5 ms·

Fast and Hard Code

115 points by tosh 2mo ago

Tim_yanxi 2mo ago
[flagged]
tosh 2mo ago
what i'm seeing is agentic coding helps be(come) more ambitious build your own framework, database, operating system, game engine etc things that used to be infeasible (too hard, too big, …)
- ChrisMarshallNY 2mo ago
  > agentic coding In my personal experience, agentic coding wasn’t useful, but using a chat inference, was. I still need to be the critical path, but the LLM has, indeed, become a major force multiplier. A few minutes ago, I submitted an app for review, that I started work on, alone, in February. The Quality of the new version is astounding. I’m absolutely thrilled. It’s a full rewrite (backend server, and frontend client) of a fairly large app that’s been shipping for a couple of years, and that took over two years, to originally write. I wouldn’t have even tried it, without an LLM. That made all the difference. The majority of the work was done with the $20/month ChatGPT Plus subscription, but the last few days, as I developed supporting materials and Web sites, I used the $100/month Pro level. After my work, over the last few months, the upgrade was a “no brainer.” But, at every step of the way, I needed to be there, to intimately review and manage the interaction with the LLM. There’s no way that I could trust it to “just do it.” I’m sure that, sooner or later (likely sooner), LLMs will have progressed to the point that I can trust them to vibe-code a project like this, but I guarantee, that they aren’t quite there, yet. To be fair, I know that I may have much higher standards than a fairly significant number of developers, but the end product of my work is about as far from “AI slop” as you can get.
  - noduerme 2mo ago
    When it's your own codebase that you know intimately, you obviously don't want it polluted, and you want to continue to understand everything that's there. For rewriting things you understand perfectly, or porting code to different platforms, the LLMs truly are a force multiplier. But that's so different from the way they are used on new projects. Letting them make design decisions is the problem. To make design decisions, you have to understand the system as a whole.
  - tosh 2mo ago
    you can also situate the agent within your codebase and have it only write things you review (or have it not write/change the code at all)
  - Krei-se 2mo ago
    > as far from “AI slop” as you can get as always: no code, no link, not even a description. Incoming reasons: possible doxx, "internal", etc. pp.
    - ChrisMarshallNY 2mo ago
      Sigh... Seriously? I've explained this many times, but I assume that doing background research before insulting isn't a "modern" thing to do. Just Ready, Fire, Aim. Seriously, you could probably use ChatGPT to make a decent guess. The issue is that the app addresses a specific (very privacy-aware) demographic. Each signup is manually vetted by two admins. It will probably never have more than a couple of thousand users, and the ones that are there, are more than a little [justified] paranoid. Having several thousand curious geeks, do throwaway signups, just so they can see that the app is not for them, is not going to be helpful, so I never mention it here. If anyone really wants to know about it, I'm easy to contact. Unlike lots of folks, here, I am quite open about who I am. The app, itself, is closed-source, but uses a significant number of open-source dependencies (that I also wrote -sometimes with AI help), which are easy to see. And that's all I'll say. Have a great day!
      - inigyou 2mo ago
        Thanks for confirming Krei-se was right.
        ChrisMarshallNY 2mo ago
        It's so inspiring to see high school students participating here! Have a great day!
      - Krei-se 2mo ago
        called it
- adammarples 2mo ago
  I don't even know any more. I wanted a weather bapp that shows the whole forecast on one page with no scrolling, so I was ambitious and asked anti-gravity to build one for me. Half an hour later, done. Then I asked codex to review it and half the stuff didn't even work, made up wind gust data, misaligned hourly data, polluted caches. So I asked codex to fix the issues. Did it? I don't even know, it said it did.
  - kaashif 2mo ago
    The way to use AI is to make sure it has clear, verifiable success criteria, test suites, etc. Make sure any output has citations, reduce the need for trust to zero, etc. I see people one shot stuff and it makes no sense, is completely fake half the time, just like you point out. It should be the case that Codex and Claude Code should incorporate this kind of thing automatically at some point.
    - gwerbin 2mo ago
      Claude Code more or less does have the tools to do this: plan mode, todo lists, user question prompts, et al. What it does not have is a "guided" mode where the agent (or harness) interviews you and helps you structure a work plan for the agent, including eliciting those success criteria and any design constraints the user might have in mind (eg it will be used on a boat over slow satellite connection). I can't speak for OpenAI but I get the impression that Anthropic think of these things as opt-in power user features, perhaps on the premise that their LLMs alone are "smart enough".
