Unlike OP, I want to maintain these couple of projects. I am maintaining these projects. They are getting better daily, and my confidence in them is increasing, not decreasing.
technology has generally flooded us with more speed, more choice, more entertainment - even the introduction of bicycles caused a similar outrage response, that we're moving too fast and should be slowing down to take in the world around us
the paradox is that choice is both great and awful for us
the one skill to hone / develop in the last couple of decades (way before AI) is the ability to focus, filter, discard, and choose a direction to move in (whether its hobbies, career, apps to build, social media to consume, etc etc etc)
I'm wondering whether this is what they call pseudo-productivity: a lot of low-friction back and forth that feels productive, and perhaps even enjoyable, but in objective terms, takes longer?
Never be ashamed of making useless things, the really useful things are hiding amongst them.
If having fun is interfering with your productivity, that isn't necessarily a problem, it is only a problem if it interferes with your livelihood.
If Robots are to take all our jobs, we need to retain our livelihoods. Then we all could perhaps have fun making the things we want to make for the pleasure of making them.
I too have ADHD, perhaps it is different for me because I began medication about the same time the models got good, but I have worked on some individual projects for longer than I could have earlier.
I don't spend all day typing prompts though. It's more of a step in, do a thing, then think about it while doing something else.
I think the answer is simply to not use LLM’s to generate much anything at all. When writing code I only use Claude chat (in separate virtual desktop on a browser) only when I can’t grok the documentation or the bug really kicks my ass. I rarely want it to even write the code, just to explain what I am doing wrong.
When I write the initial idea might be just me having a discussion with Claude (“What exactly was Marcia Williams’ hold on British PM Harold Wilson”) about a topic I am interested in and want a quick overview of the literature, but if I end up writing about it none of it is generated.
Claude just helps me to refine my thinking like a rubber duck that has in its palmate tips most all of information saved online. It is simply an extension of my intellect. The thinking and the work remains my own.
Every time you need to make an update, you need to bring up the old context, or otherwise get the AI up to speed, which especially if you're using one of the frontier models could be a significant financial drain long term.
You don't get the same dopamine hit too, because you're just making boring updates to something which you threw together in 5 minutes with zero effort. The time and financial cost of building all this stuff may have been better spent on one, good, properly architected project.
Maintaining the project manually also assumes you can quickly understand the codebase which has been produced, otherwise you're completely dependent on Anthropic and them maintaining prices which you can afford. Bearing in mind that as you add new features, the cost of getting the LLM to understand the project increases, right? I might have a naive perspective here.
All that being said - sometimes there really are one-off niche things that are just for personal use that you do continue to use long term. Usually the simpler stuff where you can easily grasp the codebase at a quick glance. It's also great for debugging back and forths.
Personally I just run my local setup with a bunch of MCP stuff and the primary way it helps me is to keep me functional and on task. In some ways it's good if the AI can supervise you as opposed to you supervising it - at least from an ADHD perspective.
It's an interesting idea for sure, I like this article and agree with it.
This part reminded me of a recent article and it’s interesting that he brings up ADHD because that’s probably the bigger issue then. Because what I got from the article and the related conversation, specifically the top comment:
> > Sometimes, tools don’t move the needle because there’s no needle to move.
> It reminds me of something my old CS mentor, now elderly, had said about LLMs a few months ago: "it's a force multiplier, but there has to be some force to multiply."
From: https://news.ycombinator.com/item?id=48254336
The fact that it turned out that “Human Bottlenecks” post was written by the same person who wrote “Notes on Managing ADHD” which I had printed and studied for tips not that long ago made sense.
So, to connect the dots, the fact he made all of those things without them being part of a bigger plan is, I think, the problem. In the framework of the above quote, there’s no needle there, nothing to multiply.
I’ve been trying to think more about whether what I’m doing is going somewhere, or if I can skip it and simplify things.
Then, I've built a keyboard for myself and I'm still using it. I liked the process and started to build them basically for giveaway. My hope was that it will help people who eager to switch to ergonomic keyboards but the bar is too high for them to build, to figure out things etc.. But it turned out that people who get it without this effort they just try, fail, and leave it dusting on the shelf. They lack commitment, nothing fuels their enthusiasm.
I have zero interest in AI note-taking apps. I write notes for myself to process the meaningful outcomes of a meeting. My notes are short, only capture stuff I actually think I will care about in the future, and after I've written them I have a better mental model of the meeting than I did before.
