The fun / creative part for me is not googling “how to slurp the contents of a file into a string” or “the exact syntax for marking some functions as unit tests” or “the correct order of symbols to specify generic type param”
It’s not “the correct html / css syntax for this basic gui I want to make”
It’s not “how to achieve the thing I’ve done 10 thousand times in other languages/frameworks, but for this language/framework”
It’s figuring the core logic out, building the thing while skipping the boring stuff, playing with abstractions that scratch my itch.
From this pov, AI is the best thing that has happened to my weekend coding. I code recreationally way more than before. Before AI, I would try a new language or framework, and I’d give up halfway because re-figuring out basic stuff for the umpteenth time is boring, it’s not fun at all. Now AI lets me skip those boring parts.
Learning Elixir and fixing a bug in an open source project went from "risk of a long slog over the course of a month with no reward" to "pepper an LLM with questions (debugging errors, understanding syntax, translating code snippets to English descriptions of behavior), write 20 lines of code by hand, write a few test cases, and submit the PR fix".
I'm still not using AI much, but I'm especially wary of using it to help me with any creative task such as writing or coding. I believe "vibe coding" is the anthesis of hacker culture. What interest I've lost is probably more due to being depressed about the direction I see things heading.
The problem is that coding is often not a very creative task. Its higher levels are creative, some of the details may be creative, but there's still plenty of legwork. In other words, most of our languages are not high-level enough. This is where the AI can be helpful.
I don't use LLMs much for heavy lifting around the code. But it's an almost-excellent tool for research, finding or synthesizing examples, and generating boilerplate where other tools can't do it. "Almost", because LLMs hallucinate more often than I would like, so sometimes I have to cross-check their answers.
As an older "non-developer" it has had the opposite effect. My thirst for creation that I had back in the late 90's early 00's is back. It started slowly, but once I figured out the tooling I created almost 10 applications for myself and work in less than one month. I've done things with my Raspberry Pi I'd never thought possible (without months of tinkering), and I've created apps that bring me both personal pleasure, and workplace productivity.
Quite the opposite: troubleshooting the garbage it spits out helped build confidence in my own capabilities, and now I find myself writing code more frequently than ever - and with more complexity and features than I ever dare attempt before, with no LLM assistance whatsoever.
Nothing like cleaning up someone (or in the case of LLMs, something’s) garbage code to boost ones skill and confidence.
It’s made me lose a lot of interest in reading / watching videos about programming. I enjoy AI for what it enables me to do, but it has changed the landscape of “content” to the point where I spent a lot less time taking in what’s out there since so much is AI related. Have chosen to stop following some channels on youtube / browse HN less.
I've been in growth for dev tools for 20 years now and it's the first time I've struggled to understand what type of content to have produced for y'all - it used to be pretty easy to figure out how to add value (tutorials, interviews, etc) - these days it's less easy to see what folks want - it's hard to do educational content that would land well because folks just talk to an LLM now to learn things. I have budget and I'm unsure exactly where to spend it, so I'd be curious to hear what you'd like to see more of - thank you. :)
1. I no longer write demo code, to prove skills. It's too easily replicated by someone with an AI account.
2. I used to engage small purpose-built DSL's, languages, and systems because they were easy to adopt. Now they're at a strong disadvantage for lack of AI coverage.
3. I focus a lot more on value to the customer; opportunity is now the limiting factor, so I have the product manager hat on most of the time. So I actually do less coding, pruning almost everything that I used to do just to see if I could.
4. I do try harder problems and techniques, because with AI I can typically get to a MVP I can validate and iterate (i.e., it minimizes the stage where nothing is really working). Sometimes it works, and sometimes it just gets blocked; it's more like hunting than gardening or building.
Overall, it's made skills matter less and opportunity/connections matter more, and those are mostly outside my control. That makes it generally de-powering because though I can do much more, the value of what I can do is diminished by a larger factor.
Initially, yes. For me, it took the joy out of development. I was at the point of abandoning it but decided to try some different approaches with it. I think it’s here to stay and felt there had to be some way to leverage it without it making me depressed.
The way I’m using it now I figured out through trial and error. I form a mental model of what I want from start to finish. I then break that down into pieces, and use AI (when appropriate) to generate the code for each piece in sequence. This essentially leaves me in power of the entire development process, but the AI helps me produce the syntax much quicker than I could without it.
It's hard to tell whether it's the result of doing it full-time and I'd rather do other things in my spare time, or whether it's a pre-emptive feeling of already knowing how I'd work through it such that the mystery and tedium I find compelling to grind through is less present.