  - mynegation 2mo ago
    Great minds… that’s what I vibe coded with Claude couple of weeks ago.
  - blfr 2mo ago
    Try Fable and make it write a ton of tests. I generally don't trust benchmarks, as they don't match my experience, but this one[1] very much does. [1] https://www.primeintellect.ai/research/nanogpt-speedrun https://www.primeintellect.ai/research/nanogpt-speedrun
- inigyou 2mo ago
  Is it really building your own if it's just rephrasing training data? Or is it license laundering?
  - illuminator83 2mo ago
    People do the same. Everybody learns from what was there before and then added or changed things. No difference.
  - Pannoniae 2mo ago
    Do you really care if it works?
- br121 2mo ago
  When I first started learning game engines there were a lot of "understend a game engine by building one" courses in various forms, and a lot of open source projects (plus the closed source/never published ones I don't know about) that where the implementation of an engine or a kernel or a database based on a known book on the field. So it's at least not entirely a result of agentic coding and AI in general, even tho it probably incentivized the phenomenon
superjose 2mo ago
I'd say it depends. On the degree the software evolves and will be used. The reason we've spent years discovering patterns, creating special syntaxes has been to tackle certain domain problems more efficiently and to have systems that can evolve through time. The only constant is change. Albeit LLMs chunk out code (and with great know how impressive output), the developer must have the know how to pass a certain threshold. Writing in unknown languages may seem fine at first. But once you go to the edge, you'll be finding certain quirks, inefficiencies along the way that the LLM may work around it instead of removing it from root. For example, I've been learning Effect.ts for some weeks now. I've used LLMs extensively, but before that there were a series of manual coding rounds first. To understand composability, the nitty gritty, where things break, how, how the syntax is formed, and how could I structure some observability challenges I had around the library. If I hadn't gone through that process, the code quality would be subpar. It wouldn't have been evident at first, but once the system would begin to evolve and adapt to feedback, things would be brittle, existing customers would be affected, and more. I like to move fast without breaking things
noduerme 2mo ago
As someone not in the know about cryptography, I know just enought that the words "custom cryptography" scare the hell out of me.
- deadbabe 2mo ago
  It's time to get over the "never roll your own crypto!" bs. AI can roll you crypto far better than what humans have built by hand. They can literally test things to an extent that no human ever would.
  - Jhater 2mo ago
    Lmao, please go do that and get back to me. The Dunning Krueger in this day and age is alarming.
    - RunSet 2mo ago
      If no one rolled their own crypto then there would be none. "Don't roll your own crypto." sounds a lot like "Don't you worry about crypto. Let _me_ worry about crypto."
      - svpk 2mo ago
        That's not really the point of the saying though. The point is more so that if you are the kind of person who is in a position to roll your own crypto you probably have a PhD and have worked with cryptography for years. And the thing that you're setting out to do is to produce a cryptography library. If you're that kind of person, then sure go for it! But if you're a top person in the field of cryptography you didn't need anyone to tell you if you were fit to make a cryptography library anyway. And if you're not that kind of person you do need someone to tell you because the whole field is a minefield where subtle oversights break the whole thing. If you want to just implement cryptography as a fun learning experience that's great. But actual implementations that people will actually depend on need to be handled by experts.
        2mo ago
sorokod 2mo ago
Fast and Hard - very much like Zapp Brannigan's love
Jhater 2mo ago
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uygar 2mo ago
[dead]
jeffrallen 2mo ago
Fine article, though it ended on a low note with the comment about cryptography engineers gatekeeping the technology. I have worked on high stakes crypto code. Getting it right requires a level of knowledge, care and engineering conservativism that is very hard to come by. I was teaching students. I wasn't gatekeeping. But a vanishingly small percentage of them were able to make secure software, or analyze existing code to know if it was secure. In as much as AI coding makes testing or code verification cheaper, sure let's use it. But cryptography engineering is hard for reasons that are not "write moar code" and so AI coding should not be used on production crypto work.
