8 ms·

Learn to code, ignore AI, then use AI to code even better

158 points by kyrylo 2y ago

kyrylo 2y ago
This is my reaction to the recent tweet by the Replit CEO, where he said that learning to code will be a waste of time.
- deleted 2y ago
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- lukan 2y ago
  That is obviously just something he has to say, to pitch his AI company, but I reckon it is BS. Since AGI does not seem around the corner, coders will be required as ever. But I would not ignore AI to learn to code. Its great for asking endles stupid beginner questions. And yeah, some answers will be wrong, but my human tutors also taught me some very wrong concepts. But some coding without any help, is likely beneficial for learning.
- neomantra 2y ago
  I was pretty shocked and dissappointed at his quote -- Replit's rise was so aspirational. So the VC $$$ forced Replit to pivot to shilling AI schlock rather than actually improving humans...
- ak_111 2y ago
  Replit is a bit strange phenomena, they clearly are creating a huge buzz online, but I mingle a lot with university students and academics and I hardly ever heard anyone mentioning using, even sometimes when I explicitly ask them they don't seem to have heard of it? Generally curious if it is gaining traction and somehow I haven't bumped into others who use it.
Tade0 2y ago
I wonder how much the success of AI coding tools hinges on having a decent learning set? Because if a lot, I predict that as more published code is generated, we will find ourselves locked in a certain point in history in terms of versions of dependencies.
- ngvjmfgb 2y ago
  To me this is just like maths ... At school we learnt addition subtraction multiplication and division... Then we did it with a calculator... Same thing here ... Except the calculator needs much more compute and ram ... So the thing is we need to learn what is right before we can use these tools....
Ygg2 2y ago
Using LLMs to write code is a waste. If its rote code or boilerplate it sucks at writing it consistently. If its novel code, it's not in its training set. What LLMs don't suck as much is writing semi readable docs and commit messages.
- Cthulhu_ 2y ago
  We've got an LLM analyzing merge requests. While most of what it writes is too wordy for my liking and I'd prefer if people making MRs would actually write good descriptions and commit messages instead of saying "we use squash merges", one thing I do like it is that it suggests a better title. The title of an MR is used in the squash merge commit, and that commit is used in the changelog which is what users of our library rely on to consider what they need to check before upgrading. On the one side, people should write good MR titles for this reason. On the other, sometimes you just don't know, and people's brains are already overflowing with all of the tasks they need to do in order to do their job properly. But also, finally, it's just a suggestion; we don't have AIs writing our changelog yet, except ironically to make them worse / cringe.
- ieie3366 2y ago
  Your understanding of LLMs is wrong. Please read https://www.anthropic.com/news/tracing-thoughts-language-model https://www.anthropic.com/news/tracing-thoughts-language-mod...
  - quantumHazer 2y ago
    Respectfully his understanding of LLMs have nothing to do with the paper you linked.
nkrisc 2y ago
If you spend time on places that attract newbie programmers (some subreddits focused on game dev or game engines, for example) you’ll see the outcome of “I no longer think you should learn to code.” And it’s not pretty. Many, many posts of people looking for help fixing AI-generated code because the AI got it wrong and they have no idea what the code even does. Much of the time the problem is simply an invented method name that doesn’t exist, a problem that is trivially solved by the error message and documentation. But they say they’ve spent several days or whatever going back and forth with the AI trying to fix it. It’s almost a little sad. If they just take the time to actually learn what they’re doing they’ll be able to accomplish so much more. Now of course people learning the traditional way have these same problems, but they’re debugging code they wrote, not gobbledygook from an AI. It’s also easier to explain the solution to them because they wrote the code, so it tends to be simpler. Several times I’ve pitied someone asking for help with AI code and even when I explained the solution they still didn’t understand it, and I had to just give up on them - I’m not getting paid to help them.
- pydry 2y ago
  IME these tend to be the same people arguing that programmers will all be out of a job in 10 years. It makes me wonder why they persist.
- kshacker 2y ago
  I have played around wit AI code from time to time. I do not code routinely but I have pet personal projects that allow me to do some code and this is where I experimented. Rule number 1 and the only rule: You need to be a subject matter expert. Be it program logic or be it programming language. AI is only a helper, it will go wrong, frequently, and if you do not understand the reason for the code and the programming language, you will take so much more time than if you did not even use the AI. Without naming the IDE, but one of the top 3 I guess, I asked it to simplify some code. I had repeated code 8 times. 6 of them were identical, the last 2 had a variation. The AI just did not catch it, and refactored all 8 blocks to use the logic of first block. How can you even do that? The code is similar but different, it looks the same but there are extra lines of code in the last 2 blocks !! And it took me a while to realize this. I never ingest AI code directly so at first I was marveling at a job well done, and as I read and compared, the horror !! And that was not the first time it happened, but once again I got tricked by the soft spoken well mannered AI to believe that it did a fantastic job when it did not. Edit: It is just an assistant. You give it a task, it will make a mistake, you tell it to fix the mistake, it will fix the mistake. It still saves you time. Next day, it will make the same mistake - and hopefully that gets reduced as the versions evolve.
Cthulhu_ 2y ago
For a cynical take, 10, 15 years ago this headline would have been "Learn to code, ignore Stack Overflow, then use SO to code even better". In this context, AI is just one of many resources you can use - books, websites, SO, etc - to improve your coding. The big differentiator is that you can have a realtime conversation with AI, whereas when talking to other people - be it on SO, IRC, Github, forums etc - you may or may not get a response and it may or may not be helpful. AI tools are a bit more predictable that way. I'm of the opinion that AI will not replace developers but will be another tool in their arsenal. And part of the skillset of (some) developers will be working with an AI tool effectively. I don't have that yet, but then, I don't know much about Docker / K8S, cloud providers, low level memory management, pure functional coding, Rust, graphics programming etc etc either.
- gtsop 2y ago
  I don't think you are tackling (what i believe to be) the main point in this article. Yes we can all agree that replacing SO with chatgpt is very fast and often a better experience. However, this is not about researching for solutions, it is about offloading your coding capacity to the machine. These are two different things and I think the author is addressing the latter.
marjann 2y ago
The rise of tools like Cursor reminds me of the Industrial Revolution in France. When machines first appeared in factories, unskilled workers who didn’t understand how they operated often got injured - sometimes quite literally losing fingers. But for skilled craftsmen, these machines became force multipliers, dramatically increasing productivity and improving overall living standards. The same applies to software development. If you lack the fundamentals - how memory, I/O, networking, and databases work - you’re at risk of building something fragile that will break under real-world conditions. But for those who understand the moving parts, tools like Cursor supercharge efficiency, allowing them to focus on high-level problem-solving rather than boilerplate coding. Technology evolves, but the need for deep knowledge remains. Those who invest in learning the craft will always have the advantage.
- shinycode 2y ago
  Well it’s a good point that proves at least two things. First in the industrial world machine have not yet replaced man after decades. Still a force multiplier. The second point is the one who control « what » produces value wins it all. In France we had amazing industries and some were deported offshore. Maybe some genius thought that only the brain mattered. Now countries have to rely on other countries to build or make products evolve and those countries can make their own products now and can charge us whatever they want (I’m simplifying) because we don’t know how to build things anymore, tools and craftsmanship is gone and not learned anymore. I feel the article pin points exactly the main idea behind AI : who will have control and who will be able to decide that the API price can be x100 ? If no one knows how to code, that is very dangerous and what happened in the industrial world shows it’s dangerous. Companies have an endgame of power and as a developer deciding to not learn or delegate my know how makes me at mercy in the end
  - MonkeyClub 2y ago
    > machine have not yet replaced man after decades When I look at fields like car manufacturing, which is mostly robotic, it seems that nowadays humans are force multipliers for machines rather than the other way around.
