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> Sure, we're all more productive now, but…

I’ve been trying to ask people a different question: sure, we’re more productive now but to me, the AI era is only serving to plunge us deeper than ever into producing more, more, more, faster, faster, faster. And for what? What’s it all for? I became a software engineer because I have a lot of fun writing code, thinking through and solving complicated problems, and experiencing the reward of seeing what I’ve built by hand working for the first time.

Do people really have fun managing a fleet of agents that generate the code instead? Or is it just the rush of producing something extremely quickly, much more quickly than you might be able to alone, regardless of how well (or poorly) it might work? For me, being able to move quickly was never the fun part.

It’s one thing to utilize AI to lessen the drudgework, the boilerplate, but I look at people who have gone all in on agentic development and it just really makes me wonder.

I use Ai to remove large amounts of code from our code base. Do refactorings that would not have made business sense before.

I also use Ai to be more ambitious. Online evaluation for our in app flows instead of offline.

So for us the entire quality of the product has been increased a lot.

2 types of people:

People who use coding as a means to an end, producing a product

People who enjoy process over product and coding is the enjoyable part, not the end product

Company executives fall into bucket 1. Even if you love your cushy air-conditioned job, doesn’t mean the people above you don’t see you as a means to an end, a better product.

Solo founders and small startups are in bucket 1 as well but that doesn’t mean that don’t enjoy coding, just the product being made is much more satisfying.

The difference is about slop tolerance not "process over product".

Brother, there was slop before AI and slop after AI.

Pre-AI slop got a pass because the creator probably worked tirelessly to make it and that process gave it value.

Post-AI slop get criticized because AI can create it so fast and easily.

But the builder has not changed. Because the builder knows that the product depends on iteration and polish. And knowing what to iterate and what to polish requires intuition and taste. And thats the thing about taste, its forever fleeting. What we think is AI slop, was actually novel and coveted at a point before AI existed.

Yea, you can create code slop much quicker these days. That much is true.

Whether the demand will match the supply is still an open question. Did the apple app store need another 4,000 to do apps? I guess we'll see.

I think that’s a false dichotomy. I enjoyed coding but was more interested in the problems code could solve. Both were really important facets of the job. When I was a chef, I loved being creative with flavors and techniques, and giving people a new favorite aesthetic memory to file away. Losing one of those things would make the job not worth it to me even though I enjoyed both.

Great point. I learned to code to solve a problem and fell into love with programming as much as the product building. Now the first part is gone and I’m forced to decide which was more enjoyable.

I do think food is a bit different. With software and businesses, the end product keeps on giving and can be forever changed. For food, the process is many times longer than the actual eating the food part.

> I’ve been trying to ask people a different question: sure, we’re more productive now but to me, the AI era is only serving to plunge us deeper than ever into producing more, more, more, faster, faster, faster. And for what? What’s it all for?

Many devs here have stated that the fun part for them is seeing the end product, not the act of creating it. Using AI is an act of need satisfaction.

Unfortunately, cloning a GitHub repository or downloading a Squarespace template doesn't hit the spot, because you can see exactly where the code came from, so your brain knows you were not the one responsible. AI's greatest feature is that it obfuscates provenance. You can now happily clone that repository or download that template without the feeling that you're cloning someone else's repository or downloading someone else's template.

> AI's greatest feature is that it obfuscates provenance.

maybe because people see AI not just as a clever packet manager, but also, to some degree, as a problem solving engine. Similar to humans.

It is why I feel dirty after AI generates a piece of clever code: I know I am stealing somebody's IP without attribution. And the AI companies benefit from this, not the real people behind the training data.

> producing more, more, more, faster, faster, faster. And for what? What’s it all for?

If you wanted a literal answer, it is to accelerate revenue as much as possible to make the very rich people who own most of the company even unfathomably richer. No benefit to you for making more faster. Other than the burnout, that's all for you to enjoy.

Many developers became developers because of the paycheck, but they never particularly enjoyed the job, so if instead of working they can twiddle their thumbs waiting for the agent to make attempts at fixing their ticket, they prefer it that way.

I can clearly identify this kind of developers at work by their mindless enthusiasm for AI. Development is just another job before they can move into "management" and make all-knowing statements all day long.

*ask AI to write all-knowing statements for them :D

Please stop saying we - because many of us didn't ever desire or contribute (outside of having our code / data / IP stolen) to these models or the companies developing them. Many of us weren't willingly singing up to use AI - we were essentially forced to by our employers. Not everyone is more productive now because of AI - many people spend the extra time they save writing code, reviewing code produced by AI.

Yep. My job was code review heavy before AI. Now it's even worse because I can't even trust that the developer understood what they were "developing", so I have to be even more vigilant. I may have to institute a "prompt review" process for some.

> We were so spoiled. We got fat salaries to sit in air conditioned Herman Millers all day learning about computers. Now we discover a way to synthesis intelligence and the only thing we can think to do with it is ruin the most fun career most of us could have ever hoped for.

True.

> Who is to say that in 36 months you're not a worse developer over all because that systems knowledge starts to atrophy too?