jbstack 2mo ago
> one thing is pretty clear: the act of familiarizing yourself with a language no longer matters I completely disagree with this statement as a premise to the article. Sure, if you have zero care about whether the agent's work is reliable or not, then there's no need to learn a language. But if you're a developer who cares about their work and isn't just outputting 100% vibe code, then at a minimum you should be familiar enough with the language that you can review the agent's output ,follow along with the code, and make an informed decision about whether to commit. Interestingly, I've found that my approach to learning languages has fundamentally changed. Before, I'd study a book on the one or two languages which were important to me at that time. The goal was to become proficient. Now I choose to read about a variety of languages simply because they demonstrate some interesting paradigm that is new to me (e.g. Haskell -> functional, Elixir -> concurrency). I read a programming book like I'd read an engaging narrative non-fiction book: cover to cover relatively quickly, then I'm done. This gives me that "familiarity" which is useful for agentic coding, without bothering to learn every obscure bit of syntax or library call. My priority has become breadth (get an overview of many languages and paradigms) rather than depth (learn a language or two really well).
- dpritchett 2mo ago
  The author and his cited examples are folks with decades of experience shipping broadly used OSS so for them it’s probably a lot less of an issue to switch languages, even if the agent is papering over a lot of the details for them in the initial releases.
willtemperley 2mo ago
I think this is true to an extent, but it really depends on how much information the LLM has on a topic. They’re amazing at maths because maths has been open source since day 0. They’ve great at algorithms for similar reasons. C bindings are a doddle because there’s so much prior art available. They’re terrible at using cutting edge features in languages because there’s not much data yet. I think it’s fairly easy to predict what they’re good at on this basis. I’m not sure why they suck at UI design though.
- ChrisMarshallNY 2mo ago
  > I’m not sure why they suck at UI design though. I think they do OK, if you are fine with middle-of-the-road, default stuff. Also, I have found that it's important to provide guidance, constraints, and context to the LLM. I have been working on a native iOS Swift app, for the last few months, and our team consulted an LLM (might be ChatGPT, might be Claude -I wasn't the one that consulted it), for graphic and interaction design. Some context: We have written a 2.0/full rewrite of an existing app, that has been shipping for a couple of years. The 1.X version was designed by a professional graphic designer, but we didn't have him available for the rewrite, so we had to make do with our own guidance (questionable), and LLMs (also questionable, but for different reasons). Anyway, As I started on the project, I kept getting designs that were, quite frankly, awful. They looked like generic Apple SwiftUI app screens, or worse, old Facebook app screens, with absolutely no relation to the current app. I had to basically ignore most of the graphic layout, and use only the interaction design. After hearing complaints about "not making it look like the screens I sent you," I explained that they needed to train their LLM on the current design. There was no way that I was going to implement those ghastly graphics (It is so good to be able to do that. I'm retired, and working for free. In the old days, I would have had to take out a spoon, tuck in a bib, and eat shit). They did that, and suddenly, their submissions were great, and I could start using them.
  - willtemperley 2mo ago
    Thanks that’s an interesting anecdote to me because I’m also developing SwiftUI apps. Claude will create something that technically works but looks terrible. I don’t have the luxury of a previously well designed app to train Claude on, but I’m finding just building the UI the old fashioned way then asking Claude to fix the bugs works to an extent. I’m hoping that creating a comprehensive design system with good semantic naming will help.
qsera 2mo ago
> All of a sudden I have seen people do some really impressive stuff with DWARF files, eBPF, custom network drivers, custom crypto and really old computing hardware. Many of these things were previously off-limits for lots of developers. In some cases (eg: crypto) you were even pushed away because those things were intentionally gatekept by the people in the know. Before at least some of us were forced to understand stuff, because without understanding it was not possible to do stuff that we really wanted to do, and some those got passionate and kept digging, and some of us even made even better stuff based on their experience. Now no one needs to understand anything, and now we will never have better stuff.
- meowface 2mo ago
  I'm not saying you're entirely wrong, but LLMs can actually be a way to create even better things than those better things. I've seen it in action.
  - jstimpfle 2mo ago
    How do you judge "better" if you don't understand the LLM output?
    - bauerd 2mo ago
      By quantifying the result.
      - jstimpfle 2mo ago
        What are you talking about?