zx10rse 2y ago
The message those people are sending is truly awful.
koakuma-chan 2y ago
I would also suggest getting off Twitter.
ChrisMarshallNY 2y ago
> Because if you can vibe code… so can everyone else. That's really the money shot, right there. CEOs have this dream of firing all their "obnoxious" engineers, and "vibe-coding" their own products. That's not something new. People have been selling this dream to gullible C-suiters since I first started coding in Machine Code (1980s). The future will belong to the engineers that can leverage AI. Engineering is a lot more involved than "HAL, write me a Facebook," which is the C-suite dream. It's just that engineering will move another level up, as it has, for hundreds of years.
- DrScientist 2y ago
  > CEOs have this dream of firing all their "obnoxious" engineers, and "vibe-coding" their own products. Give one of the key skills of a CEO's is pulling together the resources to make something happen, what happens to CEO's if you no longer need resources to make stuff happen? ie if everybody can Vibe code, vibe market, vibe deploy - aren't you going to be swamped with competitors? So the interesting thought experiment here is - in such an environment - what are the critical success factors?
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  - supriyo-biswas 2y ago
    Mostly that in such a reality software engineering will cease to be a thing; however industries based around physical resources such as manufacturing, construction and healthcare will continue to employ people, and by extension, the CEO.
  - moregrist 2y ago
    > Give one of the key skills of a CEO's is pulling together the resources to make something happen, what happens to CEO's if you no longer need resources to make stuff happen? Never underestimate how much importance a lot of people in middle and upper management place in the number of reports they have. It’s almost a <thing> measuring contest with some of them. They’ll hire people. It might not be in engineering. But I bet they’ll find a reason to hire more engineering. It might even be justified. Software productivity has been increasing for decades. This has not led to a smaller number of software engineers. Only to more ambitious projects. The future might be different, but I think the chances of that are small.
dlvhdr 2y ago
Or just keep learning and ignore AI
itchyjunk 2y ago
I guess experience is widely varying with tools. I had no idea what WSS was. Cursor searched the web and docs and necessary and built a working program. Then we went over each conceptual blocks and it explained stuff to me. When I was confused about some parts, it decided I need to strip away the RealTime API component and just understand asynco in context of WSS so it created a new file with a toy example. Could it have written some really, really bad and unmaintainable code and it was just justifying things? Very possible. I asked to strip some 60% of the code after I thought I understood, and it was still working. The original code was too abstract for me and hard to follow. Did I learn in this whole process? I think yes. Would I have learned more if I had worked without AI? I think yes. In life, some people play games and figure out the best builds after a lot of sweat and tears while others prefer googling the meta and only doing those builds, it seems. Both approach seems fine.
randomNumber7 2y ago
Imo if you learn to code today and ask the LLM to explain things to you it could very efficient. People that fall into the trap of using LLMs to write code they don't understand would just fall into another trap when LLMs wouldn't exist.
major505 2y ago
The best part of AI in my opnion is not having to search through documentation. You have any questions about a specific funcion in this lib? Just ask, and will do the search for you, and provide an quick example of use. This shit is magical.
- globnomulous 2y ago
  Trying nine wrong solutions to a problem before finding the tenth, which actually succeeds, is frequently an essential part of the learning process, in writing natural language as in programming.
  - major505 2y ago
    I agree. But is usefull when your studing. When you actually need to delivery something, is great. I used to know java sdk by memory whe I was young. Nowdays theres too many languages I have to remember. Easier just to ask copilot.
pama 2y ago
“But if AI vanished tomorrow due to, say, regulations […]” You can’t vanish math and computers globally like that.
- guappa 2y ago
  You can pop a bubble that doesn't make any money to the investors just like that :)
voidUpdate 2y ago
If nobody learns to code, who will program new AI systems?
- dailykoder 2y ago
  Even worse: Who will produce new training data? If everyone only uses AI, then nothing new will be invented. Quality will stagnate or go downhill. It cannot get better
  - daerogami 2y ago
    But haven't you heard? AI gets better every month! It's just like Moore's Law and it will keep getting better because why wouldn't it? It's not like there is a dead-end to something fundamentally built around categorization and regurgitation of existing things. (Noting this is all sarcasm in case I didn't lay it on thick enough)
dailykoder 2y ago
To me "learn to code" has ALWAYS been a synonym to "learn to think". Coding is nothing else than thinking. You learn a handful of structures and then you only think about how to combine them. It doesn't matter if you do it by AI or "by hand".
koopuluri 2y ago
> Because if you can vibe code… so can everyone else. > And if everyone can do it, what makes you think Devin won’t replace you? Devin won't replace you if you can create valuable products through "vibe coding" or whatever else you call it. when coding itself becomes a commodity, value creation becomes more concentrated up the stack: what you choose to build, how well you market / sell it, how you connect with your customers, product design. Devin won't outcompete humans at these skills anytime soon. instead of sticking to a skill that's quickly becoming a commodity (as the author recommends), moving up the stack is the way to go (outside of very niche, specialized engineering domains - e.g: training base models).
ZaoLahma 2y ago
AI does not and will not solve the most difficult part of programming: Expressing how you wish to solve a problem in simple terms. It doesn't matter if you communicate with a compiler or an LLM - you still need to express your thoughts and ideas with no ambiguity for it to produce the wanted behavior. What makes "vibe coding" with an LLM both easier and more challenging at the same time is that is will guess what you mean and give you results that "kind of " work even when you express yourself unclearly. For someone who can code, the "kind of work" results can be used as a starting point to evolve into something useful. For someone who can't code, it's an inevitable dead end. I find that those who struggle with programming have the exact same type of struggles when trying to do it with LLMs - no structured plan on how to approach a problem and difficulties to understand the context in which they are working.
CharlieDigital 2y ago
Probably the opposite is true: the more you know how to code, the less productive you'll be with AI. This has been my observation watching a non-technical friend build a SaaS as a one-man team in 4 months and is generating $#,000 in revenue within 2 months. The way he uses AI is just completely different from how the technical folks I know use AI because he doesn't think about the code at all. The way he instructs the AI is different from how engineers prompt the AI. I actually think that his success with AI is in particular because he doesn't know how to code but was previously managing projects and offshore teams (so lots of writing down exactly what he wants, but with no specifics on how it gets implemented).
- intelVISA 2y ago
  Problem is what kind of moat does that SaaS have? The flip side of 'we replaced our dev team with vibe coders look how fast we print shitware' is now shitware value falls close to 0, as anyone can make it. Though you suggest he's non-technical... "writing down exactly what he wants" is just coding!
  - exodust 2y ago
    > "writing down exactly what he wants" is just coding! Agreed. The more exact and clear your instructions are, the closer to programming it is. Presumably the non-technical person has an application where they care about things like performance, scalability, compatibility and all those things coders sweat over.
  - CharlieDigital 2y ago
    > "writing down exactly what he wants" is just coding! That would make good project managers and business analysts "coders" and they are not coders. It is only in this age with LLMs does that line between functional requirements and code become blurred. He doesn't know how to write code well; he knows how to write requirements and instructions well from managing offshore teams. In practice, his instructions are detailed in the functional domain. Engineers bias too much in the technical domain. > The flip side of 'we replaced our dev team with vibe coders look how fast we print shitware' is now shitware value falls close to 0, as anyone can make it. Actually, he recognizes this and said something to the effect of "this is the end of SaaS" meaning that anyone can build this. That's his biggest fear going all in on this (he is still keeping his day job despite this project gaining traction so quickly) But I don't think this is true; I think there are still some technical barriers (at the moment) like one needs to know to instruct about databases, set up external services, etc. The AI is writing the connections to some third party APIs, but one needs to know what an API is and which one to use to instruct the agent. A future may be coming where this is no longer the case (e.g. combining deep research and computer use that will automatically set up domains, connect external services, etc.), but it's not here yet. > 'shitware' Is it "shitware" if customers are paying because they are deriving value from it? He's got 30 customers, a few of which paid annual subscriptions because it provided value to their actual business. Is it "shitware" because it's not handcrafted? Does it matter if it's solving some real problem and customers want to pay for it?
