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The disconnect for AI is that it is a jagged frontier and it only really shines when one of its jagged frontiers extends counter to one of your valleys. If you

by u8 4mo ago

The disconnect for AI is that it is a jagged frontier and it only really shines when one of its jagged frontiers extends counter to one of your valleys. If you've been writing Perl for 30 years, you might not want to learn JavaScript just to make a little fun idea in your head to show your wife. Vibe code that shit man. Who cares? Your wife does not care about LOC or those internal design decisions you made. If you're trying to learn something new like an algorithm, protocol, or API write that shit by hand. You learn by doing, and when you know how the thing works and have that mental context, you will always be faster than an AI. Also, when did we stop liking to learn? Why is it a bad thing to know all the ins and outs of a programming language? To write and make all the decisions yourself? That shit is fun. I don't care if you disagree. If you're at work and they really care about getting something out of the door, do whatever you think is best. If you just wanna ship vibed code and review PRs all day, all the power to you. If you wanna write it by hand, and use AI like a scalpel to write up boiler plate, review code, do PR audits, etc... go for it! A hammer is a really great tool that has thousands of purpose-designed uses. I still prefer my key to get into my car. It's all tools, you are a person. A lot of this stuff if coming top-down from people who do not have the experience you do. Wouldn't a smart employee use their expertise to advise the organization? If you work at a company where that would not be okay, maybe it's time to start looking for another firm.

