Posted by dmw_ng 3 hours ago
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.
AI tools have put friction where it should be - by eliminating incidental friction. By incidental friction I mean, things that were really not ambiguous, but were made so due to lack of access to resources.
As an example, if i needed to navigate, I used a paper map. There was friction in pulling out a map, planning a route etc. This took time. With digital mapping apps this sort of incidental friction is not there.
Real friction is inherent ambiguity. For example, what product does the market need ? By eliminating incidental friction, AI allows us to focus on the smallest hard-problem where there is real-friction.
The challenge introduced by AI is that in ruthlessly eliminating incidental friction, you are being deliberate about what you choose not to learn. This is fine at a task level - but how many of us “found” our current expertise through incidental friction in the first place? I never wanted to do chemistry, I went to school for something else. But incidental friction led to discovery. That is my biggest worry, particularly for students and early career folks.
Digital maps clearly solve the end-goal needs for most people. But like your father in law, there’s definitely a loss in that exchange.
Bearings are incredibly useful. I remember navigating myself and my partner out of a small town on vacation by the position of the sun. It was international so we didnt have internet at the time. Im never going to live that one down!
People do this all the time. It's such a common problem in startups that all of the books, courses, advisors, and everyone else with experience talks about finding product market fit early and shipping MVPs to validate the product.
It's the most common startup advice and people still ignore it and build unvalidated things for years anyway.
It's too easy to get started on your big idea and then switch to a rhythm of working on the next task without ever stopping to validate the big direction
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. I think we'll find that they're both right.
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?
I setup exactly one personal finance service/dashboard and one Android app for a specific purpose. Then I stopped because my needs were met. I'm sure I will get into it when I need to again.
You can either use it as a PoC testing enabler in which case it will be bunch of unfinished things. Or you can be deliberate and focused about your goals and the results will match that. Of course being a software developer helps.
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.
Starting projects has always been easy. But once I figured out the hard stuff and then had everything figured out and only saw the long road ahead of drudgery and pipe laying my motivation fizzles out unless my paycheck depends on it.
Now? I still get to figure out the fun hard part and then go send a cheap fast working dumb minion to do the tedium.
I’ve finished 3 things in the past month that have been on my hobby list for years with no progress. It’s been really freeing.
The real moment of truth will be if it’s still worth the cost for tasks that have human value and users but aren’t profitable, which is where most of my side projects live. At current rates it is for me, but once the VC subsidies evaporate then maybe not.
For me, rather than cling to the notion that these are things I need to complete and should feel guilty about not having done so, I just started accepting that they either will be completed when the time is right if they're worth my focus, or they weren't meant to be completed and there's probably something better that's come along since starting. I usually keep them all in an archive as a timeline of tinkering and a record of how much time I didn't waste on trying to complete them
Ya'll need to stop with this cope. It's not a good look.
Many of the people who are complaining about AI vibecoding today also didn't blindly copy/paste from StackOverflow in the past.
The fact that you consider deterministic output from a compiler the same as probabilistic output from a LLM makes me think you don't know how either of those things work, even at a very superficial level.
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.
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.
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.
The change has been so rapid that I think a lot of people are having a hard time I guess wrapping their head about the lived experience of it. For a while my only access to the tools was through work. Then I ended up getting a $20/month ChatGPT account and that comes with codex and now I can't imagine sitting there Googling a problem anymore. It literally feels low tech these days. Big "I'm not paying for Cable, the antenna is good enough" energy. It saves me soooooo much time just maintaining my own local stuff. I mean it literally saves me hours and hours of personal labor.
The local models will 100% catch up. Most likely the inference I use now will be free in five years across the board and you'll be buying a cyberdeck or something with a 128G of RAM and an LLM friendly bus architecture.
But for code it's a race to the bottom because it's all text and local works quite well. You can host models on LangSmith and similar and because people use those services to create chat bots the overall use of them for coding is a very tiny fraction of their overall usage. The race to the bottom is further exacerbated by the fact that as GPUs become more powerful you can host more per unit so the cost of text inference will drop precipitately. Right now people are reporting that for some of the self hosted services they are able to do everything for under $5 / month. That price WILL drop because that's how computers work.
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™?
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.
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.
I've never done that; many experienced devs I know have never done that. We barely used it, in fact! The few times I asked a question, the answer was not "Here's a piece of code".
Look, this comment of yours, coupled with a previous comment from you in this thread (demonstrating you don't know the difference between probabilistic and deterministic output) makes it painfully clear you don't do development; or at least you didn't until you were handed a magic "write me a program" tool...
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.
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.
Where does this idea come from that good programmers were ever cool with that?
Copium from folk who were never developers before, but who now want the badge anyway. Too bad the same badge can be given out to a bright 12 year old who doesn't know the difference between a variable and a type.
