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I can't relate that much to this. Every time I use AI to write code, I'm constantly fighting a feeling on the back of my neck that I need to look over everythin

I can't relate that much to this. Every time I use AI to write code, I'm constantly fighting a feeling on the back of my neck that I need to look over everything it has done and supplement/alter it with my own code. That ick feeling counteracts the dopamine hit of having a working app after a few minutes of vibe coding, and I don't think that's going anywhere anytime soon. That said, I have experience. I could absolutely see myself falling into this as a junior or even mid level dev. I'd no doubt not feel that feeling on my neck if it wasn't scarred from code review lashings early in my career by knowledgeable mentors.

steezeburger 5mo ago
Experience is so so valuable right now. We can guide these agents super well, but I do fear for the juniors as you said. I would like to think I'd use the agents to dive deeper and learn faster. It was pretty rough piecing together solutions from Stack Overflow, various irc channels, Reddit, etc. But also, I cheated on my homework in college and didn't really review the answers, so not sure. Though I pursued programming out of interest and not just to complete a degree. Maybe it would have been different. In any case, I'm glad I came into the LLM era with a lot of experience and failures already.
- hparadiz 5mo ago
  Metrics, profilers, architecture! Use AI to get back to basics! Wanna prove a technique is better? Use AI to make a benchmark! Learn by experimentation! That is my advice to juniors. At the end of the day AI is writing code and there may be 10 different ways to run something. Only one is the fastest in any given use case.
  - chowells 5mo ago
    Fastest is usually the wrong metric. But you'd need experience to know that, I suppose...
    - steezeburger 5mo ago
      I think it's just the wrong metric to optimize for _first_. It's not generally a bad metric to keep tabs on though. Make it work, make it right, make it fast? Or something like that.
    - mikepurvis 5mo ago
      But the point is that LLMs giving you 10x the potential code output doesn't have to mean 10x the code committed. It can also be "let's look at all three possible implementations in more detail and decide which is really the best fit for our situation, and commit that one." That's still 2-3x the velocity, but you get a better result because you went deeper on the paths-not-taken when designing.
      - shimman 5mo ago
        [dead]
  - steezeburger 5mo ago
    Yeah I totally agree! I also think people should still be reading as much code as they can. That's always been true imo. It is just hard to keep up with it now because of how much code an LLM can generate for $20/month. I do think we'll move to higher abstractions of course. We won't have to understand code as much as how the systems and components are architected. It would also be nice to use our new efficiency to return to producing truly optimized and fast software.
- shigawire 5mo ago
  I don't think "cheating" is the right way to frame it. A junior has managers pushing them to do more, faster. You review the code but do you really understand it the same as if you struggled through it? Do you ever build the muscle memory of what works and what doesn't? It is the thought process that builds skills. I've seen some projects trying to be deliberate about learning from the agent as it writes to code - but I'm not sure there is a substitute for struggling and learning by doing.
- svachalek 5mo ago
  When the chainsaw fails the juniors, they're going to be adding wood chippers and stump grinders. The seniors are going to be out there chipping artisanal wood blocks with a hatchet. You don't need a lot of history to see who you really need to be worried about.
  - whattheheckheck 5mo ago
    Its not the internet that needs convincing, its the ones writing the checks
- sarreph 5mo ago
  I think this is one of the key takes right now. I too have similar experience. Which way is it going to go? i) “Seniors” also get superseded by even more capable models that can do all of the things which currently require experience. ii) Linguistics become the new higher order abstraction (English is the new high-level programming language) _but_ there are different / orthogonal ways of approaching software development than the way we do things now — which “juniors” become more adept at more quickly.
  - bigstrat2003 5mo ago
    There's also iii) people realize that if the LLM needs that much babysitting, it doesn't actually add value. So they don't use it very much because it is too limited as a tool.
- nomel 5mo ago
  > Experience is so so valuable right now. And probably the least valued it has ever been.
- usefulcat 5mo ago
  > Experience is so so valuable right now. I think traditional coding experience will be a lot more valuable in 5-10 years, given the apparent inverse relationship between that and LLM usage, and the number of people who seem to already be heavily reliant on LLMs today. The next killer app on the scale of today's LLMs could be an LLM (or call it whatever) that can un-spaghettify the reams of code that are currently being generated by LLMs.
embedding-shape 5mo ago
> after a few minutes of vibe coding Don't vibe-code, it's a joke someone coined in the moment, that somehow the industry decided shouldn't be a joke, and some people think it's a feasible way of developing stuff, it's not. Find a better way of working together with agent, where you get the review what's important to be reviewed by a human, and "outsource" the rest, and you'll end up with code and a design that works the way you'd program it yourself, you just get there faster. I probably end up reviewing maybe 90% of the code that the agent writes, but still it's a hell of a lot more pleasant writing/dictating a few prompts over typing tens of thousands of characters and constantly moving between files. Maybe I'm just tired of typing...