wickedsight 2y ago
I'm getting back into programming after a couple of years other roles. I have to learn a framework I haven't worked before and get to know new paradigms I never used. In a way, I'm feeling lucky that my company currently explicitly bans the use of AI tools on our code bases (for good reasons). This forces me to write all my own code and understand what it's doing. The only thing I use AI tools for is to explain some new concepts or paradigms in ways I can understand. What's also great is that I can throw some code from Stack or Github in there and get it explained. I'm glad these tools exist, since they make learning much easier, but they're also a trap if you depend on them in stead of your own knowledge.
keepamovin 2y ago
That is what I did. I programmed since I was 10 on and off until around age 27 where I started basically full time after studying chemistry but not wanting to work in the lab. I was 100% FT on a project since 2018/2019 and began using AI when ChatGPT came out, but couldn't use it on this project for ages because it was all giant legacy code with lots of context (both explicit and implicit). I used it for new projects and side things. I really enjoyed it. I learned SQL and Bash and PowerShell from the collaborations. I also made my first macOS app. I have even learned a few new things in JavaScript which is my main and began to use it on my main project too. I feel so lucky to be alive at this time. It's amazing to have this way to work!
jillesvangurp 2y ago
I've been programming for a few decades. I love LLMs. They make tedious things quick. Help me resolve gnarly issues. Make short work of writing unit tests. Generate oodles of boilerplate at will. Etc. It makes me more productive and less reluctant to take on risky things. By risky I mean things that formerly would have likely derailed my busy schedule because I'd get side tracked for to long and would have to de-prioritize more important stuff. Anyway, resistance is futile. You will be assimilated ... or retired. The reality of our job is that new generations are going to come in and they'll be using all the latest tools and gadgets. That's nothing new. And I'm part of a generation that in a decade or two will be mostly on the sidelines enjoying retirement. So, I'm well aware that progress isn't going to stop over my whining and grumbling. It annoys me when I catch myself doing that. I want to be better than that. LLMs are part of the job now. They are tools. And tools are only as good as the people wielding them. So, skill up and learn. It's not like it's very hard. If you are getting poor results, you might be doing it wrong. Figure it out; part of the job. Your mileage may vary. But there are a lot of tools and chances are you just haven't found the right one yet. Also, if some tool/llm limitation is blocking getting good results for something, wait 3 months and try again. The pace of progress is ridiculous currently. Or better yet: become part of the solution and make your own tools. This stuff is stupidly easy. It's prompt engineering with some trivial plumbing around them mostly. And you can generate the plumbing (what, you were going to do that manually?). That's why there are so many AI tools popping up right now. Most of them won't survive very long. But there are some good ideas lurking there.
- dingnuts 2y ago
  I've been programming for a few decades. I hate LLMs. They generate oodles of buggy shite that I have to fix by hand. They frequently steal my time and make me less productive because people on this site say I have to learn them or retire, and then I waste time looking up the details the bot got wrong. They're a slot machine and the people who think they are good are justifying an addiction and sunk costs. So retire me, I guess. I'm probably younger than you, but I'm almost ready to retire because I'm cheap and I don't buy into expensive fads, so I'm almost ready to cash out of this nightmare except then you realize the valuations of anthropic etc are propping up the whole economy and doing so on the promise that LLMs are going to deliver AGI! LLMs are marginally useful in some contexts. But I have seen absolutely nothing -- nothing -- to justify the costs or the valuations of these companies. They are definitely not AGI and before you accuse me of moving the goalposts, the AI companies are the ones promising this. It's a bubble. It's easy to get started. Good luck building a real product with just AI though. Good luck with that. If you turn out to be right I will happily exit this God forsaken industry. Lord free me from silicon valley; I liked computers. Not this. Not these people.
grumbel 2y ago
Ignoring AI would be foolish, since AI is the best programming tutor you can wish for and will speed up your learning noticeably, since you can always ask for clarification or examples when something isn't clear. It's also a great way to get random data for testing. And it will help you unearth lesser known corners of a programming language that you might have overlooked otherwise. The downside is that at the current speed of improvement, AI might very well already be at escape velocity, where it improves faster than you, and you'll never be able to catch up and contribute anything useful. For a lot of small hobby projects, that's already the case. I don't think there are any easy answers here. Nothing wrong with learning to code because it's fun. But as a career choice, it might not have a lot of future, but then, neither might most other white-collar jobs. Weird times are ahead of us.
- exodust 2y ago
  > AI is the best programming tutor you can wish for...you can always ask for clarification or examples when something isn't clear Yep, AI can teach beginners the fundamentals with endless patience and examples to suit everyone's style and goals. Walking you through concepts and giving you simulated encouragement as you progress. Scary stuff, but that's how it is. But... as we know, it doesn't always provide the best solution. Or it gets muddled. When you point out its mistakes, it apologises, recognises the mistake and explains why its a mistake. It's reasoning is incredible, but it still makes mistakes. This could be very risky for production code. Related anecdote... I needed Photoshop help recently for horizontally offsetting a vignette effect. Surprisingly not easy. The built-in vignette filter can't be applied to a new blank layer, and is always centred on the image. AI suggested making it manually but I didn't want to do that, as I like the built-in vignette better. AI's next solution involved several complicated steps using channel isolation and weird selection masking etc. No thanks. Then my own brain sparked a better idea... simply increase the canvas size temporarily, apply the vignette, then crop back to the original size. Job done. I told AI about my solution and it was gushing with praise about how brilliant my solution was compared to its own. Moral: never stop trusting your own brain.
- guappa 2y ago
  I wonder what kind of trivial boring jobs people who keep saying that LLMs are so incredibly useful at programming must have to have that opinion. What does your day look like?
dansmyers 2y ago
I'm a professor at a small college. I teach intro programming most semesters and we're now moving to using tools like Cursor with no restrictions in upper-level courses. "How do students learn to code nowadays?" - I think about this pretty much all the time. In my intro class, the two main goals are to learn about structured programming (using loops, functions, etc.) and build a mental model of how programs execute. Students should be able to look at a piece of code and reason through what it does. I've moved most of the traditional homework problems into class and lab time, so I can observe the students coding without using AI. The out-of-class projects are now bigger and more creative and include specific steps to teach students how to use AI collaboratively. My upper-level students are now doing more ambitious and challenging projects. What we've seen is that AI moves the difficulty of programming away from remembering details of languages or frameworks, but rewards having a careful, structured development process: - Thinking hard and chatting about the problem and the changes you need to implement before doing anything - Keeping components encapsulated and thinking about interfaces - Controlling the scope of your changes; current AIs work best at the function or class level - Testing and validation - Good manual debugging skills; you can't rely on AI to fix everything for you - General system knowledge: networking, OS, data formats, databases One of my key theories is that AI might lower the value of "computer science" as a standalone major, but will lead to a lot more coding across fields that currently don't use it. The intersection of "not a traditional engineer" and "can work with AI to solve problems with code" is going to be an emerging skill set that will change a lot of disciplines.
