The solution might be cancelling my AI subscription
thoughts.hmmz.org
thoughts.hmmz.org
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?
What I want to say is that it's very situational and it's likely good to focus on the average. Using LLMs as docs are bad when good docs exist, but if you aren't sure if they do, it's a gamble. A much better approach would be to have somebody pre-create and edit the docs with an LLM for each service with bad docs.
Only when your situation isn't covered would it make sense to create new docs.
I hope that this isn't the case for me poking around in vim, using ctags etc. But sadly it may be true.
I think another set of related effects might when people switch programming languages. There two major things tend to happen. Rewrites of something they now understand way better and having a clean slate. As well as - in case of new programming languages - way less historical bagged, 15 ways of doing the same way, deprecated tools, lots of the "new way" code in dependencies and "old ways".
What I mean with that is that there are a lot of overlooked things going on. And humans in general are really good at mistaking moving a problem somewhere else as not having to deal with that problem. Sometimes that is the case, sometimes even moving things to another apartment or being able to move work to a free coworker is a worthwhile investment even if it adds overhead. But it's also really easy to forget about how you didn't make issues disappear but just moved the issue somewhere else.
I think psychology plays a much bigger role in many of these things than technology does.
These are just examples. I don't argue against any of these things, also because whether they are worthwhile depends a lot on context. However, I do think that LLMs aren't the first example of that happening.
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
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.
But sometimes, I feel it is too easy to bounce from thing to thing.
I moved my docker compose stack to opentofu so that (in theory) I can just run tofu apply on any server and the setup will be 1:1 what I want and need.
Maybe some day I'll see if even AI can figure out NixOS :D
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.
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.
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
Almost any reasonable idea that is not obviously bad (as in having some clearly insurmountable technical or market hurdles, etc) can be made to work.
What makes ideas work (and this is what separates those with a true entrepreneurs mindset from those just playing the lottery of "MVP"s) is the creation of what I call a viability field around them.
When a person decides to create an app, or some other product, or a certain business, they have not exhaustively considered all the possible things they could do and decided that this is the objectively most viable thing to pursue. They commit to a space they like ot be in, that feels like a good match for their skills and temperament, etc.
Then, within the general idea, the key I think is to begin creating a product, the development and marketing of which acts as a substrate for the learnings you need to succeed in that market. AI used judiciously can help you to cover ground more quickly, or at least be a bit more fearless about attempting that.
Basically you should build something that allows you to learn, to pivot, to adapt as necessary until you find product market fit. Rarely, you'd need to throw everything out, but even then I often argue it is matter of personal decision rather than any fundamental roadblock. If you you are really committed to an idea, and have developed it enough (not just a 1 week MVP) to deeply understand its context, there is almost always a tangent you can take that brings you to success without throwing out everything.
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 wrinkle that needs to be added is that there are no truly universal rules as to what counts for incidental vs ambiguous friction - the definitions are relative to individual/project goals. I am working with some scientific instruments to map out chemical data, and 3d modeling is needed. I don’t particularly care about 3d modeling - it is incidental to me. The chemistry is the focal point. So the STL files are vibe coded so I can keep my focus on chemistry. But if I were working for the latest marvel movie, the reverse would be true. The actual chemistry would need to fit the script and the visual effect intended. To a scientist the visualization just needs to be good enough. To the film director, the world building physics and chemistry instead become the supporting actor. 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!
Agree, and I have the same worry, and so did the OP to the point that he considers canceling his AI subscription. Most of have to first get through the incidental friction to be able to arrive at expertise to address ambiguity.
I’m much more able to navigate without the map than I was before I started this experiment - and it’s had the added benefit of giving me the ability to know what part of the 101 I’m on solely by the angle and shape of the nearest exit.
I hope eventually AI gets to a point where I can split the difference between ambiguous and incidental friction like this, although tbh I’m not really sure what that would look like.
People who speak those languages have an almost supernatural way of knowing where is north intuitively, because they HAD to do it to communicate.
> 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.
You should def try to commercialize your slop and get feedback. No one cares about your tech stack or whether it's maintainable. Does it add value? You'll get a strong signal as to whether it does or not. And adding value, picking the right problem in the right domain, that's the hard part. You can always re-write or clean it up. Didn't Javascript start out as a weekend project? (maybe not a great example depending on how much you like JS)
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.
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.
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 you didn't encounter those people. People said they've used the tools, and then you said it wasn't recent enough. Not because you know when they've used it last, but because their experience didn't match yours.