- wahnfrieden 5mo ago
  There are tasks where it is appropriate to vibe code
  - embedding-shape 5mo ago
    Agreed, whenever you're 99% sure you'll throw away the code afterwards.
    - wahnfrieden 5mo ago
      Internal/personal tooling, marketing automations, etc. tend to afford it without needing to throw it out after. These are also cases where you can simply rewrite later without having to address a mountain of debt. If you do this work for a wage and are nearly fully alienated from the value of your labor, I understand the distaste for applying it in any circumstance. You'll care more for your personal experience of the work: how informed you appear when reporting on it to your colleagues, how your boss/colleagues will judge you when an issue arises, how much you feel you are learning from the work, how frustrating it feels to return to items at the behest of others, etc. Vibe coding in these circumstances is unpleasant.
      - embedding-shape 5mo ago
zackify 5mo ago
I agree with your sentiment. I've been trying to get from plan -> complete with AI and it's been working very well in a sandbox. I am trying super hard to give the tools to validate everything to AI. I finish by opening a draft PR and then I go through doing a deep review myself. If I didn't already have 10+ years experience, it would be hard to learn and not atrophy with easy shortcuts being so available. You still need people who know stuff in detail and can own the code... for now
stolen_biscuit 5mo ago
Fully agree. I supplement my game development with AI. Anything novel or interesting I want to do, I need to write the code for myself, otherwise I'm in for a world of hurt. But for the drudgery work that is necessary to invest a lot of time in but boring to actually write, I design a clear architecture and ask AI to do the implementation leg-work. And still you have to go back over and make sure it didn't decide to just create something outlandish. A good recent example is Codex trying to recreate from scratch the behaviour already provided by Area2D in a game I'm making with Godot. If you try and get AI to do anything meaningful, it will be riddled with footguns and bizarre choices. Maybe if you have hundreds of dollars worth of tokens that might not be the case - but for someone who spends $10 a month, it's just not worth the headache. Besides, for me these are hobby projects and writing code is still fun, I just make AI write the boring parts (good examples: saving and loading, parsing of data files and settings menu functionality) - but I keep it away from anything that needs a humans judgement to create.
- promptunit 5mo ago
  [flagged]
- clownpenis_fart 5mo ago
  [dead]
SarikayaKomzin 5mo ago
I have the same feeling on the back of my neck. I think it’s born from my crippling imposter syndrome, which is maybe a super power now.
ryandrake 5mo ago
In my experience, Claude only knows how to spew code. Every problem you want it to solve, it translates into "more code" rather than "less code". You have to very closely code review everything it does, otherwise your codebase is going to just grow and grow, and asymptotically approach 100% debt. I code review everything that Claude produces, and I'd estimate about 90-95% of the time, my reaction is WOW it works but too much code dude, let's take 3 hours to handhold you through simplifying it until nothing more can be removed.
- tailscaler2026 5mo ago
  Of course it writes a lot of code. It gets paid per token. That's guaranteed future income every additional line of technical debt.
  - HoldOnAMinute 5mo ago
    Periodically you can also ask it to review the recent changes and see if there is a risk-free way to streamline them. You can also tell it to periodically summarize the "lessons learned" from the recent session(s)
  - embedding-shape 5mo ago
    Then local models shouldn't suffer from the same problems, but they do. They just aren't trained in the direction of "less code == better long-term maintainability" I'd say, rather than some grand "increased-token-usage" conspiracy. You can certainly steer them a bit to reduce the issue parent talks about, but they still go into that direction whenever they can, adding stuff on top of stuff, piling hacks/shim on top of other hacks/shims, just like many human developers :)
    - bonesss 5mo ago
      Training data is the masses of code from everyone. Restrict that data to just the best of the best, the tersest of the tersest, and we’d see better output. I don’t think people are sharing that kinda stuff (Jane Street’s gems stay locked up), and even if they did my presumption is that it’d be too narrow and demanding for general audiences. Big hopes for the long future, damned to some degree of mediocrity in the near term mass product.
gchamonlive 5mo ago
> I'm constantly fighting a feeling on the back of my neck that I need to look over everything it has done and supplement/alter it with my own code Can relate but the only thing I do different is I teach AI how to cleanup after herself in followup prompts, sessions and refining AGENTS.md. Static code quality analysis tools are also really good to keep the agent on its toes.
aerodexis 5mo ago
Reading and writing are related, but separate activities. One's capability to write code can degrade independently of one's ability to review it.
epolanski 5mo ago