More ambiguity to me is more interesting, I like the hunt and the iterative process.
That said, it's a choice to use them for hobby projects, and LLMs are sufficiently bad that I'm coming full circle and feeling like their impact on those hobby projects might not be so pronounced. For them to be actually valuable, the process of using them needs to be significantly less tedious and more rewarding, and it's only in a few caes have I had that feeling.
In recent years I've struggled with knowing the details and how to get started. I've had to programme/design in Java, C#, Android, Python, bits of c and c++ all kinds of stuff. In theory now I can write programmes because I know what I want to do but I don't have a good knowledge of all the details so spent too long looking at docs or Stackoverflow. Now in theory I can write useful programs with AI. In some ways this makes me more keen to create and design programs. In other ways this means I don't really need to learn all the details that I didn't learn recently anymore.
Also stuff like leetcode goes away hopefully soon as as long as you understand a data structure and it's benefits you don't have to learn to implement it in every language?
The parts I don't like about coding are figuring out little details, or figuring out 'how to do X thing' that I've never done before when I'm not really sure where to start.
I have fun with the logic and making things work how I want them to work, and getting an end result that I like.
So it's been nice having something I can give details on what I want the end result to be, and getting suggestions on ways to get there. Or just have it figure out silly little issues for me.
AI has increased my interest in programming, because it's made me far more productive and it's quicker to learn new things. I am more creative than ever because I have new avenues.
I use AI 90% for research, learning, and prototyping. It's increased my interest because before, I felt that I didn't have time to do all those things, now I can expand my knowledge so much faster that it makes greater challenges feel more attainable.
The exact opposite: AI has made the mundane go away, so I can focus on the differentiating features.
1. I spend less time fiddling with Flutter/SwiftUI to make things look decent.
2. I don't have to worry about simple data management code much.
3. I learn new things much faster by watching AI does its thing.
AI's coding abilities take care of the mundane so I can focus on the more interesting bits. Plus, it sharpens your code review skills - you have to review the results and adjust as necessary.
Really want to know what these "more interesting bits" are that GPT-5-thinking and other models of this calibre cannot do. Unless of course you choose to do them even though these models can in fact do them, in which case, please do share regardless.
What I've observed the benefits to be: AI chat apps are great at internet searches that can filter out all the nonsense. They are good at transferring algorithms between languages. They're great at knowing common patterns.
I still write all my own code 100%, AI has simply replaced my Google research (ironically using Gemini).
I haven’t been “interested in programming” for decades probably since I started doing it professionally. It was, is and always has been a method to get companies with money to give me some of that money to exchange for food and shelter and to support my hobbies and life outside of work.
I like the design aspect of implementations. But coding has always been drudgery. LLMs have removed a lot of that drudgery. I just test the output and read it for correctness, see if it’s well formed etc.
It's made me uninterested in working in tech professionally, but I still write code on my own without delegating an easy and enjoyable part to a nondeterministic and overconfident junior.
The bits I actually like, I’m still doing. Abstractions, architecture, optimisations. It’s taken away a lot of the boring parts and made troubleshooting much easier. Definitely a net positive for me personally.
Complete opposite. I think Gosucoder said it best; let be badly paraphrase.
AI coding removed the bad part of coding. Lets you handle all the fun part; and you can of course always go and 'code' yourself, you dont have to prompt everything.
The new "developer" skill is ensuring that you're building a reliable app that isnt a house of cards. AI will tend to give you bare minimum. You cant have that, your prompts need to be better.
No. The exact opposite. It makes me hooked to it even more since now I can finally focus on designing the algorithm instead of thinking about releasing memory, converting datatypes, going to stackoverflow to grab the postgresql connection string or whatever. No more calloc/malloc or int to double or pointers. Plus most of the code generated will compile (ok, "will get interpreted" in the case of Python or whatever you see the point) so if you have designed the right algorithm, it's like 90% job done.
Opposite. I'm sickened by boilerplate like a customer service person is sick of call centers. This lets me build the thing without getting too caught up in making some piece of tech happy.
It’s quite the opposite for me.
The fun / creative part for me is not googling “how to slurp the contents of a file into a string” or “the exact syntax for marking some functions as unit tests” or “the correct order of symbols to specify generic type param”
It’s not “the correct html / css syntax for this basic gui I want to make”
It’s not “how to achieve the thing I’ve done 10 thousand times in other languages/frameworks, but for this language/framework”
It’s figuring the core logic out, building the thing while skipping the boring stuff, playing with abstractions that scratch my itch.