- greenchair 2y ago
  appreciate the insight
- NeutralCrane 2y ago
  This is by far the most interesting insight in this thread
- ghaff 2y ago
  I observe the course catalog at one not small college now has options for a lot of majors—many of which weren’t terribly computer-heavy historically.
amelius 2y ago
I want an AI that can reliably help me refactor a codebase.
DeathArrow 2y ago
To each, their own. To deeply understand an area you have to learn it from bottom up. I learned BASIC as a small kid, using a clone of ZX Spectrum. I was aware that the memory was limited and that I can poke and peek a memory address to set or retrieve the info. I learned Pascal and then rapidly went to C and C++. I learned about pointers and how the memory is layed out and what are system calls. I learned about CPUs and I learned some X86 assembly. Ar the university I learned about digital circuits and how to assemble one using logical gates. Of course I learned much more, data structures, algorithms, operating systems, distributed systems, parallel and concurrent programming, formal languages and automata theory, cryptography, web, lots of stuff. I learned other lots of stuff by myself. I've built desktop apps, websites, software for microcontrollers, games, web applications and now I am working on microservices based apps running in cloud. I was a junior developer, graduated somehow to senior. I worked as a software architect and now I am a team leader. These days I work almost exclusively with C#, but I am also interested in other languages if I have some spare time to evaluate them. What I want to say is this: is not enough to learn the highest level of technology of today. Today that is AI, few years ago it was JS frameworks, more years ago it was Java, .NET, Python. To be good at what you do you always have to learn all layers under the current top layer. Learn from bottom up. You don't have to be good at every technical detail, but you have to understand at least how the things work.
- daerogami 2y ago
  To add to this, if someone depends on AI (the top-layer in your example) and doesn't learn the the 'how's and the 'why's of programming, they or their organization will be completely beholden and dependent on the organizations running those AI tools. Not a great position to be in.
littlecranky67 2y ago
That advice was true already a decade ago, but replace AI with StackOverflow. I encountered many junior devs (mostly money-driven, not out of passion for software development) that were completely fine just copy-pasting code out of Stackoverflow without getting a deeper understanding or at least trying to understand what their copied code does. Same is true for AI. Both are great tools, but to become truly a master of your craft you should always thrive to become the person that would have answered the SO question - or wrote the article that the AI learned from.
nightfox1 2y ago
This resonates a lot with what I’ve seen outside of code too. I’ve been building an AI chess coach and noticed the same pattern: people plug their games into Stockfish, see a list of best moves, and walk away thinking they’ve “analyzed” the game. But real understanding — like in programming — only comes from engaging with why things went wrong. That’s what I’m trying to fix. Instead of just showing lines, my AI coach gives voice-guided feedback, visual highlights, and practical insights. More like working with a real coach than sifting through raw engine output. The goal is to make analysis as engaging as playing—and shift the mindset from “just tell me the best move” to “help me think better.” Demo if curious: https://www.loom.com/share/9e1578f1348841c1992c5d902e371312?sid=56108d1f-e81a-4538-84e9-c4792e96aea1 https://www.loom.com/share/9e1578f1348841c1992c5d902e371312?...
- morcus 2y ago
  Seems like an interesting idea - is it only tactics in scope or has does the AI also do well at analyzing strategic ideas? Some other thoughts: Isn't the first example just wrong? The AI says "after dxe3 Rxd8 Rxd8, white wins the exchange, gaining a Rook for a Bishop" but unless I am mistaken actually it's a Queen for a Rook and Bishop? Also, it seems the visual highlight AI referenced is not working? Talks about Rad1 while the pawn is still highlighted.
  - nightfox1 2y ago
    It will do both tactics and strategy. Also working on incorporating positional concepts. Yes you are right. It is still in demo phase, it still does make mistakes. I am refining the model and inputs, so definitely a work in progress :) Regarding the circle highlighting, the agent is deciding / reasoning which square to highlight. So it is non-determinsitic, so it is sometimes right / wrong. It will definitely get better as the models improve
voidhorse 2y ago
There are a lot of reasons I dislike the use of LLMs in software, one of which is that I think it's absurd to claim that using such fuzzy and imprecise tools and methods should be considered engineering... But to be honest, I think the main thing is that they just absolutely suck the joy and fun out of an activity. I like writing, I like coding, these are things that I do at least in part because I get some kind of direct enjoyment out of doing them. Using a chatbot simply is not interesting or fun to me. It's like being a spectator and thinking that means you "participated" in the game you watched. If you code or whatever just as a means to make ends meet sure, it makes total sense that you'll want to use these tools, but I will absolutely never understand the people that claim to like a craft and reach for LLMs to do it—to me these people have just entirely missed the point of what it means to have an activity you enjoy. It's not about the output, it's all about the process and self-enrichment that happens along the way.
- ghaff 2y ago
  You seem to be saying that you’re more interested in writing code than understanding problems and designing architectural solutions to them that exploit the best available tools to help create the actual code. Which may be LLMs (to some degree) at this point. But maybe that’s not your intent.
wintorez 2y ago
This is the way.
ArthurStacks 2y ago
The only people saying this kind of thing are coders desperate to stay relevant. There is no future in coding. Its gone in a few years. Instead begin learning the skills required to work with AI to get it create what you want.
- guappa 2y ago
  https://news.ycombinator.com/item?id=43504924 https://news.ycombinator.com/item?id=43504924
  - ArthurStacks 2y ago
    I run a software development business. I know as good as anyone where things are headed
    - guappa 2y ago
      So you're not a software developer and can't really evaluate how useful it is?
      - ArthurStacks 2y ago
        You should have spent more time in school
        guappa 2y ago
        Is there any research that shows that failing years in school and remaining longer than expected is linked with blindly believing anything AI grifters say?
sunwukung 2y ago
I've been following some kid on TikTok who started last year on this journey - and it's been truly frustrating to watch. I tried to discourage them from leaning so heavily on AI, but they insisted it was a different way of learning. A year later, and they still don't comprehend for loops or conditional blocks, and believe that comprehending this basic material is a deep understanding of code.
kornaki 2y ago
I think of it as a magic wand that makes me more efficient when it comes to smaller projects. I now do things I would earlier not even pick up because I simply type less now. But I feel like you need to have intuition/experience to question AI all the time. Why this code was added? Is it safe? Is it the right way? Is it the right method, tool, library, maybe we can try another approach. I feel like I learn faster too, because I can so quickly ask a question in a context with which AI is familiar. I would neither down play its role or follow "learning how to code is useless" hypers.
bookofjoe 2y ago
I've stopped reading HN posts about AI because comments on them are the same old same old: 2 camps, one of which says get over it 'cause it's great, the other of which says it's a complete FAIL and always will be.
sieste 2y ago
s/code/think/g
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nialv7 2y ago
Re what Replit CEO said: i mean sure, learn how to think, learn how to breakdown problems and communicate - good skills to have, regardless of AI or not. and learning how to code is one of the great ways to improve these skills. people generally aren't going to learn how to think in a vacuum, right? Math, science, and programming, among others, that's how most people learn how to think, they are not going to be a waste of time.
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fmxsh 2y ago
In a way, "vibe coding" is like what infants do when they give "error messages" of "hungry" to query mom for food. Newcomers may be tempted to maintain the uttermost ignorance of what they are creating, as I imagine "vibe coding" implies, where the height of problem-solving is creating quicker pipes between errors and re-submission to AI to fix those errors. I'm really glad I learned programming a long time ago, before AI. I use AI more like a tool for getting information (much like browsing manuals, forums, Stack Overflow), but it is, of course, magnitudes better. I still do the conceptual outlining and problem solving, and that is what programming is to me. If there's something I don't understand from the AI, I always query to know how it works. It's even easier now to understand how things work thanks to AI.