The thing is that you seem to have that luxury to be able to dig more into the problem and scratch that itch. But the industry is changing around you fast. If MIT-bred devs were already building crap in faang before, the trend has been getting nothing short of worse across the industry. Expectations are rising, the field is becoming a rat race of which engineer can output the most mediocre/acceptable/good enough amount of features in the least time as possible. Let me make this clear: you're in an increasingly rarer bubble where you have a luxury that is disappearing in this industry, plain and simple. I have the fortune of having stellar devs around me, people that contributed to projects and software you use every day. They are also outputting magnitude of order more than they ever did, and none of them is getting genuinely better at the craft, but it is what it is.
dclowd9901 5mo ago
I've been using it mostly to bat away yak shaving rabbit holes one can get into when working on a large and complex project. I work mostly on platform work, which is generally nebulous in its feedback loop and testing. Relegating AI to refactoring and building tools to help me research keeps me focused on solving the actual main problem I'm trying to solve, reduces context switching. I really don't understand people who use it to bat out their main focus. I simply don't trust it at that level.
onlyrealcuzzo 5mo ago
> I'm constantly fighting a feeling on the back of my neck that I need to look over everything it has done and supplement/alter it with my own code. On the flip side, I'm working on stuff FAR more challenging than I would ever be able to do on my own. My brain is melting because I can barely keep up with learning how to figure out if I'm even doing what I'm trying to do. AI might be making me a worse coder, but I don't care. If it hasn't "solved" coding now, I'm pretty confident it will long before my career is over. I don't have a job because I can write code - that's a small part of it. I have a job because I can get things to work. Anyone can code things that don't work (especially AI). AI is certainly making me a far better overall engineer. Instead of spending my time trying to make the compiler happy (or fixing dynamic type errors at runtime), I can spend my time trying to solve substantially harder problems that I would never even dare try without an entire team to back me up (i.e. never). Coding - imo - is VERY low on the totem pole of engineering skills. I don't care if the function is pretty. I care if the system is upholding invariants and performing as expected, and there's adequate testing in place to PROVE to me that it ACTUALLY works. High performance concurrent code has always blurred the line between sorcery and arcana... Go didn't really solve that. Rust/Tokio didn't. Zig didn't. C certainly hasn't. It might be easier to prove to yourself, if you're the one doing all the writing, but at the end of the day, code is rarely just for you... You probably should have the same level of proof whether you wrote it yourself and just trust yourself bro, or whether a Chinese Room wrote if for you. I feel like I'm living in a Brave New World, and - at least for the time being - I'm enjoying it, even if it feels like I'm sprinting as fast as I can and still unable to keep up.
- ferngodfather 5mo ago
  > My brain is melting because I can barely keep up with learning how to figure out if I'm even doing what I'm trying to do. This is not a good thing. You should understand what your code does. Writing code nobody can understand is not a flex.
  - onlyrealcuzzo 5mo ago
    > You should understand what your code does. It is not hard to understand what a line of code does... It is hard to keep up with solving the problem I'm trying to solve...
movpasd 5mo ago
I feel the same way, and yet I would still say I feel AI usage atrophying my thinking skills. I feel less tempted to use it to shortcut whole files, but even just using it to speed up looking up and carefully reading docs, tinkering with a library to understand it when docs are inadequate, working out the tradeoffs for design decisions... These sound less objectionable and more like simplr speedups, but when I _do_ need to do it (because the agent refuses to do it properly) I can feel the friction so much more keenly. Whether that's just me losing the habit of those specific tasks, or a generalised loss of g-factor, I don't know.
- 2snakes 5mo ago
  Maybe like a certain blurriness to the edges of those task’s schema? Like becoming a manager or reviewing an intern’s work?
randusername 5mo ago
I really enjoy having the AI write the spec then I write the code. Reviewing code is pain, reviewing requirements and giving feedback feels more productive. I have to confront the full shape of the problem and I usually discover a few cans of worms that make me rethink my approach.
- dualvariable 5mo ago
  Yeah, I'll talk out design with AI in a brainstorming session. Then I'll usually go and implement at least one piece of that. If I get stuck, I'll ask for some help. Then, once I'm happy with it, I'll ask the AI to review what I came up with. Then typically ask it to stamp the pattern around the codebase. And often to just iterate through writing out unit tests. So I just did this for getting dense output from interpolants for an ODE integrator that I maintain. I did the work to make Tsit5 work by hand. I asked AI to stamp out the same pattern for DP5 and BS3, because it was just gene splicing those changes into a very similar RK integrator. I can review the diffs and see that it faithfully stamped out the same pattern with two prompts and a couple of minutes. I'm still maintaining pretty strong contact with the codebase by doing a lot of my own programming, and fighting with the design while I'm writing that first