From this pov, AI is the best thing that has happened to my weekend coding. I code recreationally way more than before. Before AI, I would try a new language or framework, and I’d give up halfway because re-figuring out basic stuff for the umpteenth time is boring, it’s not fun at all. Now AI lets me skip those boring parts.
Agree that is has been great for weekend coding.
Learning Elixir and fixing a bug in an open source project went from "risk of a long slog over the course of a month with no reward" to "pepper an LLM with questions (debugging errors, understanding syntax, translating code snippets to English descriptions of behavior), write 20 lines of code by hand, write a few test cases, and submit the PR fix".
Yes, but perhaps not in the way you imagine.
I'm still not using AI much, but I'm especially wary of using it to help me with any creative task such as writing or coding. I believe "vibe coding" is the anthesis of hacker culture. What interest I've lost is probably more due to being depressed about the direction I see things heading.
The problem is that coding is often not a very creative task. Its higher levels are creative, some of the details may be creative, but there's still plenty of legwork. In other words, most of our languages are not high-level enough. This is where the AI can be helpful.
I don't use LLMs much for heavy lifting around the code. But it's an almost-excellent tool for research, finding or synthesizing examples, and generating boilerplate where other tools can't do it. "Almost", because LLMs hallucinate more often than I would like, so sometimes I have to cross-check their answers.
As an older "non-developer" it has had the opposite effect. My thirst for creation that I had back in the late 90's early 00's is back. It started slowly, but once I figured out the tooling I created almost 10 applications for myself and work in less than one month. I've done things with my Raspberry Pi I'd never thought possible (without months of tinkering), and I've created apps that bring me both personal pleasure, and workplace productivity.
Quite the opposite: troubleshooting the garbage it spits out helped build confidence in my own capabilities, and now I find myself writing code more frequently than ever - and with more complexity and features than I ever dare attempt before, with no LLM assistance whatsoever.
Nothing like cleaning up someone (or in the case of LLMs, something’s) garbage code to boost ones skill and confidence.
It’s made me lose a lot of interest in reading / watching videos about programming. I enjoy AI for what it enables me to do, but it has changed the landscape of “content” to the point where I spent a lot less time taking in what’s out there since so much is AI related. Have chosen to stop following some channels on youtube / browse HN less.
I've been in growth for dev tools for 20 years now and it's the first time I've struggled to understand what type of content to have produced for y'all - it used to be pretty easy to figure out how to add value (tutorials, interviews, etc) - these days it's less easy to see what folks want - it's hard to do educational content that would land well because folks just talk to an LLM now to learn things. I have budget and I'm unsure exactly where to spend it, so I'd be curious to hear what you'd like to see more of - thank you. :)
It’s because we always sensed an amateur quality to the YouTube creators and LLMs make them appear even more amateur.
1. I no longer write demo code, to prove skills. It's too easily replicated by someone with an AI account.
2. I used to engage small purpose-built DSL's, languages, and systems because they were easy to adopt. Now they're at a strong disadvantage for lack of AI coverage.
3. I focus a lot more on value to the customer; opportunity is now the limiting factor, so I have the product manager hat on most of the time. So I actually do less coding, pruning almost everything that I used to do just to see if I could.
4. I do try harder problems and techniques, because with AI I can typically get to a MVP I can validate and iterate (i.e., it minimizes the stage where nothing is really working). Sometimes it works, and sometimes it just gets blocked; it's more like hunting than gardening or building.
Overall, it's made skills matter less and opportunity/connections matter more, and those are mostly outside my control. That makes it generally de-powering because though I can do much more, the value of what I can do is diminished by a larger factor.
Initially, yes. For me, it took the joy out of development. I was at the point of abandoning it but decided to try some different approaches with it. I think it’s here to stay and felt there had to be some way to leverage it without it making me depressed.
The way I’m using it now I figured out through trial and error. I form a mental model of what I want from start to finish. I then break that down into pieces, and use AI (when appropriate) to generate the code for each piece in sequence. This essentially leaves me in power of the entire development process, but the AI helps me produce the syntax much quicker than I could without it.
It's hard to tell whether it's the result of doing it full-time and I'd rather do other things in my spare time, or whether it's a pre-emptive feeling of already knowing how I'd work through it such that the mystery and tedium I find compelling to grind through is less present.
More ambiguity to me is more interesting, I like the hunt and the iterative process.
That said, it's a choice to use them for hobby projects, and LLMs are sufficiently bad that I'm coming full circle and feeling like their impact on those hobby projects might not be so pronounced. For them to be actually valuable, the process of using them needs to be significantly less tedious and more rewarding, and it's only in a few caes have I had that feeling.