I suppose I'd have to admit to not being a "developer" anymore, because developers in the age of AI won't know how to write code. Perhaps I can still hold on to the label "programmer" for a little while longer.
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 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.
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.
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.
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.
The most important point was:
It’s uncomfortable. The discomfort is the point.
Pain is the greatest teacher, but nobody willingly
attends her classes.
[0]: https://freebsdfoundation.org/our-work/journal/browser-based...
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.
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.
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.
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.
Just today I was toying with AI to make some bumper music. It came up with some great phrases and fragments. But its 'song' output is a hilarious mess, and feels like I'd be better off starting from scratch and taking only the bits that work.
Then there's the ethical question of where those clever lyrics even came from. Perhaps just lifted from niche works I never heard before.
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.
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.
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.
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.
There are a lot of people with high slop tolerance and who are seemingly prepared to endure the side effects of that.
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.
Yeah, it does make me wonder though - have these AI boosters never written their own tools before? I've written, for my own personal use, literally thousands of tiny little bash scripts, vim scripts, emacs scripts, Python programs, C programs, etc. I still daily use a music player (wish wrapper around mpg123) that I did in 2001[1]!
And yet, I'd be the first to admit that, for each 1000 things I wrote, probably 1 got permanent use for a significant length of time; the value, over time, to me was the lessons learned.
Now people are going through that cycle faster (i.e. instead of doing 5000 persona-use programs over 30 years, they're doing it in a single year), but the end result is still going to be the same - no one is ever gonna use it, including themselves!
It comes with an additional downside - you don't actually learn anything by having the AI generate your programs for you.
--------------------------------
[1] In case anyone is interested why I wanted a wrapper - it uses the locatedb so that I don't have to search for my mp3s:
#!/usr/bin/wish
# Copyright Lelanthran K. Manickum 2002, provided under BSD license
#
set version "1.0"
proc playSong {songname} {
set rc [catch { exec killall -9 mpg123 }]
if {$songname=="\[Stop Playback]"} {
.midFrame.lblPlaying configure -text "Stopped"
return 0;
}
set rc [catch { exec mpg123 --loop -1 "$songname" & }]
if {$rc==0} {
.midFrame.lblPlaying configure -text "Playing: $songname"
}
}
proc locateSongs {pattern} {
.lstResults delete 0 999999999
set tmpvar [split [exec locate -i "*$pattern*.mp3"] "\n"]
.lstResults insert 0 "\[Stop Playback]"
foreach title $tmpvar {
.lstResults insert 1 $title
}
}
frame .topFrame
frame .midFrame
entry .topFrame.entSearchString -text "Search String"
button .topFrame.btnSearch -text "Search" -command {locateSongs [.topFrame.entSearchString get]}
listbox .lstResults -yscrollcommand {.sby set} -xscrollcommand {.sbx set}
scrollbar .sby -orien vert -command {.lstResults yview}
scrollbar .sbx -orien horiz -command {.lstResults xview}
label .midFrame.lblPlaying -text "Stopped"
locateSongs ""
focus .topFrame.entSearchString
bind .topFrame.entSearchString <Return> ".topFrame.btnSearch invoke"
bind .lstResults <Double-B1-ButtonRelease> {playSong [.lstResults get active]}
bind .lstResults <Return> {playSong [.lstResults get active]}
grid .topFrame -row 0 -column 0 -sticky nsew
grid .topFrame.entSearchString -column 0 -row 0 -sticky nsew
grid .topFrame.btnSearch -column 1 -row 0 -sticky nsew
grid .midFrame -column 0 -row 1 -sticky nsew
grid .midFrame.lblPlaying -column 0 -row 0 -sticky nsew
grid .lstResults -column 0 -row 2 -sticky nsew
grid .sby -column 1 -row 2 -sticky nsew
grid .sbx -column 0 -row 3 -sticky nsew
grid rowconfigure .topFrame 0 -weight 1
grid columnconfigure .topFrame 0 -weight 1
grid rowconfigure . 2 -weight 2
grid columnconfigure . 0 -weight 2
wm protocol . WM_DELETE_WINDOW {
set rc [catch { exec killall -9 mpg123 } ]
destroy .
}
wm title . "Simple Music Player - v$version"
wm geometry . 700x500If 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).
as we grow we change
that is life
lots of things i cared deeply about 10 years ago that i don’t even remember now
i find self loathing a previous version of yourself to be a by product of religious thinking
yes the original sin is that you were born but for now you can enjoy your life do so
Rest is a little stretch
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.
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.
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.
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?
YMMV
That often requires marketing it.
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.
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.
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".
> 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.
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.
If this argument actually worked in practice, the world would be a better place
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.
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.