158 points by kyrylo 2y ago

kyrylo 2y ago

This is my reaction to the recent tweet by the Replit CEO, where he said that learning to code will be a waste of time.

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lukan 2y ago
That is obviously just something he has to say, to pitch his AI company, but I reckon it is BS. Since AGI does not seem around the corner, coders will be required as ever. But I would not ignore AI to learn to code. Its great for asking endles stupid beginner questions. And yeah, some answers will be wrong, but my human tutors also taught me some very wrong concepts. But some coding without any help, is likely beneficial for learning.
neomantra 2y ago
I was pretty shocked and dissappointed at his quote -- Replit's rise was so aspirational. So the VC $$$ forced Replit to pivot to shilling AI schlock rather than actually improving humans...
ak_111 2y ago
Replit is a bit strange phenomena, they clearly are creating a huge buzz online, but I mingle a lot with university students and academics and I hardly ever heard anyone mentioning using, even sometimes when I explicitly ask them they don't seem to have heard of it? Generally curious if it is gaining traction and somehow I haven't bumped into others who use it.

Tade0 2y ago

I wonder how much the success of AI coding tools hinges on having a decent learning set? Because if a lot, I predict that as more published code is generated, we will find ourselves locked in a certain point in history in terms of versions of dependencies.

ngvjmfgb 2y ago
To me this is just like maths ... At school we learnt addition subtraction multiplication and division... Then we did it with a calculator... Same thing here ... Except the calculator needs much more compute and ram ... So the thing is we need to learn what is right before we can use these tools....

Ygg2 2y ago

Using LLMs to write code is a waste. If its rote code or boilerplate it sucks at writing it consistently. If its novel code, it's not in its training set. What LLMs don't suck as much is writing semi readable docs and commit messages.

Cthulhu_ 2y ago
We've got an LLM analyzing merge requests. While most of what it writes is too wordy for my liking and I'd prefer if people making MRs would actually write good descriptions and commit messages instead of saying "we use squash merges", one thing I do like it is that it suggests a better title. The title of an MR is used in the squash merge commit, and that commit is used in the changelog which is what users of our library rely on to consider what they need to check before upgrading. On the one side, people should write good MR titles for this reason. On the other, sometimes you just don't know, and people's brains are already overflowing with all of the tasks they need to do in order to do their job properly. But also, finally, it's just a suggestion; we don't have AIs writing our changelog yet, except ironically to make them worse / cringe.
ieie3366 2y ago
Your understanding of LLMs is wrong. Please read https://www.anthropic.com/news/tracing-thoughts-language-model https://www.anthropic.com/news/tracing-thoughts-language-mod...
- quantumHazer 2y ago
  Respectfully his understanding of LLMs have nothing to do with the paper you linked.

nkrisc 2y ago

If you spend time on places that attract newbie programmers (some subreddits focused on game dev or game engines, for example) you’ll see the outcome of “I no longer think you should learn to code.” And it’s not pretty. Many, many posts of people looking for help fixing AI-generated code because the AI got it wrong and they have no idea what the code even does. Much of the time the problem is simply an invented method name that doesn’t exist, a problem that is trivially solved by the error message and documentation. But they say they’ve spent several days or whatever going back and forth with the AI trying to fix it. It’s almost a little sad. If they just take the time to actually learn what they’re doing they’ll be able to accomplish so much more. Now of course people learning the traditional way have these same problems, but they’re debugging code they wrote, not gobbledygook from an AI. It’s also easier to explain the solution to them because they wrote the code, so it tends to be simpler. Several times I’ve pitied someone asking for help with AI code and even when I explained the solution they still didn’t understand it, and I had to just give up on them - I’m not getting paid to help them.

pydry 2y ago
IME these tend to be the same people arguing that programmers will all be out of a job in 10 years. It makes me wonder why they persist.
kshacker 2y ago
I have played around wit AI code from time to time. I do not code routinely but I have pet personal projects that allow me to do some code and this is where I experimented. Rule number 1 and the only rule: You need to be a subject matter expert. Be it program logic or be it programming language. AI is only a helper, it will go wrong, frequently, and if you do not understand the reason for the code and the programming language, you will take so much more time than if you did not even use the AI. Without naming the IDE, but one of the top 3 I guess, I asked it to simplify some code. I had repeated code 8 times. 6 of them were identical, the last 2 had a variation. The AI just did not catch it, and refactored all 8 blocks to use the logic of first block. How can you even do that? The code is similar but different, it looks the same but there are extra lines of code in the last 2 blocks !! And it took me a while to realize this. I never ingest AI code directly so at first I was marveling at a job well done, and as I read and compared, the horror !! And that was not the first time it happened, but once again I got tricked by the soft spoken well mannered AI to believe that it did a fantastic job when it did not. Edit: It is just an assistant. You give it a task, it will make a mistake, you tell it to fix the mistake, it will fix the mistake. It still saves you time. Next day, it will make the same mistake - and hopefully that gets reduced as the versions evolve.

Cthulhu_ 2y ago

For a cynical take, 10, 15 years ago this headline would have been "Learn to code, ignore Stack Overflow, then use SO to code even better". In this context, AI is just one of many resources you can use - books, websites, SO, etc - to improve your coding. The big differentiator is that you can have a realtime conversation with AI, whereas when talking to other people - be it on SO, IRC, Github, forums etc - you may or may not get a response and it may or may not be helpful. AI tools are a bit more predictable that way. I'm of the opinion that AI will not replace developers but will be another tool in their arsenal. And part of the skillset of (some) developers will be working with an AI tool effectively. I don't have that yet, but then, I don't know much about Docker / K8S, cloud providers, low level memory management, pure functional coding, Rust, graphics programming etc etc either.

gtsop 2y ago
I don't think you are tackling (what i believe to be) the main point in this article. Yes we can all agree that replacing SO with chatgpt is very fast and often a better experience. However, this is not about researching for solutions, it is about offloading your coding capacity to the machine. These are two different things and I think the author is addressing the latter.

marjann 2y ago

The rise of tools like Cursor reminds me of the Industrial Revolution in France. When machines first appeared in factories, unskilled workers who didn’t understand how they operated often got injured - sometimes quite literally losing fingers. But for skilled craftsmen, these machines became force multipliers, dramatically increasing productivity and improving overall living standards. The same applies to software development. If you lack the fundamentals - how memory, I/O, networking, and databases work - you’re at risk of building something fragile that will break under real-world conditions. But for those who understand the moving parts, tools like Cursor supercharge efficiency, allowing them to focus on high-level problem-solving rather than boilerplate coding. Technology evolves, but the need for deep knowledge remains. Those who invest in learning the craft will always have the advantage.

shinycode 2y ago
Well it’s a good point that proves at least two things. First in the industrial world machine have not yet replaced man after decades. Still a force multiplier. The second point is the one who control « what » produces value wins it all. In France we had amazing industries and some were deported offshore. Maybe some genius thought that only the brain mattered. Now countries have to rely on other countries to build or make products evolve and those countries can make their own products now and can charge us whatever they want (I’m simplifying) because we don’t know how to build things anymore, tools and craftsmanship is gone and not learned anymore. I feel the article pin points exactly the main idea behind AI : who will have control and who will be able to decide that the API price can be x100 ? If no one knows how to code, that is very dangerous and what happened in the industrial world shows it’s dangerous. Companies have an endgame of power and as a developer deciding to not learn or delegate my know how makes me at mercy in the end
- MonkeyClub 2y ago
  > machine have not yet replaced man after decades When I look at fields like car manufacturing, which is mostly robotic, it seems that nowadays humans are force multipliers for machines rather than the other way around.

zx10rse 2y ago

The message those people are sending is truly awful.

koakuma-chan 2y ago

I would also suggest getting off Twitter.