piece of it, but then I use the AI to stamp out the mindlessly repetitive stuff. That just seemed like the obvious way to me to go about programming with AI rather than pure-vibecoding and never touching anything other than prompts. Also, you probably run out of tokens a lot faster if you're pure-vibecoding. Plus you should spend some time debugging your own code. Even if AI could find and fix a bug in a minute or three that would take you 20 minutes, it is generally going to be better for you to burn that 20 minutes on trying to fix it before asking for help. Of course, unlike another poster in this comment thread, I never cheated in college and spent a lot of time on "academic" side projects that weren't part of any course I was taking. Once the vibecoders and cheats are done spamming a billion lines of AI generated code into industry, there's probably going to be positions for people who can (with AI assistance) sort out the mess and get production stable again.
collingreen 5mo ago
Learning from code review lashings is amazing in its effectiveness and minimal blast radius! I'm glad you were able to take that in the easy way. Scar tissue from production going down and staying down is probably powering those code reviews and I think will be teaching this wave of vibe projects a few hard lessons. I've had to learn a few things the hard way like this and it's as effective as it is painful. I'm very pro ai-generated-software in the right context. I think being able to vibe out software as needed is awesome and could finally unlock the potential of our computer and data dominated world. I also think we haven't yet learned as a culture where this new thing is different from traditional software and misunderstanding that is where a lot of the pain will be felt.
svachalek 5mo ago
I'm a very senior dev (32 years exp) but I've got the process nailed down tight enough with .md documents, skills, review agents, etc, that I don't typically have that feeling or any need to do anything extra. I don't think this makes me dumb though, I've just moved up stack. Rather than caring about assembly language or source code, I'm focused on requirements, architectural decisions, engineering process, and ever more automation.
- guelo 5mo ago
  Every engineer to manager has the same thought but after a few years they can barely code.
- skydhash 5mo ago
  Are you the one coding a fix if there's a bug in production? If not, then you do not have the process nailed down.
cyanydeez 5mo ago
I'm using a local model. The code gen is never fast beyond the first few context. As the context grows, it slows down. It's basically it's own self limiting process. When it starts doing things, the threshold of lethargy lowers and triggers me to 'do it myself'; especially, I've developed the understanding of knowledge where it starts doing stupid things and that's valuable. There must be an epistemic problem with just how fast these SOTA models run. I don't think it's just that my local model is dumber, I think it's more that the speed of token gen trains my brain with different expectations. There's no way it'll just generate hundreds of files by itself. When it can via a opencode loop with thought files, letting it run for a day is the only way you get that.
davnicwil 5mo ago
I think this instinct is intrinsic, and comes from really caring about detail and wanting to fully understand it and own it. That's what drives it, and I don't really think the extrinsic things about the way you learned (while helpful) have that much bearing on it. It comes from you and you should take credit for it. I think if you were learning today you'd probably find have the same feeling and do just fine because of it.
cedws 5mo ago
The code that LLMs produce is just average IMO. I wouldn’t call myself an authority on clean code but I can tell when code is well structured. I prefer my hand written code over Claude or GPT’s every time. I once did an experiment where I generated a spec from a project I’d already written, then had an LLM blindly reimplement it from the spec, and compared code. The LLM’s version looked like vomit.
- therealdrag0 5mo ago
  Agree, however in some cases avg code is good enough, especially when refactoring it is just a little attention and more tokens.
98codes 5mo ago
As someone now firmly in the "used to be a developer" part of my career, AI use seems like good old atrophying of the memory muscle of coding. Whether it's because you just don't code anymore at all, or offload that thinking to AI, the effect on you is the same. You start to forget. Don't have AI do anything you want to stay sharp on.
ericmcer 5mo ago
Yesterday it got completely tangled trying to fix a dependency issue across different platforms in react-native. I had to manually undo Claude codes shit, read the docs and install deps in a certain order to make it work correctly. I have no idea what a junior/non-tech person would have done. Like I have wrangled with JS dependencies for 10 years so so I very quickly identified Claude was about to create a tangled nightmare.
stevepotter 5mo ago
I'm the same way, which makes sense because for 20 years I've done things by hand, tediously managing every line. I hired a few fresh grads and they have no problem just going with the default AI output. As long as it works, they are good. For me, it comes down to the ability to properly test. If the code works, is covered by tests, and its performance is measured for regressions, and the high level design is sound, it's hard to argue with vibing. The problem is almost nobody has such a testing system. They are still hard to find and/or build. So that's what I'm putting my effort into because otherwise I'll have trouble sleeping at night (for good reason)