If I gave the task to an AI, no matter how advanced, it would produce much more unfocused content than the focused notes I am used to writing, and I would lose the process of synthesis that helps me absorb the meeting outcomes. More work product, but actually less productivity.
Nothing different from all innovations.
"Because the effort was removed, so was the commitment, and with the commitment the focus, and with the focus any meaningful product at all."
This is the truth. Otherwise known as "easy come, easy go".
Also, if nobody uses them, they don't need to be maintained. You can shut them down with no regrets.
'Waiting for AI to finish' - even if it's only 1 minute segments, is real, especially if we are delegating. (Maybe I'm interrupted right now!)
But this - it's not the fault of the tool that you're not focused on building something useful, long lasting or material.
That's an entirely different question - and I think if you look into most people's 'experiment' folders, that tendency was always there. Just more code now.
That's on us.
https://www.tyleo.com/blog/the-terminal-star
A lot of good comes out but it can be hard to separate from the parts that just take advantage of your brain.
I've never made more awesome things. And those "things" now matter less to the outside world than they ever would have before.
That sorta sucks. Emotionally as well as financially.
buts its a refreshing that there is an initial list of half baked projects, i suppose meant to evoke horror at the untidiness and wasted time. but honestly each of those projects sound cool as hell. not necessarily durable - but who cares. i’d argue there is a skill, one that is different than traditional programming, that the author was building up over that period.
discipline is important. focus is hard. but allowing yourself to play is not a bad thing at all and i dont think building little interesting side projects should be a shameful act.
He always asked me to help him build this app and that app and thinks his ideas are million dollar ideas. He has ADHD.
Surprisingly, he really loves LLM. He doesn't care that LLM destroys knowledge worker bargains by stealing work without compensating the original authors. He doesn't care that LLM uses a lot of energy. He doesn't care that LLM will concentrate money in the hands of the few. He doesn't care that the Pope has a crusade against LLM. For someone with humanist tendencies this seems to contradict his beliefs.
All he cares is, "I can make apps now and my 5 year old kids are making games by prompting, and we can make money using this, those who don't will be left behind, including you".
In other words, the issue isn’t the AI subscription, it’s the ADHD.
When friends start dying within 10 years of your age, it's a hell of a wake up.
"I wish I'd made more throw away apps I never use" ... said no one on their death bed, ever.
This is like a kid playing videogames instead of studying, you take the console away and force the kid in front of a book and the kid will spend most of his time looking at the wall and dreaming.
I am engineer with very deep programming background that have managed people, with real experience in the real world.
One of the best things about AIs is that you can test crazy ideas and create prototypes very fast. Only one in a hundred will work great in the real world, but you have to create the 100 before to know.
Creating the 100 before AI was extremely expensive, and took so much time.
For me it is liberating and gives me focus because I can spend so little time testing prototypes and spend real time in what is really important and works.
This is something I learned from game developers: If you are going to create a game, you spend a weekend testing the dynamics and the gameplay of your prototype to know if is is fun. You use boxes, no textures, no complex sounds of music.
Then if it works and is is so fun, you create the game! You can spend 2 years creating the game after that.
You don't spend two years doing a Game only to realise later that is not fun, and you either spend 3 more years or abandon it at this moment.
Perhaps at a population scale AI inhibits people from finding fulfillment.
But on an anecdotal basis, "just go find something meaningful". For some of us that "hate the AI timeline", we are still finding purpose and fulfillment by applying AI toward our personal missions.
In my day, when there's something that is distracting me from moving my objectives forward, I'm asking "Can AI help me automate this?" The answer is surprisingly often "yes". I call these "rough edges" and have been doing a lot of work over the last few weeks to "file the rough edges down".
What a strange perspective. His dismissal of the long list of projects at the top is also odd.
What's wrong with making something cool and functional (if not "useful"), even if just for yourself, without any profit motive or plan to turn it into some huge business?
I spent the last weekend vibing some plugins for Quod Libet -- a custom bookmark/preview function, a click-to-jump lyrics sidebar, thinking about a search-within-lyrics thing now. It all works beautifully, but I have no illusions about it being some kind of moneymaker -- heck, I doubt it's even worth the time beautifying/minimizing the code to get it acceptable to submit to the Github. But it makes me happy and makes using my library more enjoyable. Isn't that enough? Do they go around asking garage tinkerers and hobby crafters what their marketing plan is, too?