bananaboy 4mo ago
100% agree!
rimmontrieu 4mo ago
Some people actually don't really like to learn new things. If the machine spits out plausible working code, they'd be perfectly happy with that. Personally I think AI is doing a lot more harm than good and I can't wait for the bubble to burst.
- skeledrew 4mo ago
  Let those who want to learn go learn. And let those who just want something that works well enough without having to learn get it.
- justech 4mo ago
  I don’t think it’s going to burst like how other people expect. The technology is already out there, when it loses steam people aren’t suddenly going to stop using it. I predit it’ll be more like the dot come crash where companies that can survive the downturn come out dominant.
  - kyykky 4mo ago
    It ends like this: all codebases become unmaintainable spaghetti after agentic AI spends years on it. Then after every agent in existence will spend minimum 24 hours reading the codebase to add a simple feature, the software is abandoned.
    - necovek 4mo ago
      I believe most codebases were "unmaintainable spaghetti" even before LLMs: depends on how you define it though. To be, it means expensive to evolve.
    - r4nd0m4ch 4mo ago
      no way it's going to happen
- hirvi74 4mo ago
  To use an analogy, LLMs are like the Ring of Power in Lord of the Rings. The Ring of Power does not corrupt one nor does it magically turn one evil. Rather, the Ring just serves as a catalyst for what is already inside the bearer. Many that wore the Ring had pure and righteous intentions. The thought of, "If I were in power, I would..." was the arrogance and corruption which the Ring amplifies. So, I cannot agree that it is AI doing the harm. Rather, AI just gives us the power to do the harm, the shortcuts, the cheats, etc. we have always desired. And just like the Ring, I believe much of the harm from LLMs often comes from people that started with good intentions, and the power it grants is just too tempting for many.
Xeronate 4mo ago
When I started spending 40-60 hours a week programming and wanted to spend my remaining time doing other things.
- hirvi74 4mo ago
  I imagine my future will involve spending 40–60 hours a week using LLMs to do the work of multiple roles instead of just one, while wishing I could spend my remaining time doing other things.
jesterson 4mo ago
> Why is it a bad thing to know all the ins and outs of a programming language? To write and make all the decisions yourself? That shit is fun. It's not just fun (i agree it is), but it is also essential for creation. What we have done with the 'AI' is to create a lot of ignorant morons who think they can create a lot of things without knowledge. This is not gonna end well.
- zx8080 4mo ago
  > they can create a lot of things without knowledge. This is not gonna end well. Who said "managers"
  - jesterson 4mo ago
    Oh managers are not the biggest evil here. At least they know basics. Now we have influx of people with not a single shred of technical knowledge thinking they can create something.
brentcrude 4mo ago
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jacktu 4mo ago
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allthetime 4mo ago
AI is just revealing the two types of people in this line of work. Those who don’t actually like software and just do it because it’s lucrative, and the actual nerds who care.
- tyyyy3 4mo ago
  Can we build a list of the actual nerds who care? Need it for my future recruitment needs lol.
  - andai 4mo ago
    The benchmark is "do they do it for fun", i.e. personal projects. But the real trick isn't "number of personal projects", but how weird they are. There's no "rational" reason to do them, they don't increase the person's marketability / hireability. They are done purely for intrinsic reasons. (On reflection, this also seems to be a pretty robust predictor of autism. :)
- eli 4mo ago
  A much more charitable framing: people who enjoy the process vs people who enjoy the result. (Though, granted, the results are a lot better if you craft it by hand)
  - Daishiman 4mo ago
    I am not really sure. I wrote some scripts that aggregated data from several APIs with an LLM and the LLM had the foresight to create a caching layer for the API responses as it properly inferred that I would need the results over and over again as well as using asyncio to accelerate fetch speed. This would have been a v2 or v3 and it one-shotted it perfectly.
    - anygivnthursday 4mo ago
      Yeah, they are good at applying generic patterns, but often it can be overkill/YAGNI that lead to more maintenance work in places that are fine with a much simpler/straightforward solution. But this is what the engineer can decide and with LLMs they wont be forced to make the trade off because it takes longer to build, but rather whether it is really necessary or not.
ditchfieldcaleb 4mo ago
I agree with you on everything you said here except: > when you know how the thing works and have that mental context, you will always be faster than an AI That's just plain false, honestly. No one can type at the speed AI can code, even factoring in the time you need to spend to properly write out the spec & design rules the AI needs to follow when implementing your app/feature/whatever. And that gap will only increase as LLMs get more intelligent.
- nullsanity 4mo ago
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- JSR_FDED 4mo ago
  It should be “…you will always be faster than someone _without the knowledge_ using an AI”
- leostarship 4mo ago
  as i understood it he's referring to the overall time it takes to build a complete finished piece of software, accounting for the refactoring and bug fixes and all that. cause handn't you understood the tools you're using you would be running into roadblocks and that adds up
  - deleted 4mo ago
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- notnullorvoid 4mo ago
  Some of us do actually have intimate knowledge in certain areas where guidance of an AI takes longer than doing it yourself. It's not about typing speed, it's that when you know something really really well the solution/code is already known to you or the very act of thinking about the problem makes the solution known to you in full. When that happens it's less text to write that solution than it is to write a sufficient description of the solution to AI (not even counting the back and forth required of reviewing the AI output and correcting it).
jtr1 4mo ago
I have been building an iOS app that I had kicking around in my head for years but never had time to build. I have been a frontend UX engineer for the better part of a decade and went through a handful of tutorials on Swift. The project definitely sits in this uncanny valley for me. I have test suites for every aspect of the app and have the agent using TDD to avoid cheating - this has gotten me pretty far without having to look too close at the output other than general structure. As I'm reaching a more mature stage of the project though, I'm finding that I want to tweak a lot by hand in the code to get the details right without burning tokens.