steezeburger 5mo ago

Experience is so so valuable right now. We can guide these agents super well, but I do fear for the juniors as you said. I would like to think I'd use the agents to dive deeper and learn faster. It was pretty rough piecing together solutions from Stack Overflow, various irc channels, Reddit, etc. But also, I cheated on my homework in college and didn't really review the answers, so not sure. Though I pursued programming out of interest and not just to complete a degree. Maybe it would have been different. In any case, I'm glad I came into the LLM era with a lot of experience and failures already.

hparadiz 5mo ago
Metrics, profilers, architecture! Use AI to get back to basics! Wanna prove a technique is better? Use AI to make a benchmark! Learn by experimentation! That is my advice to juniors. At the end of the day AI is writing code and there may be 10 different ways to run something. Only one is the fastest in any given use case.
- chowells 5mo ago
  Fastest is usually the wrong metric. But you'd need experience to know that, I suppose...
  - steezeburger 5mo ago
    I think it's just the wrong metric to optimize for _first_. It's not generally a bad metric to keep tabs on though. Make it work, make it right, make it fast? Or something like that.
  - mikepurvis 5mo ago
    But the point is that LLMs giving you 10x the potential code output doesn't have to mean 10x the code committed. It can also be "let's look at all three possible implementations in more detail and decide which is really the best fit for our situation, and commit that one." That's still 2-3x the velocity, but you get a better result because you went deeper on the paths-not-taken when designing.
    - shimman 5mo ago
      [dead]
- steezeburger 5mo ago
  Yeah I totally agree! I also think people should still be reading as much code as they can. That's always been true imo. It is just hard to keep up with it now because of how much code an LLM can generate for $20/month. I do think we'll move to higher abstractions of course. We won't have to understand code as much as how the systems and components are architected. It would also be nice to use our new efficiency to return to producing truly optimized and fast software.
shigawire 5mo ago
I don't think "cheating" is the right way to frame it. A junior has managers pushing them to do more, faster. You review the code but do you really understand it the same as if you struggled through it? Do you ever build the muscle memory of what works and what doesn't? It is the thought process that builds skills. I've seen some projects trying to be deliberate about learning from the agent as it writes to code - but I'm not sure there is a substitute for struggling and learning by doing.
svachalek 5mo ago
When the chainsaw fails the juniors, they're going to be adding wood chippers and stump grinders. The seniors are going to be out there chipping artisanal wood blocks with a hatchet. You don't need a lot of history to see who you really need to be worried about.
- whattheheckheck 5mo ago
  Its not the internet that needs convincing, its the ones writing the checks
sarreph 5mo ago
I think this is one of the key takes right now. I too have similar experience. Which way is it going to go? i) “Seniors” also get superseded by even more capable models that can do all of the things which currently require experience. ii) Linguistics become the new higher order abstraction (English is the new high-level programming language) _but_ there are different / orthogonal ways of approaching software development than the way we do things now — which “juniors” become more adept at more quickly.
- bigstrat2003 5mo ago
  There's also iii) people realize that if the LLM needs that much babysitting, it doesn't actually add value. So they don't use it very much because it is too limited as a tool.
nomel 5mo ago
> Experience is so so valuable right now. And probably the least valued it has ever been.
usefulcat 5mo ago
> Experience is so so valuable right now. I think traditional coding experience will be a lot more valuable in 5-10 years, given the apparent inverse relationship between that and LLM usage, and the number of people who seem to already be heavily reliant on LLMs today. The next killer app on the scale of today's LLMs could be an LLM (or call it whatever) that can un-spaghettify the reams of code that are currently being generated by LLMs.

embedding-shape 5mo ago

> after a few minutes of vibe coding Don't vibe-code, it's a joke someone coined in the moment, that somehow the industry decided shouldn't be a joke, and some people think it's a feasible way of developing stuff, it's not. Find a better way of working together with agent, where you get the review what's important to be reviewed by a human, and "outsource" the rest, and you'll end up with code and a design that works the way you'd program it yourself, you just get there faster. I probably end up reviewing maybe 90% of the code that the agent writes, but still it's a hell of a lot more pleasant writing/dictating a few prompts over typing tens of thousands of characters and constantly moving between files. Maybe I'm just tired of typing...