It's great that it's working for you, really. But since you have been posting on HN a lot about this, while simultaneously claiming you don't care what other people do, maybe consider a different approach than calling everyone luddites. If people call you a shill, and you exit the conversation claiming you don't care, but then you go to the next thread doing the same low effort stuff, don't be surprised when people see a pattern. There are lots of people communicating more effectively about this.
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™?
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.
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.
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.
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...
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.
Where does this idea come from that good programmers were ever cool with that?
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 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.
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.
Where's yours?
After all, my CV (online like everything else) shows almost 30 years in the field, 7 of which as a research scientist, 6 of which was spent writing software for munitions, many of which were spent as an EMV developer, a stint at a FAANG...
All you've done is state the things that very junior devs state, with just as much confidence.
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...
With such a list of side projects you would learn just SO MUCH by doing it yourself, which IMHO is the whole point of playing around and what makes the experience satisfying. Here they get the artifacts, but nothing else.
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.
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.
Rest is a little stretch
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.
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.
I love coding. I've always loved coding. But coding with llms has helped me step back and see the overall design of a project better. And llms know tricks I didn't, and some of these are neat, and now I know them too. So, personally, I feel like I'm still learning, a lot. It's just a different way of learning - and one that makes coding interesting all over again.
(That said, I cannot use agentic systems and embed myself fully in the loop, and still code myself. Sometimes its faster to code the next change manually, sometimes it's faster to guide an llm. But it's still interesting, and it's even more fun, at least to me.)
I know, for example. That I can take a Cheap Yellow Display from Aliexpress and have it show the train timetables and weather. BUT I also know that the timetable public Web API requires encryption - which is a pain with the small chip in the display - but the private API with an API key works via plain http.
I didn't write a single line of code, but the display is on my hallway cabinet, working 100% the way I like it.
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.
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.
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.
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.
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.
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).
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
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 . 700x500Perhaps 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".
> 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.
>What will happen once all the rough edges are filed down?
You're new around here? ;-) Or maybe I'm just old and jaded, and feel like there's always infinite more work to do. My boss, the CTO, has said "if you are getting twice your pre-AI work done in half the time, the rest of the time is yours." Unfortunately that statement came after "I'm not sure how the CEO feels about this but..."
My company has 25 years of tech debt built up, and the AI tooling has allowed us to make amazing headway on that, but I'm ~5 years from retirement, even working 10X I'm not expecting we can catch up in that time.
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.
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.
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?
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.
The big difference is, prior to LLMs, that you spent no money but gained something in the process of doing that little half-baked throwaway project.
Now, you spend some money, and get nothing in return.
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.
In other words, the issue isn’t the AI subscription, it’s the ADHD.
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.
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.
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.
Sure, but also, who cares? The machine code is completely incidental for most purposes.
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.
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.
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.
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 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.
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.
Nothing different from all innovations.
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.
"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".
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.
Why is it wasted? A powerful new tool was invented, and enthusiasts are exploring ways to harness it. They'll come away with the skill to wield this new tool effectively. The programs they're writing are completely secondary.
AI makes single purpose throw away tools easy to create. This is GREAT. I had to migrate an old Windows 2012 file server share to SharePoint. Microsoft's tools don't work on this old OS. Their SharePoint migration tool running on other machines on the local network constantly failed for nebulous reasons. I finally got fed up and spent a few hours with Gemini Pro and Claude and created a sync tool using C# that does the migration and keeps the network share in sync with SharePoint until we do the final cutover. I don't expect to ever use this tool again, and that's totally fine. I'll still put it on GitHub in case someone has a use for it, but I'm not sure why I should lament the fact that this tool exists and may never see another use or the fact that I won't maintain it.
Don't waste your life playing with shiny new toys, sure, but learning how to use AI by creating things is not a waste of time.
> Except for the SaaS, almost none of this is useful and I don't want to maintain any of it.
So don’t. Nobody’s twisting your arm.
Nobody told the author to sit down and write a bunch of random useless stuff.
This is like blaming your bicycle for enabling you to stop at too many shops that you didn’t mean to go to when you originally meant to ride straight to the grocery store.
I can relate to this greatly I have started dozens of projects since last summer but have been having a hard time turning these into real value. Not even money but just something that people find useful beyond my own learnings.
Yeah I think we should protect these people from accessing these technologies, because they clearly can't handle it!
I have the feeling a lot of people are advocating to at least (try to) boycott AI, and downplay it, make people feel guilty about it's usage. It's vaccines vs no vaccines all over again. So binary.
Maybe we should maybe some kind of license, like driving license, but for AI. So only people qualified to use it safely and sanely can legally use it.
We can’t blame bicycles or dumbbells for exercise addiction.
You started those projects because you felt like starting those projects.
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.