- throwaway219450 4mo ago
  The agents always do the best work IMO if you already know exactly what you want, but are too lazy to implement it. I like having the agent mock up a working solution before reimplementing it. To split the difference, I now try to hand code as much as I can from the beginning, leave TODO comments for the agent to mop up and I'll ask it to complete the issue with reference to the current diff. It reduces the surface for agents to make stupid assumptions. If I can get it done fast on my own, win for me, if the agent finds issues or there's logic that needs checking, also a win. This way you stay sharp, but you have access to an oracle if you get stuck and it costs you fewer tokens.
  - jtr1 4mo ago
    Yeah, I like the "get out of jail free" card approach. The thing I always used to hate before this era was getting stuck in a hole on something that would take days or worse to grind through. It's nice to drop a little plank bridge across those now
deleted 4mo ago
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nbvkappowqpeop 4mo ago
thanks for this take, articulates what i've been feeling towards "AI" without my angst
Finbel 4mo ago
>Also, when did we stop liking to learn? Why is it a bad thing to know all the ins and outs of a programming language? I do not know the inns and out of the assembly layer my high level code end up as. It's not because I don't like to learn, it's because I genuinely don't need to. At a certain level of AI performance, how will this be any different?
- californical 4mo ago
  Because you may not know the specifics of the assembly being generated, but you’ve likely learned a language built on top of assembly. And the compilers do some great tricks behind the scenes to generate efficient assembly, but those tricks are specifically coupled to semantics of the source language. An LLM is not coupled to anything and can generate output that simply does not relate to the input. This doesn’t happen with compilers, and if it does, then it’s a specific bug to be addressed. An LLM can never guarantee certain output based on the input. If I write x < 100, I know exactly how the compiler will treat that code every single time, and I know what < means and how it differs from <= If I tell an LLM that “I want numbers up to 100.” Will that give me < or <= and will it be consistent every single time, even the ten thousandth program that I write? The language is ambiguous where the code is specific
  - Finbel 4mo ago
    To me this is semantics as far as it's related to "why don't you want to learn?" I have a co-worker in another team that write java endpoins we consume. I can tell him what I need and I trust the output. I don't need to know java to trust him, it doesn't mean I don't want to learn. There are thousand examples like this across every stack and abstraction level. From ssh-handshakes to gps. Sure my co-worker is fundamentally different from a compiler which is fundamentally different from an LLM. My argument is that the chain-of-trust where you offload knowledge to an external source is identical. We do it all the time but somehow doing it with an LLM means we no longer want to learn?
- sdevonoes 4mo ago
  One difference is: to use a top notch compiler/assembler you don’t need to pay. They are open source and have a lot of support. To use the latest and greatest models (bc no one around likes to use non sota ones) you need to pay a premium price. Multibillion dollars companies are now the gateway for every line of code you need to write. That’s dystopian. It sucks
imrozim 4mo ago
100% aggred, i learn coding by building stuff and breaking it when you let ai do everything you skip that pain and also skip the understanding.
pjmlp 4mo ago
Except those are the same people that will decide who is getting hired, and who gets layoff because of increasing productivity. And no, this isn't playing what ifs. I have seen it happening with offshoring, migration to cloud, serverless, SaaS and iPaaS products, and now AI powered automations via agents. Less devops people, less backend devs , no translation team, no asset creation team,... I have been layoff a few times, having to do competence transfer to offshoring teams, the quality of the output is something c suites don't care all. Do you wanna bet what is behind Microslop, Apple Tahoe bugs and so forth?
rufasterisco 4mo ago
Let’s see if someone can point me towards some resources over the following. The problem is mixing vibe-coding and agentic-eng, and switching the brain in 2 different modes (fast-feedback gratification vs deep-focus gratification). There’s no clear cut rule on what works. Different people, different brains, and especially amongst devs some optimized low-key neurodivergence. And then there’s waiting mode, those N seconds/minutes that agents take to think and write. What’s the right mix? Keep a main focused project and … what do you do in the meantime? Vibe code something else? Hn? Social media? Draw lines on a paper sheet? Wood carving? Exercise? Rewatch some old tv series? I have experimented…. There are side activities that help you go back to the task at hand in the correct mental framework for it. Not just for productivity, but for efficiency and enhancing critical thinking on the main task. Or whatever you choose to optimize for. Can anyone point me towards some people talking about this?
sdevonoes 4mo ago
Agree except for this part > If you're at work and they really care about getting something out of the door, do whatever you think is best. If you don’t mind being jobless, sure do whatever you think is best. Not all of us can simply switch companies easily. Folks need to realise that AI in a company setting works for the benefit of the company, not for the individual.
- 0xpgm 4mo ago
  But do companies really know how to use AI? I think most of it is experimentation - throwing things to the wall and seeing what sticks. It's the practitioner who eventually figures out what really works. I see this the same way the agile movement emerged. It was initiated by people who were hands-on programmers and showed enough benefit at minimizing software waste before it took a life of its own and started getting peddled by people who didn't really understand the underlying principles.
  - dpoloncsak 4mo ago
    > I think most of it is experimentation - throwing things to the wall and seeing what sticks. This is true in macro, but I think we're specifically referring to LLM-generated /assisted code (vibe-coding). 'Getting something out the door' is not an necessarily in reference to an AI-infused product, just new code written by AI
NikolaosC 4mo ago
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IanCal 4mo ago