Some really good points on how these bots are incentivized to reward mindless engagement though and the bit about voice transcription not producing useful writing landed. When the barrier to release drops the quality naturally does too.
I think the next stage of us learning to harness these tools is us building the ability to reach for excellence even when we are not required to. To accustom ourselves to going beyond minimum viable bar for functionality and to reach for qualities or standards beyond that which the AI brings to the table unaided. A new kind of engineering rigor.
I move that this was always true and is now only far more so.
This what they have been spending their human tokens on: https://killedbygoogle.com/
They are a decreasing quality searching engine who shows ads. It has never been about intelligence, or lack of resources. Its about incentives and execution.
Your AI wont save you, or make you rich or increase your productivity.
You make this sound like a bad thing. ADHD isn't always about attention deficit, although it is right there in the name. It's more about attention dysregulation. For those of us prone to hyperfocus, working with AI can provide the kinds of stimulation we crave. I can hardly remember a time when I've felt more engaged with my work, more productive, and more badass.
I actually enjoy the collaborative programming process, and was pair programming with folks before the term was coined. At the end of the day I have the satisfaction of browsing the pretty, readable, DRY, maintainable code we end up with after rounds of refactoring and back and forth. I have always employed linters and code formatters, and this is no different, and my standards are still the same. I yell at the clanker about code duplication, hard-coded assumptions, tightly coupled logic, and in the end, while I don't understand the details of every algorithm, I really understand what we've built and the architecture we've designed.
And they get to convince people to pay them to give away their most intimate nontraining data and secret ideas to a for profit entity.
I think the biggest difference is that I no longer care about what people think about me and how I am perceived, so the motivation to publish my work went down to near zero. I used to build open source stuff, I no longer want to spend time on preparing stuff for publishing, making it available, dealing with people who will inevitably want something of me eventually. There just isn't enough time.
I can still be baited into responding on HN for some reason, and I am trying to work on that, because that is the ultimate waste of time.
My younger self was always excited when the latest tech came out, when the latest MSDN arrived, etc. But the last 15 or so years, I totally lost interest. I still love writing code but the desire for the latest and greatest had fade.
These LLMs were dogshit for a while, but I would keep returning to them.
Now I am excited again.
I work on a large web project with lots of legacy that is slowly being rewritten and copilot and codex are helping a lot by first writing tests for the old code, and then converting to the new.
I thought we'd never finish, but now I can see how we can do it.
It's brought a bit of the fun back into the game.
If you optimized for minimizing deathbed regret perhaps you'd regret that on your deathbed!
If I have cogent thoughts on my deathbed I expect they'll be along the lines of "I wish I wasn't dying" and not regretting the many ways I enjoyed my time on Earth (which includes vibe coding apps nobody uses).
That does happen on occasion, the commonly-cited example being Half-Life. How awesome would it have been if the Valve team hadn't had to waste so much time, money, and personal energy on their initial failed prototype?
Unfortunately most studios ship their failures, either because they don't realize they built something crappy or because the alternative is bankruptcy. A cynic would say that if AI can reduce the cost of experimentation, it will only result in more bad games, while an optimist would argue that it will result in more good games.
> He explains that this happens because knowledge work often relies on “pseudo productivity,” where visible busyness is treated as a proxy for real value. Digital tools reinforce this by making people look active: sending more messages, producing more drafts, attending more meetings, and generating more work artifacts. To avoid the trap, he recommends measuring real outcomes, identifying the true bottlenecks in one’s work, and separating deep work from shallow work so that digital tools support meaningful progress instead of consuming attention.
---
Like, you are just as well make the argument that if you replace the pseudo-work, you end up with 8 hours of deep work for things that bring you value.
YMMV
The problem I've had is two-fold.
1. I'm making amazing things (from my perspective) but nobody is paying me for it. I have many friends like this. We're older, very senior engineers with decades of experience and a love of computers/computer science. And we're building the platforms and tools we always wanted to exist. Summoning them into existence.
And nobody is going to pay us a single cent for it.
That's fine, until your roof needs replacing or your AC unit dies, like mine did.
"Dismissing the long list of projects" may in fact be a result of this.
What we have now with these tools is the ability to do more projects than ever, and the result is the marginal value of each of the projects is dropping like a rock.
