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Posted by dmw_ng 6 hours ago

The solution might be cancelling my AI subscription(thoughts.hmmz.org)
310 points | 212 commentspage 3
rossjudson 4 hours ago|
Quoting:

"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".

propter_hoc 4 hours ago||
This actually really resonates with me, particularly the part about his AI tools for blogging and note taking.

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.

elliotbnvl 5 hours ago||
It seems like the author is overindexing on useful and underindexing on wonderful. He clearly had fun building these products — and in hindsight is disavowing them because they didn’t generate income? An oddly capitalist view of play.

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.

xendo 5 hours ago||
In the old days, producing all those things would be tremendous learning opportunity. Today it's a pure waste, not producing income is not a problem, not producing anything is.
elliotbnvl 5 hours ago|||
If it wasn’t a learning opportunity to build those things, that was the waste. You can learn from an AI far more easily than from a book — only now it’s far more easy not to and many people unconsciously choose that route.
naasking 5 hours ago|||
Learning how to use AI effectively was the learning opportunity here, what was created is completely incidental. You're effectively obsessing over programming languages obscuring the machine code that actually runs. "Imagine all the missed learning opportunity of digging into all that machine code!"

Sure, but also, who cares? The machine code is completely incidental for most purposes.

xendo 5 hours ago||
I work with AI everyday, despite what many people suggest there is so little to learn. After a couple of hours you are good to go. You don't even need gstack.
elliotbnvl 4 hours ago|||
This is patently false. I work with and on AI every day at multiple levels of the stack, and every day I'm learning massive new swathes of information. I'm honestly shocked how deep the field goes and how much more effective you can be with time. The floor is falling and the ceiling is rising and the gap between them is widening every day.
xendo 4 hours ago|||
Maybe it depends on the task, but the biggest productivity gains are from boiler plate generation, and there it's as easy as "generate me the boiler plate". Even if you can learn some very specific workflows today they would be model dependent and mostly obsolete within a month or two.
skydhash 4 hours ago|||
That would be more convincing if you put up two or more examples of what is there to learn.
elliotbnvl 4 hours ago|||
Go off and run a comparison of Qwen 3.6 27B and GLM 5.1 GGUF (https://huggingface.co/ubergarm/GLM-5.1-GGUF) at IQ2_KL 261.988 GiB (2.985 BPW) and let me know if you learn anything.

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.

skydhash 3 hours ago||
> Go off and run a comparison of Qwen 3.6 27B and GLM 5.1 GGUF

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.

elliotbnvl 3 hours ago||
> You may as well ask to run a comparison between gnu libc 2.42 and musl 1.2.5.

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.

xendo 4 hours ago||||
Even with examples it's still not convincing. I'm working on real products so I don't have time to waste comparing models that won't be relevant next month.
naasking 4 hours ago|||
Using AI effectively for long horizon tasks, like maintaining a large codebase, is a wide open field. No single AI is good at it autonomously. That means achieving the right balance of testing, formal specification of pre/post-conditions and invariants and manual review.

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.

naasking 4 hours ago|||
Unless you just happen to work in a domain where the code you generate every day is very common in the AI training data, this isn't true.
cardanome 5 hours ago|||
> He clearly had fun building these products

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.

elliotbnvl 4 hours ago||
> And I don't read anything indicated they had fun.

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.

GuB-42 4 hours ago||
It is not just about not generating income, it is also about learning very little.

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.

ryanisnan 3 hours ago||
I have a different take. I empathize with the author, but my experience is quite different. I have a couple of side projects going, not dozens, like the author mentioned, but my approach with each is heavily focused around verification and testing. The AI is doing all of the development, but I maintain a strict set of documentation defining what properties I want the product to achieve. Everything cyclically is evaluated vs. my view of the world.

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.

4b11b4 3 hours ago||
I'm increasingly over it. Don't care how good the model/harness gets, the second I can't hold every bit of the mental model in my head is the second it's all over. And that's a very fine line and very easy to cross
selectedambient 3 hours ago||
i feel like regardless what you're doing, consistency is key, aside from actually learning right? you mentioned people running three sessions at once on projects they have no hope of maintaining. very fair point, it's just gambling at that point. however, working on the same project or few projects, you DO hope to maintain (even with ai) for 8 months to a year straight is an entirely different experience than trying to powerhouse anything and everything just to have it? or something, i'm not really sure what the point in this would be. it isn't applicable on a resume or impressive to anyone with any real technical experience. at least if you're staying consistent you're learning something about the process, how to improve it, everything it does, etc. i've seen it time and time again, previously nontechnical or barely technical people "getting into coding" (i.e. using ai), creating something that would've taken time 10 years ago and marveling at it like they've done something. meanwhile, without thinking.. "if i had no prior experience and was able to quickly throw something together with AI, how valuable is the thing i threw together really?" to be clear i'm not saying you're doing this, but this is certainly what a LOT of the people you described are doing. this isn't even delving into the bugs and security flaws their programs are most likely full of. never mind they're learning practically nothing. anyway, i generally agree with your sentiment.
yawnxyz 3 hours ago||
> Generically, it's about a unit time of life and how it is spent meaningfully

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)

slashdave 5 hours ago||
This is not an AI problem. Or rather, AI just made it worse. Focus can be hard. The thing is, AI can help you focus, by making code maintenance easier too.
Trasmatta 4 hours ago|
AI makes code maintenance harder
docheinestages 4 hours ago||
We're still in the phase where we're having our first reaction to the software development lifecycle with the help of AI. We're quickly starting to realize what AI is making cheap, and where the new bottlenecks are. How most people are currently using AI is rather naive and superficial. One-shotting only takes you so far.
ruguo 5 hours ago|
AI makes me far more productive, but I’ve lost quite a bit too. There’s less fun in coding these days, and it leaves me feeling adrift at times.
dawnerd 5 hours ago||
For me the sweet spot has been next suggested edit. I’m still writing code but the autocomplete does make it faster. That’s made coding more fun for me. What’s not fun is prompting then waiting around to find out it’s not what you wanted.
naasking 5 hours ago||
Coding has engaging parts, and plenty of drudgery. AI is generally good at the latter, and you don't need to use it for the former.
slashdave 5 hours ago||
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