Fundamentally you need to start with "what am I trying to do?" and "given that goal, where is my time best spent?". I made a checklist for my kids to stamp off items after they get back from school (sort bag, get changed, etc). I had two goals, 1) I was trying to solve a problem at home and would have pip installed a library that just straight up did this already and 2) I wanted to check out what the claude website outputs was like at the time. My time was best spent poking at claude a bit but mostly playing with my kids - so vibe coding it was. Client test speedup issues, I'm trying to speed up tests for them and spend as little time as possible doing so. Vibe coded some analysis and visualisation tools, mostly AI but with some review guided multiple prototypes for timing and let it just fix whatever. More dedicated review for the actual solutions. Learning a new thing - goal is to learn that thing. AI there is good for doing a lot of the work around that. Maybe I'm focussing on, say, Z3. AI there can help with debugging, finding docs, setting up an environment and leave me to do the central part.
aimiraclemag 4mo ago
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deleted 4mo ago
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latexr 4mo ago
> Also, when did we stop liking to learn? I suspect it happened when we achieved a level of such constant stimulation (there is a pocket computer always on us with infinite effortless distraction) that we’re never bored and never engage the default mode network. https://en.wikipedia.org/wiki/Default_mode_network https://en.wikipedia.org/wiki/Default_mode_network https://www.youtube.com/watch?v=orQKfIXMiA8 https://www.youtube.com/watch?v=orQKfIXMiA8 When you’re bored, your mind goes to places it wouldn’t otherwise go. Curiosity kicks in. Curiosity is a precursor to learning. Learning engages the brain and is fun. But it’s not fun all the time, some of it is challenging and frustrating (which is good, that’s the process that teaches you). When you have the digital equivalent to infinite candy and the brain equivalent to a sweet tooth, it’s hard to resist the siren’s call. The consequence is the brain equivalent to a stomachache—depression and loss of meaning—but unfortunately it doesn’t hit you the same way so you don’t make the immediate connection to make yourself stop. When you think about it, it’s ridiculous from several angles: the candy is infinite, it’s never going to run out, so you don’t need to gorge! But then we justify ourselves as only a true addict would, that while the candy is infinite, the flavours are limited editions and always rotating, and what if I miss that really good one everyone is on?! Then you miss it, is the answer. No one will be talking about it in fifteen minutes anyway.
- AStrangeMorrow 4mo ago
  I still love learning, especially outside of tech. Been working in the ML field for over 8 years, and while I went into it because I liked the field, I did lose some interest in learning things, but mostly because of the sheer volume of publication and the rate of change. Learning stopped being something I enjoyed doing and went to something I had to do to keep up. And it just stopped having the same flavor.
- gchamonlive 4mo ago
  > it happened when we achieved a level of such constant stimulation (...) that we’re never bored and never engage the default mode network. I don't know... I don't disagree, but I think this has been repeated so much that I believe everyone, at least everyone that is actively participating in HN discussions is aware of this. So if we are aware of this and we consciously choose to keep engaging in dopaminergic activities, without having some time to be bored, I think it starts to become a choice. We can blame tech for starting this trend of stealing our attention, but once we become aware of this, we can only blame ourselves for perpetuating it.
maxsilver 4mo ago
> Also, when did we stop liking to learn? When the economy got so bad for so many people, that every waking moment has to be either chasing fresh cash (or spent in recovery from cash-chasing, worrying about new cash), to the point they have to largely ignore their own long term goals or basic morals or principles. You can blame all the new gadgets (phones/social media/tiktok/‘dopamine-things’) — but it’s a very much blaming the symptom, not the problem. (It’s the meme. “Guys, this isn’t funny. Humans only do this when they’re very distressed”)
eloisant 4mo ago
Exactly, I'm a back-end engineer and I vibe-coded that in a couple of hours: https://erwan.github.io/sovereign-cards-database/ https://erwan.github.io/sovereign-cards-database/ I could have learn all the frameworks to make it, but honestly I wouldn't have bothered.
throwaway613746 4mo ago
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dpoloncsak 4mo ago
Just here to say I love the line 'A hammer is a really great tool that has thousands of purpose-designed uses. I still prefer my key to get into my car.' Been saying the 'Hammer is a great tool but you need to know when to use it, just like AI.' to coworkers, and i'm ̶s̶t̶e̶a̶l̶i̶n̶g̶ borrowing your quote instead, now
miki123211 4mo ago
In my view, AI is worst at crossing the rubicon from a 200-line script to a maintainable architecture of ~10kloc. If you already have a decent architecture, adding a new feature is usually fine. If you have nothing and need it to write a 200-line script, that's usually fine. If you need it to figure out a maintainable architecture that will be easy to extend in the future... that;'s where the problems start.
- esafak 4mo ago
  You need to be involved in the architecture.
throwanem 4mo ago
> Also, when did we stop liking to learn? When it got dangerous to spend that kind of time without a bullet-point deliverable.
kreneskyp 4mo ago
> If you're trying to learn something new like an algorithm, protocol, or API write that shit by hand. You learn by doing, and when you know how the thing works and have that mental context, you will always be faster than an AI. Also, when did we stop liking to learn? I vibe engineer to learn. I am currently doing this with a project to build a Vector DB extension in postgres. Several aspects of this project are very new to me. I don't write any of the code. I have never written a single line of Rust. I do, however, spend a significant amount of time discussing architecture and design with the agents. I started with well known algorithms (HNSW, IVF, DiskANN, TurboQuant, RabitQ, PQFastScan) and have since moved on to a novel implementation based on fairly recent research papers. My primary goal is to learn. That is a success and ongoing. A stretch goal is to contribute novel ideas back to the community, which may be useful even if what I build isn't ever production ready.
dirtbag__dad 4mo ago
> Also, when did we stop liking to learn? Says who? One of the most enriching things about coding with agents is I have them provide new information, tools, patterns, whatever as a follow up to every feature I work on. I’m learning a ton and it’s helping me build better with agents, too.