2. Given the choice between attending meat-space issues and making these things, guess what I choose?
That's a me-shaped problem, I know, but I think it reflects the personality of a lot of people on this forum.
I feel like I'm on a roller coaster, and am simultaneously on the leading edge of being able to do more than ever while the value of all that "more" plummets plummet plummets.
You can do more than ever and unless you're independently wealthy (or incredibly well connected) it will go nowhere at all.
Also half the joy of writing code was having other people use it.
When everyone is a conjurer with a staff, nobody is going to care about what you just brought into existence. Build it and they won't come.
At the end of your life, if all you've done are little half baked throwaway projects, you might look back and realize one day you never made anything of any particular significance, just thrashed around building stuff people had already done so many times before that some unthinking, unfeeling LLM can spit it out almost verbatim just so you can say "me too".
This applies to more than just AI, it can be about any type of "side project" really, or any context where you have a wealth of so many possible options that focusing on one intensely forces you to deliberately ignore most of them.
An example for me lately is hackernews. I used to jump around wildy, looking at comments not really even reading articles. I felt like I was learning a lot. But lately I've taken another approach. Instead of clicking a bunch of things, I'm actually determining what is the most interesting article of the day, reading it thoroughly and truly thinking about it, and then after pausing for reflection, forming my own thoughts about it. I have found this to be a far more enriching experience than my previous habit. I think a lot of things in life turn out this way.
The only reason to use AI to build is when you don't really care too much about things, you just want something, anything. An image here, some code there, a ridiculous video. Cheap thrills with no soul required.
But I’m also one of those people for whom the “fun” was always solving human problems rather than solving computer problems. I can see how if you are in the latter category AI has already sucked out a lot of joy and how rapidly project switching could be the least-unfun option.
So when a blocker or an idea pops up, it's very easy to use that magic-like tool to solve it quickly and then go back to whatever it's you were doing before.
However, if you care about the quality of your output, that won't be a quick detour. It will pile up with the other "quick" tasks you were doing simultaneously and that's how you end up with 5-10 sessions working on totally unrelated projects.
I like to compare AI to GPS navigation. At least my experience of it. With GPS, I enter my destination, follow the direction and get to it. Problem is, I have no idea how I got there, I didn't pay attention to the landmarks, time and orientation, only to the arrow on the screen telling me where I should go, I learned nothing and should I go back, I will need the GPS again. And if the GPS is wrong, maybe because some road closed and it didn't get the update, too bad.
One may argue that using AI is a skill, yeah, sure, as much as following an arrow on a navigation screen is. It is nothing like actual development/navigation.
Personally, I have a terrible sense of direction, so I fully embrace GPS, and importantly, it isn't my job, no one pays me to navigate (they would want their money back anyways :)). But programming is my job, and I believe that if I want to keep it, I have to offer more than mindless vibe coding, that is a part that anyone can do, and practicing is the way to go. And even without the capitalist view, passion is about doing things the hard way because it is more rewarding, the easy way is wonderful at first, but it gets boring quickly.
Now, more specifically for AI, I think it has its uses. It can be a good rapid prototyping tool. I used to write some quick and dirty scripts, but rewrote them completely in a different language, with proper design, once I realized it would grow in complexity and have to be maintained. The first part can be vibe coded, before scrapping everything and doing it over by hand before it starts to grow. It is not an AI problem, it is more like a language problem, plain english simply isn't great for telling computers what to do exactly, in fact it is not good enough for telling other people what to do precisely, that's why many professions evolved their own language, math, chemical diagrams, blueprints, music scores, etc... In fact, that why porting is what AI does best: it already has a precise description of what to do in a programming language, human programmers already did the hard work, the AI just has to translate into another programming language. In the best case scenario, someone even wrote unit test so the AI can go over if it screwed up.
The author did not build those products. AI did.
And I don't read anything indicated they had fun.
There is pleasure in making something yourself. There is learning. There is pride.
With generative AI you are just stealing other people's work. You are learning nothing. Anything could have generated the same projects. There was no skill involved, just enough disposable income to pay for tokens.
And yes some people develop some weird psychosis and think that they did the thing and not the AI. Everyone else is vibe coding but they got the special sauce, the perfect prompts. They are delusional.
But prior to this I would rabbit hole. I would try desperately to remember some nuance, or I would not be able to move off a point until I got the validation I was looking for.