wahnfrieden 5mo ago
There are tasks where it is appropriate to vibe code
- embedding-shape 5mo ago
  Agreed, whenever you're 99% sure you'll throw away the code afterwards.
  - wahnfrieden 5mo ago
    Internal/personal tooling, marketing automations, etc. tend to afford it without needing to throw it out after. These are also cases where you can simply rewrite later without having to address a mountain of debt. If you do this work for a wage and are nearly fully alienated from the value of your labor, I understand the distaste for applying it in any circumstance. You'll care more for your personal experience of the work: how informed you appear when reporting on it to your colleagues, how your boss/colleagues will judge you when an issue arises, how much you feel you are learning from the work, how frustrating it feels to return to items at the behest of others, etc. Vibe coding in these circumstances is unpleasant.
    - embedding-shape 5mo ago

zackify 5mo ago

I agree with your sentiment. I've been trying to get from plan -> complete with AI and it's been working very well in a sandbox. I am trying super hard to give the tools to validate everything to AI. I finish by opening a draft PR and then I go through doing a deep review myself. If I didn't already have 10+ years experience, it would be hard to learn and not atrophy with easy shortcuts being so available. You still need people who know stuff in detail and can own the code... for now

stolen_biscuit 5mo ago

Fully agree. I supplement my game development with AI. Anything novel or interesting I want to do, I need to write the code for myself, otherwise I'm in for a world of hurt. But for the drudgery work that is necessary to invest a lot of time in but boring to actually write, I design a clear architecture and ask AI to do the implementation leg-work. And still you have to go back over and make sure it didn't decide to just create something outlandish. A good recent example is Codex trying to recreate from scratch the behaviour already provided by Area2D in a game I'm making with Godot. If you try and get AI to do anything meaningful, it will be riddled with footguns and bizarre choices. Maybe if you have hundreds of dollars worth of tokens that might not be the case - but for someone who spends $10 a month, it's just not worth the headache. Besides, for me these are hobby projects and writing code is still fun, I just make AI write the boring parts (good examples: saving and loading, parsing of data files and settings menu functionality) - but I keep it away from anything that needs a humans judgement to create.

promptunit 5mo ago
[flagged]
clownpenis_fart 5mo ago
[dead]

SarikayaKomzin 5mo ago

I have the same feeling on the back of my neck. I think it’s born from my crippling imposter syndrome, which is maybe a super power now.

ryandrake 5mo ago

In my experience, Claude only knows how to spew code. Every problem you want it to solve, it translates into "more code" rather than "less code". You have to very closely code review everything it does, otherwise your codebase is going to just grow and grow, and asymptotically approach 100% debt. I code review everything that Claude produces, and I'd estimate about 90-95% of the time, my reaction is WOW it works but too much code dude, let's take 3 hours to handhold you through simplifying it until nothing more can be removed.

tailscaler2026 5mo ago
Of course it writes a lot of code. It gets paid per token. That's guaranteed future income every additional line of technical debt.
- HoldOnAMinute 5mo ago
  Periodically you can also ask it to review the recent changes and see if there is a risk-free way to streamline them. You can also tell it to periodically summarize the "lessons learned" from the recent session(s)
- embedding-shape 5mo ago
  Then local models shouldn't suffer from the same problems, but they do. They just aren't trained in the direction of "less code == better long-term maintainability" I'd say, rather than some grand "increased-token-usage" conspiracy. You can certainly steer them a bit to reduce the issue parent talks about, but they still go into that direction whenever they can, adding stuff on top of stuff, piling hacks/shim on top of other hacks/shims, just like many human developers :)
  - bonesss 5mo ago
    Training data is the masses of code from everyone. Restrict that data to just the best of the best, the tersest of the tersest, and we’d see better output. I don’t think people are sharing that kinda stuff (Jane Street’s gems stay locked up), and even if they did my presumption is that it’d be too narrow and demanding for general audiences. Big hopes for the long future, damned to some degree of mediocrity in the near term mass product.

gchamonlive 5mo ago

> I'm constantly fighting a feeling on the back of my neck that I need to look over everything it has done and supplement/alter it with my own code Can relate but the only thing I do different is I teach AI how to cleanup after herself in followup prompts, sessions and refining AGENTS.md. Static code quality analysis tools are also really good to keep the agent on its toes.

aerodexis 5mo ago

Reading and writing are related, but separate activities. One's capability to write code can degrade independently of one's ability to review it.