by u8 4mo ago

bananaboy 4mo ago

100% agree!

rimmontrieu 4mo ago

Some people actually don't really like to learn new things. If the machine spits out plausible working code, they'd be perfectly happy with that. Personally I think AI is doing a lot more harm than good and I can't wait for the bubble to burst.

skeledrew 4mo ago
Let those who want to learn go learn. And let those who just want something that works well enough without having to learn get it.
justech 4mo ago
I don’t think it’s going to burst like how other people expect. The technology is already out there, when it loses steam people aren’t suddenly going to stop using it. I predit it’ll be more like the dot come crash where companies that can survive the downturn come out dominant.
- kyykky 4mo ago
  It ends like this: all codebases become unmaintainable spaghetti after agentic AI spends years on it. Then after every agent in existence will spend minimum 24 hours reading the codebase to add a simple feature, the software is abandoned.
  - necovek 4mo ago
    I believe most codebases were "unmaintainable spaghetti" even before LLMs: depends on how you define it though. To be, it means expensive to evolve.
  - r4nd0m4ch 4mo ago
    no way it's going to happen
hirvi74 4mo ago
To use an analogy, LLMs are like the Ring of Power in Lord of the Rings. The Ring of Power does not corrupt one nor does it magically turn one evil. Rather, the Ring just serves as a catalyst for what is already inside the bearer. Many that wore the Ring had pure and righteous intentions. The thought of, "If I were in power, I would..." was the arrogance and corruption which the Ring amplifies. So, I cannot agree that it is AI doing the harm. Rather, AI just gives us the power to do the harm, the shortcuts, the cheats, etc. we have always desired. And just like the Ring, I believe much of the harm from LLMs often comes from people that started with good intentions, and the power it grants is just too tempting for many.

Xeronate 4mo ago

When I started spending 40-60 hours a week programming and wanted to spend my remaining time doing other things.

hirvi74 4mo ago
I imagine my future will involve spending 40–60 hours a week using LLMs to do the work of multiple roles instead of just one, while wishing I could spend my remaining time doing other things.

jesterson 4mo ago

> Why is it a bad thing to know all the ins and outs of a programming language? To write and make all the decisions yourself? That shit is fun. It's not just fun (i agree it is), but it is also essential for creation. What we have done with the 'AI' is to create a lot of ignorant morons who think they can create a lot of things without knowledge. This is not gonna end well.

zx8080 4mo ago
> they can create a lot of things without knowledge. This is not gonna end well. Who said "managers"
- jesterson 4mo ago
  Oh managers are not the biggest evil here. At least they know basics. Now we have influx of people with not a single shred of technical knowledge thinking they can create something.

brentcrude 4mo ago

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jacktu 4mo ago

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allthetime 4mo ago

AI is just revealing the two types of people in this line of work. Those who don’t actually like software and just do it because it’s lucrative, and the actual nerds who care.

tyyyy3 4mo ago
Can we build a list of the actual nerds who care? Need it for my future recruitment needs lol.
- andai 4mo ago
  The benchmark is "do they do it for fun", i.e. personal projects. But the real trick isn't "number of personal projects", but how weird they are. There's no "rational" reason to do them, they don't increase the person's marketability / hireability. They are done purely for intrinsic reasons. (On reflection, this also seems to be a pretty robust predictor of autism. :)
eli 4mo ago
A much more charitable framing: people who enjoy the process vs people who enjoy the result. (Though, granted, the results are a lot better if you craft it by hand)
- Daishiman 4mo ago
  I am not really sure. I wrote some scripts that aggregated data from several APIs with an LLM and the LLM had the foresight to create a caching layer for the API responses as it properly inferred that I would need the results over and over again as well as using asyncio to accelerate fetch speed. This would have been a v2 or v3 and it one-shotted it perfectly.
  - anygivnthursday 4mo ago
    Yeah, they are good at applying generic patterns, but often it can be overkill/YAGNI that lead to more maintenance work in places that are fine with a much simpler/straightforward solution. But this is what the engineer can decide and with LLMs they wont be forced to make the trade off because it takes longer to build, but rather whether it is really necessary or not.