The worst is when speaking a foreign language and I hit some complex word in my native language that isn't present in my foreign lexicon. My brain just halts. It wants THAT word or phrase, not a 3 minute detour describing a whole concept.
AI has empowered me to move past these unnecessarily difficult speed bumps in my thinking.
It's allowed me to clear out some long-standing brush on the forest floor. And burn it down once or twice.
Yep, the same here, I'm a long pair programming enjoyer, but I'd like to raise that collaboration is usually meant with a human being in the context of pp, and prompting and agent to execute a task is nothing like that.
It’s a way of working that I really despise and if it’s the future of the profession I want nothing to do with it.
People who want to write code hate AI because it's doing the part they wanted to do.
People who want the end product of the code love AI because they want anything that helps them get to the end product faster.
The person who wrote this post feels oddly in neither camp. They like playing with the AI and seeing what comes out the other end. Some of the projects they boast about having built aren't even usable projects, like when they had it mock up a UI of a product and then got bored and moved on to the next before writing a backend.
AI industrialized a previously creative output. If you enjoyed the writing of code this is a nightmare. If writing code was a chore to solve a problem, this is a blessing.
There are a lot of people with high slop tolerance and who are seemingly prepared to endure the side effects of that.
That's not just because young people have time like GP explained, but it is also because young people haven't been through the endless rounds of getting beaten up at work over daring to suggest that the "old ways" of one's superiors might be outdated, inefficient or just plain wrong.
I am trying to think of a list of all the wonderful things I've built with AI:
Except for the SaaS, almost none of this is useful and I don't want to maintain any of it. I accidentally run a news outlet which is surely a liability. Sure, it has helped me "learn AI tooling" and I use many of these tools, but I didn't need them. I can't afford to maintain any of them, not in terms of time, commitment, belief, attention or willingness to spend on tokens.
I didn't mean to build most of these things. Usually the Claude session started with something like write a quick script for X, and one hour later the result is not a quick script for X, nor in the usual case is my problem solved, whatever the original itch happened to be.
On that last point, this technology is horrific for attention. It's a thermonuclear ADHD amplifier and I have seen the same effect in every single one of my adult friends. Folk running 3 screens simultaneously working on totally unrelated "projects" they have little hope of maintaining, and such little commitment to the outcome that the time is obviously wasted.
In recent times, at least once per month someone sends a screenshot for an awesome tool they are working on. I'm like whoa, that's really something and the sender is obviously proud and enthusiastic. I try not to ask, but am always thinking and where will you market it?, because when the question is asked of an engineer, the answer is unchanged since before LLMs existed.
I recently interviewed and when the topic of AI usage came up, the host answered something like oh we're quite light on it, everyone has up to 5 rooms where they manage their agents and I immediately felt a tightness in my stomach.
I had a vague sense of the effect a few months into using Claude. Later I reduced my subscription to Pro in the belief a quota restriction would mitigate excessive use. Then Claude went through a bad service period and I moved to Codex. Codex's CLI is much nicer than Claude's and noticeably faster. And usage started creeping back up.
The technology, when honed, is genuinely amazing. Ask it to zero shot a parser for an esoteric grammar implemented in an esoteric language with full tests and it's done. The tooling as it exists today promotes absolutely nothing like the focus required to apply it judiciously.
Almost every vendor and every tool intends to do exactly the opposite: more usage, more tokens, more output. Ask a simple yes/no question of ChatGPT and you can clearly see that it is hard-wired to include a relevant follow-up question to promote excessive interaction.
Slopping out a 10,000 LOC untested Python/JS mess in 5 minutes helps nobody. The thought of this happening in every commercial environment simultaneously is horrifying.
One of my early AI experiments, exploring AI as a lens in Marshall McLuhan-like thinking, was to connect speech recognition to a pipeline that generated blog posts on the other side, in the belief it would encourage me to capture my thoughts. All I needed was to press the voice note button in a Telegram channel, and out pops an Opus-formatted post.
The output was unbridled garbage. Because the effort was removed, so was the commitment, and with the commitment the focus, and with the focus any meaningful product at all. Quality writing is not conversational English simply cast through a lens: conversational English is low-bit rate noise, quality writing attempts to capture high bit rate information with better formed concepts, and this should have been obvious before I began.
I looked at repurposing the pipeline to capture private notes, but I have no need for private notes. It subverts the natural process of noise being forgotten. It is just more excess tool use.