ChrisMarshallNY 2y ago

> Because if you can vibe code… so can everyone else. That's really the money shot, right there. CEOs have this dream of firing all their "obnoxious" engineers, and "vibe-coding" their own products. That's not something new. People have been selling this dream to gullible C-suiters since I first started coding in Machine Code (1980s). The future will belong to the engineers that can leverage AI. Engineering is a lot more involved than "HAL, write me a Facebook," which is the C-suite dream. It's just that engineering will move another level up, as it has, for hundreds of years.

DrScientist 2y ago
> CEOs have this dream of firing all their "obnoxious" engineers, and "vibe-coding" their own products. Give one of the key skills of a CEO's is pulling together the resources to make something happen, what happens to CEO's if you no longer need resources to make stuff happen? ie if everybody can Vibe code, vibe market, vibe deploy - aren't you going to be swamped with competitors? So the interesting thought experiment here is - in such an environment - what are the critical success factors?
- deleted 2y ago
  [deleted]
- supriyo-biswas 2y ago
  Mostly that in such a reality software engineering will cease to be a thing; however industries based around physical resources such as manufacturing, construction and healthcare will continue to employ people, and by extension, the CEO.
- moregrist 2y ago
  > Give one of the key skills of a CEO's is pulling together the resources to make something happen, what happens to CEO's if you no longer need resources to make stuff happen? Never underestimate how much importance a lot of people in middle and upper management place in the number of reports they have. It’s almost a <thing> measuring contest with some of them. They’ll hire people. It might not be in engineering. But I bet they’ll find a reason to hire more engineering. It might even be justified. Software productivity has been increasing for decades. This has not led to a smaller number of software engineers. Only to more ambitious projects. The future might be different, but I think the chances of that are small.

dlvhdr 2y ago

Or just keep learning and ignore AI

itchyjunk 2y ago

I guess experience is widely varying with tools. I had no idea what WSS was. Cursor searched the web and docs and necessary and built a working program. Then we went over each conceptual blocks and it explained stuff to me. When I was confused about some parts, it decided I need to strip away the RealTime API component and just understand asynco in context of WSS so it created a new file with a toy example. Could it have written some really, really bad and unmaintainable code and it was just justifying things? Very possible. I asked to strip some 60% of the code after I thought I understood, and it was still working. The original code was too abstract for me and hard to follow. Did I learn in this whole process? I think yes. Would I have learned more if I had worked without AI? I think yes. In life, some people play games and figure out the best builds after a lot of sweat and tears while others prefer googling the meta and only doing those builds, it seems. Both approach seems fine.

randomNumber7 2y ago

Imo if you learn to code today and ask the LLM to explain things to you it could very efficient. People that fall into the trap of using LLMs to write code they don't understand would just fall into another trap when LLMs wouldn't exist.

major505 2y ago

The best part of AI in my opnion is not having to search through documentation. You have any questions about a specific funcion in this lib? Just ask, and will do the search for you, and provide an quick example of use. This shit is magical.

globnomulous 2y ago
Trying nine wrong solutions to a problem before finding the tenth, which actually succeeds, is frequently an essential part of the learning process, in writing natural language as in programming.
- major505 2y ago
  I agree. But is usefull when your studing. When you actually need to delivery something, is great. I used to know java sdk by memory whe I was young. Nowdays theres too many languages I have to remember. Easier just to ask copilot.

pama 2y ago

“But if AI vanished tomorrow due to, say, regulations […]” You can’t vanish math and computers globally like that.

guappa 2y ago
You can pop a bubble that doesn't make any money to the investors just like that :)

voidUpdate 2y ago

If nobody learns to code, who will program new AI systems?

dailykoder 2y ago
Even worse: Who will produce new training data? If everyone only uses AI, then nothing new will be invented. Quality will stagnate or go downhill. It cannot get better
- daerogami 2y ago
  But haven't you heard? AI gets better every month! It's just like Moore's Law and it will keep getting better because why wouldn't it? It's not like there is a dead-end to something fundamentally built around categorization and regurgitation of existing things. (Noting this is all sarcasm in case I didn't lay it on thick enough)

dailykoder 2y ago

To me "learn to code" has ALWAYS been a synonym to "learn to think". Coding is nothing else than thinking. You learn a handful of structures and then you only think about how to combine them. It doesn't matter if you do it by AI or "by hand".

koopuluri 2y ago

> Because if you can vibe code… so can everyone else. > And if everyone can do it, what makes you think Devin won’t replace you? Devin won't replace you if you can create valuable products through "vibe coding" or whatever else you call it. when coding itself becomes a commodity, value creation becomes more concentrated up the stack: what you choose to build, how well you market / sell it, how you connect with your customers, product design. Devin won't outcompete humans at these skills anytime soon. instead of sticking to a skill that's quickly becoming a commodity (as the author recommends), moving up the stack is the way to go (outside of very niche, specialized engineering domains - e.g: training base models).

ZaoLahma 2y ago

AI does not and will not solve the most difficult part of programming: Expressing how you wish to solve a problem in simple terms. It doesn't matter if you communicate with a compiler or an LLM - you still need to express your thoughts and ideas with no ambiguity for it to produce the wanted behavior. What makes "vibe coding" with an LLM both easier and more challenging at the same time is that is will guess what you mean and give you results that "kind of " work even when you express yourself unclearly. For someone who can code, the "kind of work" results can be used as a starting point to evolve into something useful. For someone who can't code, it's an inevitable dead end. I find that those who struggle with programming have the exact same type of struggles when trying to do it with LLMs - no structured plan on how to approach a problem and difficulties to understand the context in which they are working.

CharlieDigital 2y ago

Probably the opposite is true: the more you know how to code, the less productive you'll be with AI. This has been my observation watching a non-technical friend build a SaaS as a one-man team in 4 months and is generating $#,000 in revenue within 2 months. The way he uses AI is just completely different from how the technical folks I know use AI because he doesn't think about the code at all. The way he instructs the AI is different from how engineers prompt the AI. I actually think that his success with AI is in particular because he doesn't know how to code but was previously managing projects and offshore teams (so lots of writing down exactly what he wants, but with no specifics on how it gets implemented).

intelVISA 2y ago
Problem is what kind of moat does that SaaS have? The flip side of 'we replaced our dev team with vibe coders look how fast we print shitware' is now shitware value falls close to 0, as anyone can make it. Though you suggest he's non-technical... "writing down exactly what he wants" is just coding!
- exodust 2y ago
  > "writing down exactly what he wants" is just coding! Agreed. The more exact and clear your instructions are, the closer to programming it is. Presumably the non-technical person has an application where they care about things like performance, scalability, compatibility and all those things coders sweat over.
- CharlieDigital 2y ago
  > "writing down exactly what he wants" is just coding! That would make good project managers and business analysts "coders" and they are not coders. It is only in this age with LLMs does that line between functional requirements and code become blurred. He doesn't know how to write code well; he knows how to write requirements and instructions well from managing offshore teams. In practice, his instructions are detailed in the functional domain. Engineers bias too much in the technical domain. > The flip side of 'we replaced our dev team with vibe coders look how fast we print shitware' is now shitware value falls close to 0, as anyone can make it. Actually, he recognizes this and said something to the effect of "this is the end of SaaS" meaning that anyone can build this. That's his biggest fear going all in on this (he is still keeping his day job despite this project gaining traction so quickly) But I don't think this is true; I think there are still some technical barriers (at the moment) like one needs to know to instruct about databases, set up external services, etc. The AI is writing the connections to some third party APIs, but one needs to know what an API is and which one to use to instruct the agent. A future may be coming where this is no longer the case (e.g. combining deep research and computer use that will automatically set up domains, connect external services, etc.), but it's not here yet. > 'shitware' Is it "shitware" if customers are paying because they are deriving value from it? He's got 30 customers, a few of which paid annual subscriptions because it provided value to their actual business. Is it "shitware" because it's not handcrafted? Does it matter if it's solving some real problem and customers want to pay for it?