I think that would be the best case scenario for a lot of developers. It’s not going to make anybody’s life easier. The labor market and job expectations are morphing to absorb any increase in productivity already, and we will all be forced to produce more and more and more to keep our jobs. Demand can’t instantly dramatically increase to meet the productivity, so it’s not like companies can just sell more— people will get laid off. More and more people will be fighting over fewer and fewer jobs, so the people who are still employed will get paid shit. It’s a basic supply and demand equation.

I wonder how many fewer people that told me “well my job isn’t going to be affected because it’s too complex/specialized/etc” in 2024 would say that today?

Companies must either double down on increasingly exorbitant per-token pricing and reduce payroll to compensate, or decide the tradeoffs aren’t worth it, and double down on human intelligence. I think the economics of the industry are going to decide for us in the coming months.

if computers themselves are bicycles for the mind, LLMs are cars. or even motorcycles, if we talk smaller models.

- they require specific roads being paved for them. for example, if your tooling is proprietary and not accessible from the CLI, your agent is pretty much fucked. if your tool is not represented in training data (think, `jj` VCS or your proprietary/tailor-made tooling), you require duct tapes such as "skills" and "memories". a bicycle (that is, your own mind + computer) handles such off-roads much better.

- they get you from A to B faster, sure, but along the way you may encounter something curious - a different road to take, an interesting vista. not to mention, bicycles are actually good for your health, and professional drivers suffer from all the sedentary job diseases we programmers do, unless they actively counter it. with LLMs, we get a "sedentary job disease" of skill atrophy, on top of all the other atrophies us coders should counter with a proper exercise set at least three times a week.

- finally, when you crash in a car (Opus/Sonnet, GPT-5.5) or, worse, on a motorcycle (smaller Qwens, DeepSeek, Haiku/GPT-5.4-nano), you crash very loudly and with a high chance of irrecoverable casualties.

There's one more: The "bicycle for the mind" analogy was one Jobs chose specifically in reference to the fact that a human on a bicycle moves more efficiently than a human on foot—or any other land animal for that matter. But it's still the human's own effort that propels the bike. Motor vehicles require an external energy source, the human only directs it. Similarly, with LLMs, it's no longer the user's own effort that's doing the thinking.

> There's one more: The "bicycle for the mind" analogy was one Jobs chose specifically in reference to the fact that a human on a bicycle moves more efficiently than a human on foot—or any other land animal for that matter.

One of the canonical references of Jobs’ use of “bicycle for the mind” also compared the efficiency of locomotion to the California Condor which was (I’m working from memory, here) 17X more efficient than a human walking.

A human on a bicycle, according to Jobs then, is more efficient than the most efficient animal locomotion known to humankind. The comparison included animals moving through non-terrestrial environments.

The bike/motorbike/car analogy is good. In each you can find enjoyment that suits your character.

I have been drawn to coding from the first day I took a course at college learning Pascal and assembly on an IBM PC. Hell I even wrote an IEEE/488 driver for an Osborne 1.

As an experimental physicist, coding was always central to my work. I always felt guilty because I had more pleasure coding than tackling the physics itself.

This is a new age we are entering. AI changes how we do things, but I believe that the human passion to be creative and do intellectual work will always be part of it. It's in our nature.

So I'm not worried that we'll all dry up and turn into zombies.

And, like cars, our federal/state governments are lighting astronomical amounts of cash to subsidize the infrastructure that makes them operate at the scale they currently operate at.

Just one more ~~lane~~ datacenter, bro. That'll fix it; trust. Please. One more ~~lane~~ datacenter. It'll be so good.

You're either using it wrong, or work somewhere that sucks. I'm having a ton of fun coding with AI.

I feel like I am learning a whole new branch of the programming skill tree. LLMs and their harnesses are like a mew set of constraints to work around when designing systems, but if you get them right you can build bigger, better things than ever before.

I say all of this as someone who spent the last two days rebuilding RBAC for my application after Claude royally messed it up.

What's an example of "bigger and better" and what projects did you have before?

I attempted to build a K8s based image catalog and management system a few years ago, and progress was very slow. Took 2 months to get the first vaporware demo put together.

This year I'm building and IoT data management platform and I've already built two demos of the product and am adding a bunch of features for a third. Nothing is vaporware about it. All in about 4 months.

The big wins have been system config, debugging, and exploration. I was able to build an Arrow Flight SQL backend to use as an interface and try it out with some use cases, decide it wasn't going to work, and replace it with something else, all in about two weeks. Would have taken far longer before, if I would have been able to do it at all. I knew nothing about Flight SQL before trying it out.

I shit you not I have been told to "stop trying to understand it, just make sure it works" when mandated to use LLMs at work, like the absurdity of that statement isn't self-evident.

Needless to say I have been looking for a way out of this job (and likely career) ever since.

What's going to happen is people who give a shit are going to get filtered and self-select out of the job, and then the entire field is going to be dominated by dunning kruger AI maximalists. The "AI will replace engineers" is true, but for an entirely different reason and entirely different way than most people making that argument think.

You (and many others) have become a "reverse centaur" [0]. AI has been forced on you and reduced you to little more than a button pusher.

[0] https://pluralistic.net/2025/12/05/pop-that-bubble/#u-washin...