Following from this, for as long as quality matters, I believe handwriting can never be obsolete.
It feels like we're heading towards crisis, and I doubt the answer is "better models" or "better tooling". Cal Newport relates this to pseudo-productivity:
The speaker argues that digital productivity tools, including AI and email, often create a “digital productivity paradox”: they make individual tasks faster or easier, but they can leave knowledge workers busier, more distracted, and less productive overall. He cites research showing that AI users spent much more time in email, messaging, chat, and business-management tools, while spending less time in focused, uninterrupted work. His central claim is that tools designed to reduce friction often increase the volume of shallow tasks and context switching, which weakens deep work and high-value output.
He explains that this happens because knowledge work often relies on “pseudo productivity,” where visible busyness is treated as a proxy for real value. Digital tools reinforce this by making people look active: sending more messages, producing more drafts, attending more meetings, and generating more work artifacts. To avoid the trap, he recommends measuring real outcomes, identifying the true bottlenecks in one’s work, and separating deep work from shallow work so that digital tools support meaningful progress instead of consuming attention.
-- 🤖
These experiences have opened a new perception of all tool use, because beneath it all this is not about faster development = more apps or faster email = more communication being a desirable goal. Generically, it's about a unit time of life and how it is spent meaningfully.
I have no idea how to manage AI at present except by curtailing use, because a tool producing a cheap reward with minimal input and no friction can only be a liability, and achieving that realisation is probably the only real contribution of AI to date.
David, Sun 31 May 14:31:04 2026
I've definitely spent too many sprints where LLMs told me that something would be easy and they could definitely do it, and then... 2 days later I'm still debugging their crap before it dawns on me... WTF am I doing with my time?!
Overall, I've built a memory safe programming language that solves a lot of problems I personally have - predominately in my spare time over 8 months - and I've learned A TON in the process.
I'm close to a release stage, and on top of that - I've built a lot of good tooling for Ruby that I think other people will find helpful once I polish it (especially if anyone plans to vibe code something non-trivial in Ruby - which I honestly wouldn't recommend).
But... I'm not really sure this is what I actually wanted to do with my time, and I'm constantly questioning how much time I'm sinking into this and why...
It started off as utter amazement of what LLMs can do, and then incredible frustration at what they can't do, and my unending desire to figure out why they're so bad at things so close to what they are exceptionally good at, and if there's anything I can do to bridge that gap.
That's partially what the language is designed for (before I even started using LLMs).
But after all this time... I'm not even sure I've really figured anything out tbh.
You’re very reasonable response may be “well, why don’t you just do more of what you want to do and less of what you don’t want to do” but that’s not how incentives work.
You could talk about revealed preferences, and how obviously if this person did these things maybe that’s obviously what he wanted to do. And great, feel good about that.
There’s an uncomfortable reality for most of us normies (maybe not popular with the libertarian HN crowd) that an increase in freedom can make it much more difficult to find meaning and purpose. Friction can be good actually.
I do theorize that this is one of the mechanisms by which productivity could be tanked by AI.
An agent taking notes and summarizing things is of no use. You are supposed to participate to a meeting, otherwise it is just a memo and the meeting doesn't have to take place. The correct solution is just to not attend it if you know you aren't requested to participate and are just here to grow the numbers and make your company waste money.
Sure, but also, who cares? The machine code is completely incidental for most purposes.
Maybe I'm just projecting. I enjoy making things. Maybe they do, maybe they don't. Sounds like you don't.
> There is pleasure in making something yourself. There is learning. There is pride.
You're speaking second person, when you should really be speaking first person. You enjoy making everything yourself, by hand. That is fine. It's also your personal perspective.
> You are learning nothing.
If you really aren't learning anything, you're doing AI wrong.
> Everyone else is vibe coding but they got the special sauce, the perfect prompts. They are delusional.
The delusion here is constructing a strawman out of the worst qualities you can imagine and berating that instead of actually looking at what other people are doing and trying to work out what they're thinking / how they feel. I can guarantee you that virtually nobody thinks they are the only person that can prompt a particular piece of software into existence.
I know this post probably won't land with you, because I'm a little annoyed while I write it (if only because your post comes off emotional and annoyed as well) (and, sorry in advance), but I do encourage you to consider that perhaps there are other worldviews than the clearly embittered and deeply entrenched one you've espoused. And perhaps those other worldviews are more suited to surviving the oncoming storm.