ditchfieldcaleb 4mo ago

I agree with you on everything you said here except: > when you know how the thing works and have that mental context, you will always be faster than an AI That's just plain false, honestly. No one can type at the speed AI can code, even factoring in the time you need to spend to properly write out the spec & design rules the AI needs to follow when implementing your app/feature/whatever. And that gap will only increase as LLMs get more intelligent.

nullsanity 4mo ago
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JSR_FDED 4mo ago
It should be “…you will always be faster than someone _without the knowledge_ using an AI”
leostarship 4mo ago
as i understood it he's referring to the overall time it takes to build a complete finished piece of software, accounting for the refactoring and bug fixes and all that. cause handn't you understood the tools you're using you would be running into roadblocks and that adds up
- deleted 4mo ago
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notnullorvoid 4mo ago
Some of us do actually have intimate knowledge in certain areas where guidance of an AI takes longer than doing it yourself. It's not about typing speed, it's that when you know something really really well the solution/code is already known to you or the very act of thinking about the problem makes the solution known to you in full. When that happens it's less text to write that solution than it is to write a sufficient description of the solution to AI (not even counting the back and forth required of reviewing the AI output and correcting it).

jtr1 4mo ago

I have been building an iOS app that I had kicking around in my head for years but never had time to build. I have been a frontend UX engineer for the better part of a decade and went through a handful of tutorials on Swift. The project definitely sits in this uncanny valley for me. I have test suites for every aspect of the app and have the agent using TDD to avoid cheating - this has gotten me pretty far without having to look too close at the output other than general structure. As I'm reaching a more mature stage of the project though, I'm finding that I want to tweak a lot by hand in the code to get the details right without burning tokens.

throwaway219450 4mo ago
The agents always do the best work IMO if you already know exactly what you want, but are too lazy to implement it. I like having the agent mock up a working solution before reimplementing it. To split the difference, I now try to hand code as much as I can from the beginning, leave TODO comments for the agent to mop up and I'll ask it to complete the issue with reference to the current diff. It reduces the surface for agents to make stupid assumptions. If I can get it done fast on my own, win for me, if the agent finds issues or there's logic that needs checking, also a win. This way you stay sharp, but you have access to an oracle if you get stuck and it costs you fewer tokens.
- jtr1 4mo ago
  Yeah, I like the "get out of jail free" card approach. The thing I always used to hate before this era was getting stuck in a hole on something that would take days or worse to grind through. It's nice to drop a little plank bridge across those now

deleted 4mo ago

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nbvkappowqpeop 4mo ago

thanks for this take, articulates what i've been feeling towards "AI" without my angst

Finbel 4mo ago

>Also, when did we stop liking to learn? Why is it a bad thing to know all the ins and outs of a programming language? I do not know the inns and out of the assembly layer my high level code end up as. It's not because I don't like to learn, it's because I genuinely don't need to. At a certain level of AI performance, how will this be any different?

californical 4mo ago
Because you may not know the specifics of the assembly being generated, but you’ve likely learned a language built on top of assembly. And the compilers do some great tricks behind the scenes to generate efficient assembly, but those tricks are specifically coupled to semantics of the source language. An LLM is not coupled to anything and can generate output that simply does not relate to the input. This doesn’t happen with compilers, and if it does, then it’s a specific bug to be addressed. An LLM can never guarantee certain output based on the input. If I write x < 100, I know exactly how the compiler will treat that code every single time, and I know what < means and how it differs from <= If I tell an LLM that “I want numbers up to 100.” Will that give me < or <= and will it be consistent every single time, even the ten thousandth program that I write? The language is ambiguous where the code is specific
- Finbel 4mo ago
  To me this is semantics as far as it's related to "why don't you want to learn?" I have a co-worker in another team that write java endpoins we consume. I can tell him what I need and I trust the output. I don't need to know java to trust him, it doesn't mean I don't want to learn. There are thousand examples like this across every stack and abstraction level. From ssh-handshakes to gps. Sure my co-worker is fundamentally different from a compiler which is fundamentally different from an LLM. My argument is that the chain-of-trust where you offload knowledge to an external source is identical. We do it all the time but somehow doing it with an LLM means we no longer want to learn?
sdevonoes 4mo ago
One difference is: to use a top notch compiler/assembler you don’t need to pay. They are open source and have a lot of support. To use the latest and greatest models (bc no one around likes to use non sota ones) you need to pay a premium price. Multibillion dollars companies are now the gateway for every line of code you need to write. That’s dystopian. It sucks

imrozim 4mo ago

100% aggred, i learn coding by building stuff and breaking it when you let ai do everything you skip that pain and also skip the understanding.

