegantly and frequently. So, when I look at AI writing code for developers I can't help but ask: What's different? Isn't that why Angular and React became popular, because they abstract away writing code?

It's somehow more tiring, reading complex plans in response to your guidance, and then making decision after decision. Reminds me of this Alan Watts bit...

A farmer who ordered a farmhand quickly discovered he was an extraordinarily efficient worker.

The first day, he put him on sawing logs, and the farmhand sawed more logs than anybody else, ever. It was fantastic — but the wood-cutting work was all done in one day.

So, the next day, the farmer put him onto mending fences. There were all kinds of broken fences around the farm. And, again, the farmhand had all the work done in one day.

So the farmer thought, “What am I going to do with this guy?”

The next day, he took the farmhand to a basement and said, “Look, here all the potatoes that have come in from this harvest. I want you to sort them into three groups: those we sell, those we use for seeding, and those we throw away.”

He left the farmhand to it. And at the end of the day, the laborer came back and said, “Well, that’s enough, mister, I quit.”

“Oh,” the farmer replied, “You can’t quit. I’ve never had such an excellent worker. I’ll raise your salary — I’ll do anything to keep you around me.”

The farmhand said, “No. It’s all right mending fences and chopping wood, but this potato business is decision after decision after decision.”

I agree with this, but I'd add that good judgment comes from experience. Before you can evaluate whether AI-generated code makes sense, you need to have written enough code yourself to recognize the trade-offs and failure modes. AI is an incredible productivity multiplier, but it can also make it much easier to move quickly in the wrong direction without even knowing that you are moving in the wrong direction

I always find it hilarious when these opinion pieces about the impacts of AI are AI-written (as is almost certainly the case here, a major trend in ACM and IEEE publications). Like, really? An LLM has a breadth of experience managing AI, and can recall it, and explain it to humans?

This article will apply for about 3 months until AI advances again and the assumptions made are no longer true.

You can't take a rapidly developing field and pretend progress is going to freeze at its current development level so you can decide how to handle it.

It's a coping mechanism to deal with rapid change by pretending change is going to stoo right here right now and you can get a handle on it.

How many times can we have the same discussion.

I am tired of all these AI is so smart vs AI is not so smart. AI is a tool. It is like CNC machine tools or robotics in manufacturing.

How's about a test? Put all the smart AI researchers/developers onto an airplane that its software was entirely created by AI. Now tell that airplane to travel around the world with airborne refueling and land at an airport. When will this happen and how many of AI advocates will get on this autonomous airplane?

The convergence is ongoing. We are Borg. You will be assimilated.

AI merely reduces the difficulty of coding, without directly increasing the difficulty of architectural judgment. It merely brings to light the actual difficulty of this task. Moreover, I believe that in the future, AI will also possess certain architectural judgment capabilities. However, the cost of such AI might even be higher than that of humans.

> Code becomes only one representation of thought among many overlapping ones.

This is wrong, code is the concrete "truth" being executed, the rest (plans, prompts, agent instructions) are just temporary artifacts used to generate the code. What's left is the code alone.

LLMs don't have any semantics, they can't execute anything with 100% certainty. So far programming languages are the only langugues that can do that.

Since rise of AI u haven't touched single line of code. Even though I know AI isn't good enough still in many areas, I cannot find the energy to invest in programming with writing code.

Also, the need to move with speed is an exercise in self control so you don't cut corners and accept code without really look at it. There are so many times when I catch really blatant stuff that if not caught would be over engineering, wrong engineering, hacks, logic code copies without reuse etc etc.

we automated the easy part of programming and it turns out the easy part was the fun part

It's true that there are new skills to acquire (and that those with talents for the old skills may be less talented with the new skills).

It's absolutely not true that it "just" moved the difficulty around. If that were true then I'd be just as well off continuing to use my decades of programming expertise just as I always have; but the reality is I can get more done, and get better work done (depending on level of vibing), than ever before.

Thing is, though, making programming easier doesn't mean programmers will work less hard. That's how competitive markets work. LLMs made programming easier. Capitalism prevents workers from capturing that value.

It can be both at the same time - easier and different.

Oh finally my ADHD will pay for itself! I waited for so long!

I don't think I write or read or code anymore, bar prs from juniors or senior colleagues wanting a review.

I didn't think it would work just 6 months ago, but reality is that at this point AI writes better code than me and I'm not the average developer, but someone who loved the craft and was good at it.

Lots of effort was required to get the repositories to a good level, best practices, documentation, etc, but reality is that once you do that and have strong rails most of your work is having it to write a plan focused on business logic, review it, have it derive an implementation plan, review it and then it's mostly on its own.

Codebases have never been healthier, cleaner, better documented, consisted and thoroughly tested as they are now. There was just no spare time and mental energy to bring them there before, now there is and experimenting to get there was cheap.

Needless to say I no longer enjoy the job anymore and thinking of changing domain. I loved tinkering about implementation details, etc, but the job nowadays is more of qa and architectural design than writing or reviewing code.

It's way easier. People don't need to read code anymore, nor will they have to care about building mental models about the system as this article suggests.

The way to think about coding agents is that a good one should in theory literally replace the developer entirely. No, a whole organisation of developers.

In theory a product owner should just be able to dictate how they want to product to function at a high level and the AI should take care of the rest in the same way a human programmer or team of programmers would have in the past. If there are conflicts in what's being requested, then the AI should be able to recognise that and ask for production direction.

As always with every generation of AI people seem to way over index on the now.

- "They're good for autocomplete, that's about it"

- "They're good for quickly mocking up small functions, but they make a lot of mistakes"

- "They're good for scaffolding some parts of the system if you're good at prompt engineering"

- "They're good at writing most of the code, but humans will always need to do the last 10%"

- "They can write all of the code, but humans will still need to architect the system"

You are here. Perhaps this is where progress stops. I wouldn't bet on that however.

AI is making programming an irrelevent field.

Tackling software architecture is not programming, that is architecture. They're called different things for a reason. It is now easier to write working code via AI. Anyone that can type can do it. The syntax (language) barrier is fully removed. I'm done with syntax, looking up the new right way to do things, etc. It works via prompting. Tell it what to write and it comes out the other end with a working program. That's programming, and that's not an opinion. This alone makes it easier to program.

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