I think most developers are both! Depends on the task. Sometimes I want the result, sometimes I want the process.
Also sometimes, if I want the process, it’s because it’s something I want to have intimate knowledge of. There’s a practical benefit to writing stuff yourself, even if most of the time that benefit is tiny.
But it’s never really that straightforward.
There is some truth to the idea that some people enjoy it and others do not. I haven’t seen a pattern between them.
Having worked a lot with AI agents, I don't agree.
AI agents are amazing at producing response and results that look correct as long as you don't look too closely.
Even when I try to write extremely detailed specs and test harnesses, even Opus 4.8 and GPT-5.5 on max will find creative new ways to write code that breaks under real use cases.
Doing throwaway LLM output, playing with it a little bit, and then calling it done will create a false sense that you're really good at getting LLMs to produce working things.
That's exactly what the second group in my comment was meant to address. You enjoy the end product, therefore being able to skip the code writing is appealing.
The blog post is about someone who was having AI write a lot of side projects that they weren't even interesting in using. The post directly states that they were not useful, they didn't need them, and they weren't interested in maintaining or even finishing them.
Rest is a little stretch
Ya'll need to stop with this cope. It's not a good look.
If this argument actually worked in practice, the world would be a better place
That often requires marketing it.
When you have an LLM produce something and then delete, you didn’t learn much.
And that's entirely your fault, not the LLM's.
I think the real bifurcation is whether you will settle on that belief.
Some of us are settling on the belief that the idiot savant, lacking the coherence of a functional mind, cannot be managed. It's essentially a chaos agent masquerading as something more cooperative.
With SO copy/paste, you still were undertaking the mental exercise (and reward) of thinking through hard problems, researching solutions, and assembling it yourself.
With AI, you literally outsource most or all of that. The way some people "vibe code", they barely are engaged with any of that process, if at all.
I think about it like I do video games: it's a lot of fun to play them, and while it can be interesting to watch someone else play, it's just not the same.
Stack Overflow had it's heyday, but by the time AI came around I already wasn't using it. Stack Overflow for a long time has been inundated with the kind of people who think everything is the XY problem[1], and arrogantly assume they know what your problem is better than you do. Stack Overflow was all-but-useless for at least 5 years before AI broke into the public eye.
Personally I make sure meetings are a good use of my time and I complain when they are not. I also am starting to complain about AI summarizers because they frequently misrepresent what is said in meetings and they're potentially worse than nothing, although I am starting to think that they're potentially valuable if Google is trying to datamine them for info about our company meetings as a way of poisoning their datasets. But I am worried my coworkers may be thinking they are reliable.
Many of the people who are complaining about AI vibecoding today also didn't blindly copy/paste from StackOverflow in the past.
Where does this idea come from that good programmers were ever cool with that?
There is a difference between learning woodworking as a fun hobby that would allow you to make a chair for yourself vs. doing it in hopes of turning it into a profitable business venture that would make an impact on the world.
By the grandparent comment logic, there is no point in doing anything, unless it can somehow lead you to making an outsized impact on the world. Thus essentially declaring most hobby pursuits (that are done mostly just for the sake of fun and learning) as wasteful.
So if you see an answer on stack overflow, read it, comprehend it, and you can pretty easily mentally verify the correctness to a sufficient degree of confidence…
I guess I’m not worth my salt.
r/programminghumor mostly. It was always tongue in cheek, but people took it too seriously.
However, the number of times I’ve gone over to help a colleague and realized they were trying to copy/paste code from SO, without even reading the context of the thread is baffling. Like, why did you expect it to work in the first place? I really try to be humble and not make assumptions about people competencies but it’s really hard to have those experiences and not think the average programmer is just an idiot. It’s no wonder AI is helping people when this was the baseline.
I have a standing challenge to my co-workers that valid compiler errors will be rewarded like a birthday party, with the baked goods, alcohol, or sweets of their choice. It's only been redeemed once, and I've found less than a dozen unreported compiler bugs myself.
You mean a source that's been tested on billions of PCs over 45+ years?
As opposed to a LLM which outputs code that barely works on my machine™?
Maybe this is not the case if you are doing a dozen throwaway websites, but for anything serious that is an absolute requirement. I work in hard realtime safety critical code, think things like brake controllers, medical devices, auto pilots, etc. In my case industrial control systems. You need to have full control and documentation for your development process.