wickedsight 2y ago

I'm getting back into programming after a couple of years other roles. I have to learn a framework I haven't worked before and get to know new paradigms I never used. In a way, I'm feeling lucky that my company currently explicitly bans the use of AI tools on our code bases (for good reasons). This forces me to write all my own code and understand what it's doing. The only thing I use AI tools for is to explain some new concepts or paradigms in ways I can understand. What's also great is that I can throw some code from Stack or Github in there and get it explained. I'm glad these tools exist, since they make learning much easier, but they're also a trap if you depend on them in stead of your own knowledge.

keepamovin 2y ago

That is what I did. I programmed since I was 10 on and off until around age 27 where I started basically full time after studying chemistry but not wanting to work in the lab. I was 100% FT on a project since 2018/2019 and began using AI when ChatGPT came out, but couldn't use it on this project for ages because it was all giant legacy code with lots of context (both explicit and implicit). I used it for new projects and side things. I really enjoyed it. I learned SQL and Bash and PowerShell from the collaborations. I also made my first macOS app. I have even learned a few new things in JavaScript which is my main and began to use it on my main project too. I feel so lucky to be alive at this time. It's amazing to have this way to work!

jillesvangurp 2y ago

I've been programming for a few decades. I love LLMs. They make tedious things quick. Help me resolve gnarly issues. Make short work of writing unit tests. Generate oodles of boilerplate at will. Etc. It makes me more productive and less reluctant to take on risky things. By risky I mean things that formerly would have likely derailed my busy schedule because I'd get side tracked for to long and would have to de-prioritize more important stuff. Anyway, resistance is futile. You will be assimilated ... or retired. The reality of our job is that new generations are going to come in and they'll be using all the latest tools and gadgets. That's nothing new. And I'm part of a generation that in a decade or two will be mostly on the sidelines enjoying retirement. So, I'm well aware that progress isn't going to stop over my whining and grumbling. It annoys me when I catch myself doing that. I want to be better than that. LLMs are part of the job now. They are tools. And tools are only as good as the people wielding them. So, skill up and learn. It's not like it's very hard. If you are getting poor results, you might be doing it wrong. Figure it out; part of the job. Your mileage may vary. But there are a lot of tools and chances are you just haven't found the right one yet. Also, if some tool/llm limitation is blocking getting good results for something, wait 3 months and try again. The pace of progress is ridiculous currently. Or better yet: become part of the solution and make your own tools. This stuff is stupidly easy. It's prompt engineering with some trivial plumbing around them mostly. And you can generate the plumbing (what, you were going to do that manually?). That's why there are so many AI tools popping up right now. Most of them won't survive very long. But there are some good ideas lurking there.

dingnuts 2y ago
I've been programming for a few decades. I hate LLMs. They generate oodles of buggy shite that I have to fix by hand. They frequently steal my time and make me less productive because people on this site say I have to learn them or retire, and then I waste time looking up the details the bot got wrong. They're a slot machine and the people who think they are good are justifying an addiction and sunk costs. So retire me, I guess. I'm probably younger than you, but I'm almost ready to retire because I'm cheap and I don't buy into expensive fads, so I'm almost ready to cash out of this nightmare except then you realize the valuations of anthropic etc are propping up the whole economy and doing so on the promise that LLMs are going to deliver AGI! LLMs are marginally useful in some contexts. But I have seen absolutely nothing -- nothing -- to justify the costs or the valuations of these companies. They are definitely not AGI and before you accuse me of moving the goalposts, the AI companies are the ones promising this. It's a bubble. It's easy to get started. Good luck building a real product with just AI though. Good luck with that. If you turn out to be right I will happily exit this God forsaken industry. Lord free me from silicon valley; I liked computers. Not this. Not these people.

grumbel 2y ago

Ignoring AI would be foolish, since AI is the best programming tutor you can wish for and will speed up your learning noticeably, since you can always ask for clarification or examples when something isn't clear. It's also a great way to get random data for testing. And it will help you unearth lesser known corners of a programming language that you might have overlooked otherwise. The downside is that at the current speed of improvement, AI might very well already be at escape velocity, where it improves faster than you, and you'll never be able to catch up and contribute anything useful. For a lot of small hobby projects, that's already the case. I don't think there are any easy answers here. Nothing wrong with learning to code because it's fun. But as a career choice, it might not have a lot of future, but then, neither might most other white-collar jobs. Weird times are ahead of us.

exodust 2y ago
> AI is the best programming tutor you can wish for...you can always ask for clarification or examples when something isn't clear Yep, AI can teach beginners the fundamentals with endless patience and examples to suit everyone's style and goals. Walking you through concepts and giving you simulated encouragement as you progress. Scary stuff, but that's how it is. But... as we know, it doesn't always provide the best solution. Or it gets muddled. When you point out its mistakes, it apologises, recognises the mistake and explains why its a mistake. It's reasoning is incredible, but it still makes mistakes. This could be very risky for production code. Related anecdote... I needed Photoshop help recently for horizontally offsetting a vignette effect. Surprisingly not easy. The built-in vignette filter can't be applied to a new blank layer, and is always centred on the image. AI suggested making it manually but I didn't want to do that, as I like the built-in vignette better. AI's next solution involved several complicated steps using channel isolation and weird selection masking etc. No thanks. Then my own brain sparked a better idea... simply increase the canvas size temporarily, apply the vignette, then crop back to the original size. Job done. I told AI about my solution and it was gushing with praise about how brilliant my solution was compared to its own. Moral: never stop trusting your own brain.
guappa 2y ago
I wonder what kind of trivial boring jobs people who keep saying that LLMs are so incredibly useful at programming must have to have that opinion. What does your day look like?

dansmyers 2y ago

I'm a professor at a small college. I teach intro programming most semesters and we're now moving to using tools like Cursor with no restrictions in upper-level courses. "How do students learn to code nowadays?" - I think about this pretty much all the time. In my intro class, the two main goals are to learn about structured programming (using loops, functions, etc.) and build a mental model of how programs execute. Students should be able to look at a piece of code and reason through what it does. I've moved most of the traditional homework problems into class and lab time, so I can observe the students coding without using AI. The out-of-class projects are now bigger and more creative and include specific steps to teach students how to use AI collaboratively. My upper-level students are now doing more ambitious and challenging projects. What we've seen is that AI moves the difficulty of programming away from remembering details of languages or frameworks, but rewards having a careful, structured development process: - Thinking hard and chatting about the problem and the changes you need to implement before doing anything - Keeping components encapsulated and thinking about interfaces - Controlling the scope of your changes; current AIs work best at the function or class level - Testing and validation - Good manual debugging skills; you can't rely on AI to fix everything for you - General system knowledge: networking, OS, data formats, databases One of my key theories is that AI might lower the value of "computer science" as a standalone major, but will lead to a lot more coding across fields that currently don't use it. The intersection of "not a traditional engineer" and "can work with AI to solve problems with code" is going to be an emerging skill set that will change a lot of disciplines.

greenchair 2y ago
appreciate the insight
NeutralCrane 2y ago
This is by far the most interesting insight in this thread
ghaff 2y ago
I observe the course catalog at one not small college now has options for a lot of majors—many of which weren’t terribly computer-heavy historically.

amelius 2y ago

I want an AI that can reliably help me refactor a codebase.