        Bootvis 2mo ago
        You want to solve a family of problems using some tool. You measure the relevant solutions performance metrics. Now, you or someone else vibe-coded a new tool. You created new solutions and measure again. You have just quantified the result of using the new tool.
jhide 2mo ago
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andai 2mo ago
How do you check the code if you don't know the language?
jgalt212 2mo ago
> the act of familiarizing yourself with a language no longer matters Not so fast. I've seen all sorts of LLM-generated code that was not not inline with a what a human would write if such a human were familiar with the sharp edges of the language in question.
leecommamichael 2mo ago
> One of the memes on Twitter is that “programming is solved now.” I’m not sure to what degree it is, but one thing is pretty clear: the act of familiarizing yourself with a language no longer matters and some of the friction that mattered for humans does not matter for agents. > > As a result, LLMs make language choice much less consequential than it used to be. If you don’t like the choice, you can seemingly rewrite it in another language and you can make it pick a language that you, as a programmer, are entirely unfamiliar with. ... > I’m not sure to what degree it (programming) is (solved.) > the act of familiarizing yourself with a language no longer matters > LLMs make language choice much less consequential than it used to be. ... You're reasoning as if you think it's mostly solved. How the hell are you going to read the code with any reliability or speed if you aren't familiar with the language? I realize languages have broad similarities.
RetroTechie 2mo ago
I have difficulty grasping how one would call a software project theirs, without understanding the meat of how it's put together & how it works. Or having done a good chunk of the grunt work. Without such understanding, how is it 'your' project? Simply because you started it? Your taste / selection of design choices? Your "grand vision"? Your work in setting up some coding agent(s)? The prompt(s) you devised? Ideas are cheap. But good software comes from good understanding of the problem. Good understanding comes from analyzing the issues in detail. Knowing the trade-offs between different solutions. All of which is not cheap. It is that expertise & experience which earns experts their paycheck. When you did that, then sure, go ahead & have coding agents implement using a structure you designed, algorithms you picked, reviewing the code and test results. But just vibe-code a whole project & kick it out the door? Result might work but I'd be more impressed by the coding agents' capabilities than your input. Article does give a nice hint about how the software landscape may change: "Many of these things were previously off-limits for lots of developers (..) So maybe the world will have more slop, but it might also have more developers in it, that want things to be fast and small."
librasteve 2mo ago
as a test of the proposition that human oriented software languages are redundant, I asked my favourite agent to rewrite some code in asm … and yes, it ran and it was fast conclusion… well, it’s scary but actually I think it’s a bit useless too … it’ll never catch on
- llleeeoooh 2mo ago
  I am confused. It succeeded at the task, why is the conclusion that it will never catch on ?
brainless 2mo ago
I do not know where things will go but here are some things I have been feeling: - We have tons of languages (and libraries/frameworks on top) because we, humans, have too many preferences - Many of these preferences are also abstractions because of how quickly (and with less knowledge of the underlying systems) we wanted to build things - LLMs can operate on most (any?) of these layers and the results we get depend on how much high level knowledge the operator has - LLMs + agents are able to do more and more of the digging, experimenting and ranking of different paths on their own to select good paths - As someone who is assisted by LLMs, I can focus on codifying my internal process into custom agent/harness while also building end-user software (build the shipyard while building ships) - I can reach out to any language (I am one of those who do not know Rust deeply but use it all the time) or any part of the stack now
yipinwong 2mo ago
What I got was, be more generalist and become a polymath. My thoughts below --- This means, we need to read more to produce more in many different fields, and domains. The idea is also captured in today's top 10 article, "To become a better writer, read as much as you can" (https://news.ycombinator.com/item?id=49405870 https://news.ycombinator.com/item?id=49405870) where if you want to produce good writings, read more. Reading more here means, familiarizing/learning/understanding many different fields/domains. I have never heard of "DWARF files, eBPF," and at least reading gave me an idea on what to learn about, so that when I work on projects, I can consider them by guiding AIs to even consider them. Until today, I'd never woulda have though to even consider "DWARF files, eBPF,". Now I can dig deeper into them and see what they are, and at least know what they used for and how they are used in practice.
hakesson 2mo ago
For the "harder tech" part: I played around with a "vibe code" project to see how far it gets. It's a cargo workspace linter that does things like find unused feature flags, unused pub, etc. Guiding it only on high-level feature-set requirements, it ended up doing workspace-wide lints backed by rustc's name resolution, not a parser. Something I would never have done myself. I picked that project because a missed lint costs nothing - I still wouldn't work this way on anything where a wrong answer hurts - yet.