epolanski 5mo ago

The thing is that you seem to have that luxury to be able to dig more into the problem and scratch that itch. But the industry is changing around you fast. If MIT-bred devs were already building crap in faang before, the trend has been getting nothing short of worse across the industry. Expectations are rising, the field is becoming a rat race of which engineer can output the most mediocre/acceptable/good enough amount of features in the least time as possible. Let me make this clear: you're in an increasingly rarer bubble where you have a luxury that is disappearing in this industry, plain and simple. I have the fortune of having stellar devs around me, people that contributed to projects and software you use every day. They are also outputting magnitude of order more than they ever did, and none of them is getting genuinely better at the craft, but it is what it is.

dclowd9901 5mo ago

I've been using it mostly to bat away yak shaving rabbit holes one can get into when working on a large and complex project. I work mostly on platform work, which is generally nebulous in its feedback loop and testing. Relegating AI to refactoring and building tools to help me research keeps me focused on solving the actual main problem I'm trying to solve, reduces context switching. I really don't understand people who use it to bat out their main focus. I simply don't trust it at that level.

onlyrealcuzzo 5mo ago

> I'm constantly fighting a feeling on the back of my neck that I need to look over everything it has done and supplement/alter it with my own code. On the flip side, I'm working on stuff FAR more challenging than I would ever be able to do on my own. My brain is melting because I can barely keep up with learning how to figure out if I'm even doing what I'm trying to do. AI might be making me a worse coder, but I don't care. If it hasn't "solved" coding now, I'm pretty confident it will long before my career is over. I don't have a job because I can write code - that's a small part of it. I have a job because I can get things to work. Anyone can code things that don't work (especially AI). AI is certainly making me a far better overall engineer. Instead of spending my time trying to make the compiler happy (or fixing dynamic type errors at runtime), I can spend my time trying to solve substantially harder problems that I would never even dare try without an entire team to back me up (i.e. never). Coding - imo - is VERY low on the totem pole of engineering skills. I don't care if the function is pretty. I care if the system is upholding invariants and performing as expected, and there's adequate testing in place to PROVE to me that it ACTUALLY works. High performance concurrent code has always blurred the line between sorcery and arcana... Go didn't really solve that. Rust/Tokio didn't. Zig didn't. C certainly hasn't. It might be easier to prove to yourself, if you're the one doing all the writing, but at the end of the day, code is rarely just for you... You probably should have the same level of proof whether you wrote it yourself and just trust yourself bro, or whether a Chinese Room wrote if for you. I feel like I'm living in a Brave New World, and - at least for the time being - I'm enjoying it, even if it feels like I'm sprinting as fast as I can and still unable to keep up.

ferngodfather 5mo ago
> My brain is melting because I can barely keep up with learning how to figure out if I'm even doing what I'm trying to do. This is not a good thing. You should understand what your code does. Writing code nobody can understand is not a flex.
- onlyrealcuzzo 5mo ago
  > You should understand what your code does. It is not hard to understand what a line of code does... It is hard to keep up with solving the problem I'm trying to solve...

movpasd 5mo ago

I feel the same way, and yet I would still say I feel AI usage atrophying my thinking skills. I feel less tempted to use it to shortcut whole files, but even just using it to speed up looking up and carefully reading docs, tinkering with a library to understand it when docs are inadequate, working out the tradeoffs for design decisions... These sound less objectionable and more like simplr speedups, but when I _do_ need to do it (because the agent refuses to do it properly) I can feel the friction so much more keenly. Whether that's just me losing the habit of those specific tasks, or a generalised loss of g-factor, I don't know.

2snakes 5mo ago
Maybe like a certain blurriness to the edges of those task’s schema? Like becoming a manager or reviewing an intern’s work?

randusername 5mo ago

I really enjoy having the AI write the spec then I write the code. Reviewing code is pain, reviewing requirements and giving feedback feels more productive. I have to confront the full shape of the problem and I usually discover a few cans of worms that make me rethink my approach.