pjmlp 4mo ago

Except those are the same people that will decide who is getting hired, and who gets layoff because of increasing productivity. And no, this isn't playing what ifs. I have seen it happening with offshoring, migration to cloud, serverless, SaaS and iPaaS products, and now AI powered automations via agents. Less devops people, less backend devs , no translation team, no asset creation team,... I have been layoff a few times, having to do competence transfer to offshoring teams, the quality of the output is something c suites don't care all. Do you wanna bet what is behind Microslop, Apple Tahoe bugs and so forth?

rufasterisco 4mo ago

Let’s see if someone can point me towards some resources over the following. The problem is mixing vibe-coding and agentic-eng, and switching the brain in 2 different modes (fast-feedback gratification vs deep-focus gratification). There’s no clear cut rule on what works. Different people, different brains, and especially amongst devs some optimized low-key neurodivergence. And then there’s waiting mode, those N seconds/minutes that agents take to think and write. What’s the right mix? Keep a main focused project and … what do you do in the meantime? Vibe code something else? Hn? Social media? Draw lines on a paper sheet? Wood carving? Exercise? Rewatch some old tv series? I have experimented…. There are side activities that help you go back to the task at hand in the correct mental framework for it. Not just for productivity, but for efficiency and enhancing critical thinking on the main task. Or whatever you choose to optimize for. Can anyone point me towards some people talking about this?

sdevonoes 4mo ago

Agree except for this part > If you're at work and they really care about getting something out of the door, do whatever you think is best. If you don’t mind being jobless, sure do whatever you think is best. Not all of us can simply switch companies easily. Folks need to realise that AI in a company setting works for the benefit of the company, not for the individual.

0xpgm 4mo ago
But do companies really know how to use AI? I think most of it is experimentation - throwing things to the wall and seeing what sticks. It's the practitioner who eventually figures out what really works. I see this the same way the agile movement emerged. It was initiated by people who were hands-on programmers and showed enough benefit at minimizing software waste before it took a life of its own and started getting peddled by people who didn't really understand the underlying principles.
- dpoloncsak 4mo ago
  > I think most of it is experimentation - throwing things to the wall and seeing what sticks. This is true in macro, but I think we're specifically referring to LLM-generated /assisted code (vibe-coding). 'Getting something out the door' is not an necessarily in reference to an AI-infused product, just new code written by AI

NikolaosC 4mo ago

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IanCal 4mo ago

Fundamentally you need to start with "what am I trying to do?" and "given that goal, where is my time best spent?". I made a checklist for my kids to stamp off items after they get back from school (sort bag, get changed, etc). I had two goals, 1) I was trying to solve a problem at home and would have pip installed a library that just straight up did this already and 2) I wanted to check out what the claude website outputs was like at the time. My time was best spent poking at claude a bit but mostly playing with my kids - so vibe coding it was. Client test speedup issues, I'm trying to speed up tests for them and spend as little time as possible doing so. Vibe coded some analysis and visualisation tools, mostly AI but with some review guided multiple prototypes for timing and let it just fix whatever. More dedicated review for the actual solutions. Learning a new thing - goal is to learn that thing. AI there is good for doing a lot of the work around that. Maybe I'm focussing on, say, Z3. AI there can help with debugging, finding docs, setting up an environment and leave me to do the central part.