DeathArrow 2y ago

To each, their own. To deeply understand an area you have to learn it from bottom up. I learned BASIC as a small kid, using a clone of ZX Spectrum. I was aware that the memory was limited and that I can poke and peek a memory address to set or retrieve the info. I learned Pascal and then rapidly went to C and C++. I learned about pointers and how the memory is layed out and what are system calls. I learned about CPUs and I learned some X86 assembly. Ar the university I learned about digital circuits and how to assemble one using logical gates. Of course I learned much more, data structures, algorithms, operating systems, distributed systems, parallel and concurrent programming, formal languages and automata theory, cryptography, web, lots of stuff. I learned other lots of stuff by myself. I've built desktop apps, websites, software for microcontrollers, games, web applications and now I am working on microservices based apps running in cloud. I was a junior developer, graduated somehow to senior. I worked as a software architect and now I am a team leader. These days I work almost exclusively with C#, but I am also interested in other languages if I have some spare time to evaluate them. What I want to say is this: is not enough to learn the highest level of technology of today. Today that is AI, few years ago it was JS frameworks, more years ago it was Java, .NET, Python. To be good at what you do you always have to learn all layers under the current top layer. Learn from bottom up. You don't have to be good at every technical detail, but you have to understand at least how the things work.

daerogami 2y ago
To add to this, if someone depends on AI (the top-layer in your example) and doesn't learn the the 'how's and the 'why's of programming, they or their organization will be completely beholden and dependent on the organizations running those AI tools. Not a great position to be in.

littlecranky67 2y ago

That advice was true already a decade ago, but replace AI with StackOverflow. I encountered many junior devs (mostly money-driven, not out of passion for software development) that were completely fine just copy-pasting code out of Stackoverflow without getting a deeper understanding or at least trying to understand what their copied code does. Same is true for AI. Both are great tools, but to become truly a master of your craft you should always thrive to become the person that would have answered the SO question - or wrote the article that the AI learned from.

nightfox1 2y ago

This resonates a lot with what I’ve seen outside of code too. I’ve been building an AI chess coach and noticed the same pattern: people plug their games into Stockfish, see a list of best moves, and walk away thinking they’ve “analyzed” the game. But real understanding — like in programming — only comes from engaging with why things went wrong. That’s what I’m trying to fix. Instead of just showing lines, my AI coach gives voice-guided feedback, visual highlights, and practical insights. More like working with a real coach than sifting through raw engine output. The goal is to make analysis as engaging as playing—and shift the mindset from “just tell me the best move” to “help me think better.” Demo if curious: https://www.loom.com/share/9e1578f1348841c1992c5d902e371312?sid=56108d1f-e81a-4538-84e9-c4792e96aea1 https://www.loom.com/share/9e1578f1348841c1992c5d902e371312?...

morcus 2y ago
Seems like an interesting idea - is it only tactics in scope or has does the AI also do well at analyzing strategic ideas? Some other thoughts: Isn't the first example just wrong? The AI says "after dxe3 Rxd8 Rxd8, white wins the exchange, gaining a Rook for a Bishop" but unless I am mistaken actually it's a Queen for a Rook and Bishop? Also, it seems the visual highlight AI referenced is not working? Talks about Rad1 while the pawn is still highlighted.
- nightfox1 2y ago
  It will do both tactics and strategy. Also working on incorporating positional concepts. Yes you are right. It is still in demo phase, it still does make mistakes. I am refining the model and inputs, so definitely a work in progress :) Regarding the circle highlighting, the agent is deciding / reasoning which square to highlight. So it is non-determinsitic, so it is sometimes right / wrong. It will definitely get better as the models improve

voidhorse 2y ago

There are a lot of reasons I dislike the use of LLMs in software, one of which is that I think it's absurd to claim that using such fuzzy and imprecise tools and methods should be considered engineering... But to be honest, I think the main thing is that they just absolutely suck the joy and fun out of an activity. I like writing, I like coding, these are things that I do at least in part because I get some kind of direct enjoyment out of doing them. Using a chatbot simply is not interesting or fun to me. It's like being a spectator and thinking that means you "participated" in the game you watched. If you code or whatever just as a means to make ends meet sure, it makes total sense that you'll want to use these tools, but I will absolutely never understand the people that claim to like a craft and reach for LLMs to do it—to me these people have just entirely missed the point of what it means to have an activity you enjoy. It's not about the output, it's all about the process and self-enrichment that happens along the way.

ghaff 2y ago
You seem to be saying that you’re more interested in writing code than understanding problems and designing architectural solutions to them that exploit the best available tools to help create the actual code. Which may be LLMs (to some degree) at this point. But maybe that’s not your intent.

wintorez 2y ago

This is the way.

ArthurStacks 2y ago

The only people saying this kind of thing are coders desperate to stay relevant. There is no future in coding. Its gone in a few years. Instead begin learning the skills required to work with AI to get it create what you want.

guappa 2y ago
https://news.ycombinator.com/item?id=43504924 https://news.ycombinator.com/item?id=43504924
- ArthurStacks 2y ago
  I run a software development business. I know as good as anyone where things are headed
  - guappa 2y ago
    So you're not a software developer and can't really evaluate how useful it is?
    - ArthurStacks 2y ago
      You should have spent more time in school
      - guappa 2y ago
        Is there any research that shows that failing years in school and remaining longer than expected is linked with blindly believing anything AI grifters say?

sunwukung 2y ago

I've been following some kid on TikTok who started last year on this journey - and it's been truly frustrating to watch. I tried to discourage them from leaning so heavily on AI, but they insisted it was a different way of learning. A year later, and they still don't comprehend for loops or conditional blocks, and believe that comprehending this basic material is a deep understanding of code.

kornaki 2y ago

I think of it as a magic wand that makes me more efficient when it comes to smaller projects. I now do things I would earlier not even pick up because I simply type less now. But I feel like you need to have intuition/experience to question AI all the time. Why this code was added? Is it safe? Is it the right way? Is it the right method, tool, library, maybe we can try another approach. I feel like I learn faster too, because I can so quickly ask a question in a context with which AI is familiar. I would neither down play its role or follow "learning how to code is useless" hypers.

bookofjoe 2y ago

I've stopped reading HN posts about AI because comments on them are the same old same old: 2 camps, one of which says get over it 'cause it's great, the other of which says it's a complete FAIL and always will be.

sieste 2y ago

s/code/think/g

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nialv7 2y ago

Re what Replit CEO said: i mean sure, learn how to think, learn how to breakdown problems and communicate - good skills to have, regardless of AI or not. and learning how to code is one of the great ways to improve these skills. people generally aren't going to learn how to think in a vacuum, right? Math, science, and programming, among others, that's how most people learn how to think, they are not going to be a waste of time.

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fmxsh 2y ago

In a way, "vibe coding" is like what infants do when they give "error messages" of "hungry" to query mom for food. Newcomers may be tempted to maintain the uttermost ignorance of what they are creating, as I imagine "vibe coding" implies, where the height of problem-solving is creating quicker pipes between errors and re-submission to AI to fix those errors. I'm really glad I learned programming a long time ago, before AI. I use AI more like a tool for getting information (much like browsing manuals, forums, Stack Overflow), but it is, of course, magnitudes better. I still do the conceptual outlining and problem solving, and that is what programming is to me. If there's something I don't understand from the AI, I always query to know how it works. It's even easier now to understand how things work thanks to AI.