dualvariable 5mo ago
Yeah, I'll talk out design with AI in a brainstorming session. Then I'll usually go and implement at least one piece of that. If I get stuck, I'll ask for some help. Then, once I'm happy with it, I'll ask the AI to review what I came up with. Then typically ask it to stamp the pattern around the codebase. And often to just iterate through writing out unit tests. So I just did this for getting dense output from interpolants for an ODE integrator that I maintain. I did the work to make Tsit5 work by hand. I asked AI to stamp out the same pattern for DP5 and BS3, because it was just gene splicing those changes into a very similar RK integrator. I can review the diffs and see that it faithfully stamped out the same pattern with two prompts and a couple of minutes. I'm still maintaining pretty strong contact with the codebase by doing a lot of my own programming, and fighting with the design while I'm writing that first piece of it, but then I use the AI to stamp out the mindlessly repetitive stuff. That just seemed like the obvious way to me to go about programming with AI rather than pure-vibecoding and never touching anything other than prompts. Also, you probably run out of tokens a lot faster if you're pure-vibecoding. Plus you should spend some time debugging your own code. Even if AI could find and fix a bug in a minute or three that would take you 20 minutes, it is generally going to be better for you to burn that 20 minutes on trying to fix it before asking for help. Of course, unlike another poster in this comment thread, I never cheated in college and spent a lot of time on "academic" side projects that weren't part of any course I was taking. Once the vibecoders and cheats are done spamming a billion lines of AI generated code into industry, there's probably going to be positions for people who can (with AI assistance) sort out the mess and get production stable again.

collingreen 5mo ago

Learning from code review lashings is amazing in its effectiveness and minimal blast radius! I'm glad you were able to take that in the easy way. Scar tissue from production going down and staying down is probably powering those code reviews and I think will be teaching this wave of vibe projects a few hard lessons. I've had to learn a few things the hard way like this and it's as effective as it is painful. I'm very pro ai-generated-software in the right context. I think being able to vibe out software as needed is awesome and could finally unlock the potential of our computer and data dominated world. I also think we haven't yet learned as a culture where this new thing is different from traditional software and misunderstanding that is where a lot of the pain will be felt.

svachalek 5mo ago

I'm a very senior dev (32 years exp) but I've got the process nailed down tight enough with .md documents, skills, review agents, etc, that I don't typically have that feeling or any need to do anything extra. I don't think this makes me dumb though, I've just moved up stack. Rather than caring about assembly language or source code, I'm focused on requirements, architectural decisions, engineering process, and ever more automation.

guelo 5mo ago
Every engineer to manager has the same thought but after a few years they can barely code.
skydhash 5mo ago
Are you the one coding a fix if there's a bug in production? If not, then you do not have the process nailed down.

cyanydeez 5mo ago

I'm using a local model. The code gen is never fast beyond the first few context. As the context grows, it slows down. It's basically it's own self limiting process. When it starts doing things, the threshold of lethargy lowers and triggers me to 'do it myself'; especially, I've developed the understanding of knowledge where it starts doing stupid things and that's valuable. There must be an epistemic problem with just how fast these SOTA models run. I don't think it's just that my local model is dumber, I think it's more that the speed of token gen trains my brain with different expectations. There's no way it'll just generate hundreds of files by itself. When it can via a opencode loop with thought files, letting it run for a day is the only way you get that.

davnicwil 5mo ago

I think this instinct is intrinsic, and comes from really caring about detail and wanting to fully understand it and own it. That's what drives it, and I don't really think the extrinsic things about the way you learned (while helpful) have that much bearing on it. It comes from you and you should take credit for it. I think if you were learning today you'd probably find have the same feeling and do just fine because of it.

cedws 5mo ago

The code that LLMs produce is just average IMO. I wouldn’t call myself an authority on clean code but I can tell when code is well structured. I prefer my hand written code over Claude or GPT’s every time. I once did an experiment where I generated a spec from a project I’d already written, then had an LLM blindly reimplement it from the spec, and compared code. The LLM’s version looked like vomit.

therealdrag0 5mo ago
Agree, however in some cases avg code is good enough, especially when refactoring it is just a little attention and more tokens.

98codes 5mo ago

As someone now firmly in the "used to be a developer" part of my career, AI use seems like good old atrophying of the memory muscle of coding. Whether it's because you just don't code anymore at all, or offload that thinking to AI, the effect on you is the same. You start to forget. Don't have AI do anything you want to stay sharp on.

ericmcer 5mo ago

Yesterday it got completely tangled trying to fix a dependency issue across different platforms in react-native. I had to manually undo Claude codes shit, read the docs and install deps in a certain order to make it work correctly. I have no idea what a junior/non-tech person would have done. Like I have wrangled with JS dependencies for 10 years so so I very quickly identified Claude was about to create a tangled nightmare.

stevepotter 5mo ago

I'm the same way, which makes sense because for 20 years I've done things by hand, tediously managing every line. I hired a few fresh grads and they have no problem just going with the default AI output. As long as it works, they are good. For me, it comes down to the ability to properly test. If the code works, is covered by tests, and its performance is measured for regressions, and the high level design is sound, it's hard to argue with vibing. The problem is almost nobody has such a testing system. They are still hard to find and/or build. So that's what I'm putting my effort into because otherwise I'll have trouble sleeping at night (for good reason)