aimiraclemag 4mo ago

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latexr 4mo ago

> Also, when did we stop liking to learn? I suspect it happened when we achieved a level of such constant stimulation (there is a pocket computer always on us with infinite effortless distraction) that we’re never bored and never engage the default mode network. https://en.wikipedia.org/wiki/Default_mode_network https://en.wikipedia.org/wiki/Default_mode_network https://www.youtube.com/watch?v=orQKfIXMiA8 https://www.youtube.com/watch?v=orQKfIXMiA8 When you’re bored, your mind goes to places it wouldn’t otherwise go. Curiosity kicks in. Curiosity is a precursor to learning. Learning engages the brain and is fun. But it’s not fun all the time, some of it is challenging and frustrating (which is good, that’s the process that teaches you). When you have the digital equivalent to infinite candy and the brain equivalent to a sweet tooth, it’s hard to resist the siren’s call. The consequence is the brain equivalent to a stomachache—depression and loss of meaning—but unfortunately it doesn’t hit you the same way so you don’t make the immediate connection to make yourself stop. When you think about it, it’s ridiculous from several angles: the candy is infinite, it’s never going to run out, so you don’t need to gorge! But then we justify ourselves as only a true addict would, that while the candy is infinite, the flavours are limited editions and always rotating, and what if I miss that really good one everyone is on?! Then you miss it, is the answer. No one will be talking about it in fifteen minutes anyway.

AStrangeMorrow 4mo ago
I still love learning, especially outside of tech. Been working in the ML field for over 8 years, and while I went into it because I liked the field, I did lose some interest in learning things, but mostly because of the sheer volume of publication and the rate of change. Learning stopped being something I enjoyed doing and went to something I had to do to keep up. And it just stopped having the same flavor.
gchamonlive 4mo ago
> it happened when we achieved a level of such constant stimulation (...) that we’re never bored and never engage the default mode network. I don't know... I don't disagree, but I think this has been repeated so much that I believe everyone, at least everyone that is actively participating in HN discussions is aware of this. So if we are aware of this and we consciously choose to keep engaging in dopaminergic activities, without having some time to be bored, I think it starts to become a choice. We can blame tech for starting this trend of stealing our attention, but once we become aware of this, we can only blame ourselves for perpetuating it.

maxsilver 4mo ago

> Also, when did we stop liking to learn? When the economy got so bad for so many people, that every waking moment has to be either chasing fresh cash (or spent in recovery from cash-chasing, worrying about new cash), to the point they have to largely ignore their own long term goals or basic morals or principles. You can blame all the new gadgets (phones/social media/tiktok/‘dopamine-things’) — but it’s a very much blaming the symptom, not the problem. (It’s the meme. “Guys, this isn’t funny. Humans only do this when they’re very distressed”)

eloisant 4mo ago

Exactly, I'm a back-end engineer and I vibe-coded that in a couple of hours: https://erwan.github.io/sovereign-cards-database/ https://erwan.github.io/sovereign-cards-database/ I could have learn all the frameworks to make it, but honestly I wouldn't have bothered.

throwaway613746 4mo ago

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dpoloncsak 4mo ago

Just here to say I love the line 'A hammer is a really great tool that has thousands of purpose-designed uses. I still prefer my key to get into my car.' Been saying the 'Hammer is a great tool but you need to know when to use it, just like AI.' to coworkers, and i'm ̶s̶t̶e̶a̶l̶i̶n̶g̶ borrowing your quote instead, now

miki123211 4mo ago

In my view, AI is worst at crossing the rubicon from a 200-line script to a maintainable architecture of ~10kloc. If you already have a decent architecture, adding a new feature is usually fine. If you have nothing and need it to write a 200-line script, that's usually fine. If you need it to figure out a maintainable architecture that will be easy to extend in the future... that;'s where the problems start.

esafak 4mo ago
You need to be involved in the architecture.

throwanem 4mo ago

> Also, when did we stop liking to learn? When it got dangerous to spend that kind of time without a bullet-point deliverable.

kreneskyp 4mo ago

> If you're trying to learn something new like an algorithm, protocol, or API write that shit by hand. You learn by doing, and when you know how the thing works and have that mental context, you will always be faster than an AI. Also, when did we stop liking to learn? I vibe engineer to learn. I am currently doing this with a project to build a Vector DB extension in postgres. Several aspects of this project are very new to me. I don't write any of the code. I have never written a single line of Rust. I do, however, spend a significant amount of time discussing architecture and design with the agents. I started with well known algorithms (HNSW, IVF, DiskANN, TurboQuant, RabitQ, PQFastScan) and have since moved on to a novel implementation based on fairly recent research papers. My primary goal is to learn. That is a success and ongoing. A stretch goal is to contribute novel ideas back to the community, which may be useful even if what I build isn't ever production ready.

dirtbag__dad 4mo ago

> Also, when did we stop liking to learn? Says who? One of the most enriching things about coding with agents is I have them provide new information, tools, patterns, whatever as a follow up to every feature I work on. I’m learning a ton and it’s helping me build better with agents, too.