I would be wary of using McLuhan-like media analysis of AI. His central argument is that media are tools that extend man's ability. A calculator or a spell checker extend our thinking and writing. AI does not extend those abilities so much as it completely replaces it.
The way in which it does resemble media is insofar as it captures the same urge that McLuhan wrote about to see ourselves extended into the world. McLuhan tied this to the myth of Narcissus. The difference is that where Narcissus falsely believed it wasn't him and fell in love with what he saw, we falsely believe the image we see is ourselves and fall in love with it.
At the grocery store there's countless (no pun) opportunities to do math in the sense of comparing prices and calculating unit costs etc, but most people can't do that math easily in their head because the calculator has made that skill less important.
But people also don't pull out the calculator repeatedly to do this in the grocery store, so the math just doesn't get done.
These two elements (extend/replace) are not mutually opposed according to McLuhan's tetrad.
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)
This applies to all software projects except for the "useful to you" part, which turns into valuable to "your/the business"
I don't believe I have ADHD, but I've come to realize my brain is wired 'differently'.
Highly subjective (which is why I am curious), but I know zero people in real life that have an actual ADHD diagnosis, but two that were pretty much convinced to have ADHD and when trying to establish it for real learned that they actually have a different kind of neurodivergency/mental disease.
I think both of those cases were caused by a pretty large set of ADHD and other things are not as specific as they appear to a non-professional and also some conditions can make you more sensitive to noticing specific "symptoms".
For anyone reading this: Please don't read this as "you don't have it", but also if you think please try to confirm it via a trained professional, because the result could make your life quite a bit better, whether you are diagnosed ADHD or anything else.
Wowzers this resonated with me. I’m an ideas person, and a pretty bad coder, at least compared to the normal HN crew. I’ve found Claude to be absolutely astonishing at creating amazing, working apps that I use all the time. But I’ve also been aware for a while that having no bottleneck on ideas isn’t 100% a happy situation.
I’ve spent years and years - 30, maybe - coming up with various (often web related) ideas and having to kick them into the “no time, not enough expertise” long grass. Claude removed this barrier - which is incredible - but also I’ve become aware about how damaging this is mentally, too.
My attention - already scattered - was totally, totally fucked for a while there, 5 windows with different agents all pumping out my latest, greatest idea, no guard rails, no buffer…
I’ve spent the last month being very deliberately not this - and it’s making a huge difference. I’m lucky because I noticed it, and I’m lucky because I’ve somehow got the wherewithal to do something about it, but it’s all been quite sobering.
'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.
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.
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.
Also, if nobody uses them, they don't need to be maintained. You can shut them down with no regrets.
This is a common problem with devs - they don’t understand how code fits into a business model, and generally massively underestimate non technical elements such as focus and sales
Mike Judge is a fucking genius. But every person who has every tried knows that selling your tech prototype can be hard.
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.
Bingo.
we just used ai to improve products and services
instead of all this wanking off showing how you go through 1 billion tokens a month (not really that impressive)
what would be way more cool is
i made something that reliably saves others 8 hours a month of busywork
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".
And this slipped to 23rd position on the page.
I first came to HN in the “todo.txt” era of “productivity hacking” and note-taking -platforms like Evernote. Like many people I had a zettelkasten phase, tried to make a second brain, tried to optimize everything blah blah blah.
Over the ensuing 15 years and several career shifts later, it’s fascinating to see how AI as supplanted so many of these tools. However in my personal case, greater professional success has coincided with discernment, i.e., knowing which information is important to internalize and commit to memory, which can be filed for reference, and which can be allowed to fade away or be forgotten.
In my current work, there is a huge amount of information that I really, truly need to know “by heart” to do my job well. There’s an equal portion that I maintain in traditional reference files with reliable retrieval systems. I do use machine learning for certain field tasks, but over time I have been able to learn to do these tasks myself when an internet connection is unavailable.
No LLM tool thus far appears useful for me. One big reason is that I work in a compliance/regulatory space where hallucination is simply unacceptable. If I have to check the output for errors, I may as well just look at the primary source to start with.
Another reason is that in regulatory settings, people will say in filings/documents that they are obeying XYZ law, but it isn’t true. I need to find out *in the field* whether the assertions are true. LLMs are not useful for that, either.
But I think the largest gap is between LLMs’ product promise and my personal professional goals. I want _wisdom_ and clinical experience as a professional, the type of things that accrue slowly over a lifetime and distinguish the people who are truly good at their jobs.
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.
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.
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.
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 allowed me to clear out some long-standing brush on the forest floor. And burn it down once or twice.
No matter how hard I try, I can't put myself in OP position; I think I would go crazy if the most important thing in life was chasing money or ways to monetize my hobbies.