In recent years I've struggled with knowing the details and how to get started. I've had to programme/design in Java, C#, Android, Python, bits of c and c++ all kinds of stuff. In theory now I can write programmes because I know what I want to do but I don't have a good knowledge of all the details so spent too long looking at docs or Stackoverflow. Now in theory I can write useful programs with AI. In some ways this makes me more keen to create and design programs. In other ways this means I don't really need to learn all the details that I didn't learn recently anymore.
Also stuff like leetcode goes away hopefully soon as as long as you understand a data structure and it's benefits you don't have to learn to implement it in every language?
The opposite for me I think.
The parts I don't like about coding are figuring out little details, or figuring out 'how to do X thing' that I've never done before when I'm not really sure where to start.
I have fun with the logic and making things work how I want them to work, and getting an end result that I like.
So it's been nice having something I can give details on what I want the end result to be, and getting suggestions on ways to get there. Or just have it figure out silly little issues for me.
yes, today I can't even write more than 10 line codes manually without the help of claude code as a 10 year experienced developer.
I haven't been as impressed with the AI tools as you seem to be assuming.
No, the opposite.
AI has increased my interest in programming, because it's made me far more productive and it's quicker to learn new things. I am more creative than ever because I have new avenues.
since I can no longer derive self worth by being good at it, I've had to find other hobbies
I use AI 90% for research, learning, and prototyping. It's increased my interest because before, I felt that I didn't have time to do all those things, now I can expand my knowledge so much faster that it makes greater challenges feel more attainable.
Same for me; love it for learning, researching and debating things - programming and software design included :)
It increased my interest because LLMs can explain me something that would usually take days or weeks to research and learn.
The exact opposite: AI has made the mundane go away, so I can focus on the differentiating features.
1. I spend less time fiddling with Flutter/SwiftUI to make things look decent. 2. I don't have to worry about simple data management code much. 3. I learn new things much faster by watching AI does its thing.
AI's coding abilities take care of the mundane so I can focus on the more interesting bits. Plus, it sharpens your code review skills - you have to review the results and adjust as necessary.
Really want to know what these "more interesting bits" are that GPT-5-thinking and other models of this calibre cannot do. Unless of course you choose to do them even though these models can in fact do them, in which case, please do share regardless.
In my case, talking to customers and figuring out what problems they are trying to solve or what opportunities they are wanting to pursue
It made me gain even more interest
No because it's still very bad at it.
What I've observed the benefits to be: AI chat apps are great at internet searches that can filter out all the nonsense. They are good at transferring algorithms between languages. They're great at knowing common patterns.
I still write all my own code 100%, AI has simply replaced my Google research (ironically using Gemini).
A little bit, yeah
Other way around.
I haven’t been “interested in programming” for decades probably since I started doing it professionally. It was, is and always has been a method to get companies with money to give me some of that money to exchange for food and shelter and to support my hobbies and life outside of work.
I like the design aspect of implementations. But coding has always been drudgery. LLMs have removed a lot of that drudgery. I just test the output and read it for correctness, see if it’s well formed etc.
It's made me uninterested in working in tech professionally, but I still write code on my own without delegating an easy and enjoyable part to a nondeterministic and overconfident junior.
Are you kidding? It’s like watching idiots juggling chainsaws. I haven’t been this entertained in years.
The bits I actually like, I’m still doing. Abstractions, architecture, optimisations. It’s taken away a lot of the boring parts and made troubleshooting much easier. Definitely a net positive for me personally.
Complete opposite. I think Gosucoder said it best; let be badly paraphrase.
AI coding removed the bad part of coding. Lets you handle all the fun part; and you can of course always go and 'code' yourself, you dont have to prompt everything.
The new "developer" skill is ensuring that you're building a reliable app that isnt a house of cards. AI will tend to give you bare minimum. You cant have that, your prompts need to be better.
No. The exact opposite. It makes me hooked to it even more since now I can finally focus on designing the algorithm instead of thinking about releasing memory, converting datatypes, going to stackoverflow to grab the postgresql connection string or whatever. No more calloc/malloc or int to double or pointers. Plus most of the code generated will compile (ok, "will get interpreted" in the case of Python or whatever you see the point) so if you have designed the right algorithm, it's like 90% job done.
Opposite. I'm sickened by boilerplate like a customer service person is sick of call centers. This lets me build the thing without getting too caught up in making some piece of tech happy.
Walmart selling plates doesn't make people less interested in pottery. Target selling sweaters doesn't mean people don't like to crochet or knit.