But I often do think across adjacent abstraction levels, because abstractions are (varying levels of) leaky. Modern compilers are after many decades good enough and modern computers fast enough that it is rare that I need to dig into the assembly (but I happens, compiler explorer is in my bookmark bar in Firefox).
Other abstractions are far leakier, it is far more common that I look in wireshark to debug network issues, the application level view is often not enough.
One of the leakiest abstractions currently is LLMs. Maybe in a decade or three they will be good enough, but they aren't yet, that's for sure. At least for the hard realtime systems level programming I do. For code generation they often make enough mistakes that the time spent after review and fixes comes out in the wash, even for simple tools. Their use for bug finding, RAG and similar is however promising.
Currently the openbsd mailing list for port is currently going through a clang update and one of the main point is looking at all the packages that failed to build. I even took a long look at the usb stack and the audio subsystem of OpenBSD because of an issue I was having with my DAC.
I learned to debug and built comprehension by typing it in, and built it as a practice. Later in life and career I learned the value of transcription rather than copying and pasting because it at the very least forced me to read and write what I was copying, and built the base and familiarity I needed to learn from what I was copying.
That extends to how I use AI today. I use AI tooling to explore the concept of what I am building, use spec based designs to build solid outlines, and scope individual coding sessions, so that even when I use AI to build it, I have read, edited, and managed the design, and when I run into parts that I don't consider boilerplate I treat it the same way, transcribe what was attempted to understand why it was failing, and make sure I understand what the AI is doing that I haven't done before.
I have seen entire multi million dollar operations running off the most horrible PHP spaghetti nonsense.
The base line is far below any floor you are thinking of.
It's like having a naive but super knowledgeable junior developer starting under you. It's obvious you'd learn a lot in how to communicate, framing, specifications, and what kind of follow-up you'd need to do to ensure good results.
Or maybe just compare Hermes vs OpenClaw for long-horizon personal agentic tasks. Which one performs better in offline inference personal finance analysis tasks?
Or read up on how the `/code-review` workflow works in Opus 4.8 and give me a guess as to how long it'll take Codex to implement it and which tool would be more appropriate for your engineering team (don't forget to include enterprise API token costs in workflows – it can spin up 100 agents in thirty seconds).
If you can figure out how to secure agents with simultaneous access to personal data and the internet to run unsupervised while avoiding the lethal trifecta (Willison, 2025) let me know.
At my last job the employer paid for OpenAI access for all of us.
Baby sitting an LLM is not my idea of meaningful use of time. And reviewing code that someone else had an LLM spew out even less so.
I am not lashing out because I don’t have access to LLMs. I had access and I did try it plenty.
So when you have a bug and a core dump, you can quickly load it in debugger, see the stack frame and then theorize a model for the bug to happen. If after verifying the source and having complete confidence that it's good, then you start looking at the assembly, most likely while single stepping with the debugger. But you rarely get to that point, because 99.99... it's your code.
That reliability is what AI tooling is lacking. It's exhausting monitoring the output because errors can be as simple as a minus character or the wrong comparison operator.
You may as well ask to run a comparison between gnu libc 2.42 and musl 1.2.5.
> Hermes vs OpenClaw for long-horizon personal agentic tasks. Which one performs better in offline inference personal finance analysis tasks
What are those tasks? This and the paragraph just after seems very much like a XY problem where all the energy is focusing on resolving the Y, not the X. It's like discussing how we can reach the moon using cannons.
> If you can figure out how to secure agents with simultaneous access to personal data and the internet to run unsupervised while avoiding the lethal trifecta (Willison, 2025) let me know.
If you can figure out how to run user submitted JavaScript inside a webpage with access to the internet and other user personal data, you will have your answer. There's a reason we escape user input before rendering it within the browser. The browser is an executing agent and it doesn't differentiate between your markup and other data you choose to embed in it. Same things happens with the processor if you choose to mix input data with executable code.
Telling me you wouldn't learn anything from this?
> What are those tasks? This and the paragraph just after seems very much like a XY problem where all the energy is focusing on resolving the Y, not the X. It's like discussing how we can reach the moon using cannons.
Or like how we can get from A to B without horses.
It's a different world, one worth learning about. If these tasks don't at least arouse your interest, nothing I can say will help you.