115 points by tosh 2mo ago

[flagged]

tosh 2mo ago

what i'm seeing is agentic coding helps be(come) more ambitious build your own framework, database, operating system, game engine etc things that used to be infeasible (too hard, too big, …)

ChrisMarshallNY 2mo ago
> agentic coding In my personal experience, agentic coding wasn’t useful, but using a chat inference, was. I still need to be the critical path, but the LLM has, indeed, become a major force multiplier. A few minutes ago, I submitted an app for review, that I started work on, alone, in February. The Quality of the new version is astounding. I’m absolutely thrilled. It’s a full rewrite (backend server, and frontend client) of a fairly large app that’s been shipping for a couple of years, and that took over two years, to originally write. I wouldn’t have even tried it, without an LLM. That made all the difference. The majority of the work was done with the $20/month ChatGPT Plus subscription, but the last few days, as I developed supporting materials and Web sites, I used the $100/month Pro level. After my work, over the last few months, the upgrade was a “no brainer.” But, at every step of the way, I needed to be there, to intimately review and manage the interaction with the LLM. There’s no way that I could trust it to “just do it.” I’m sure that, sooner or later (likely sooner), LLMs will have progressed to the point that I can trust them to vibe-code a project like this, but I guarantee, that they aren’t quite there, yet. To be fair, I know that I may have much higher standards than a fairly significant number of developers, but the end product of my work is about as far from “AI slop” as you can get.
- noduerme 2mo ago
  When it's your own codebase that you know intimately, you obviously don't want it polluted, and you want to continue to understand everything that's there. For rewriting things you understand perfectly, or porting code to different platforms, the LLMs truly are a force multiplier. But that's so different from the way they are used on new projects. Letting them make design decisions is the problem. To make design decisions, you have to understand the system as a whole.
- tosh 2mo ago
  you can also situate the agent within your codebase and have it only write things you review (or have it not write/change the code at all)
- Krei-se 2mo ago
  > as far from “AI slop” as you can get as always: no code, no link, not even a description. Incoming reasons: possible doxx, "internal", etc. pp.
  - ChrisMarshallNY 2mo ago
    Sigh... Seriously? I've explained this many times, but I assume that doing background research before insulting isn't a "modern" thing to do. Just Ready, Fire, Aim. Seriously, you could probably use ChatGPT to make a decent guess. The issue is that the app addresses a specific (very privacy-aware) demographic. Each signup is manually vetted by two admins. It will probably never have more than a couple of thousand users, and the ones that are there, are more than a little [justified] paranoid. Having several thousand curious geeks, do throwaway signups, just so they can see that the app is not for them, is not going to be helpful, so I never mention it here. If anyone really wants to know about it, I'm easy to contact. Unlike lots of folks, here, I am quite open about who I am. The app, itself, is closed-source, but uses a significant number of open-source dependencies (that I also wrote -sometimes with AI help), which are easy to see. And that's all I'll say. Have a great day!
    - inigyou 2mo ago
      Thanks for confirming Krei-se was right.
      - ChrisMarshallNY 2mo ago
        It's so inspiring to see high school students participating here! Have a great day!
    - Krei-se 2mo ago
      called it
adammarples 2mo ago
I don't even know any more. I wanted a weather bapp that shows the whole forecast on one page with no scrolling, so I was ambitious and asked anti-gravity to build one for me. Half an hour later, done. Then I asked codex to review it and half the stuff didn't even work, made up wind gust data, misaligned hourly data, polluted caches. So I asked codex to fix the issues. Did it? I don't even know, it said it did.
- kaashif 2mo ago
  The way to use AI is to make sure it has clear, verifiable success criteria, test suites, etc. Make sure any output has citations, reduce the need for trust to zero, etc. I see people one shot stuff and it makes no sense, is completely fake half the time, just like you point out. It should be the case that Codex and Claude Code should incorporate this kind of thing automatically at some point.
  - gwerbin 2mo ago
    Claude Code more or less does have the tools to do this: plan mode, todo lists, user question prompts, et al. What it does not have is a "guided" mode where the agent (or harness) interviews you and helps you structure a work plan for the agent, including eliciting those success criteria and any design constraints the user might have in mind (eg it will be used on a boat over slow satellite connection). I can't speak for OpenAI but I get the impression that Anthropic think of these things as opt-in power user features, perhaps on the premise that their LLMs alone are "smart enough".
- mynegation 2mo ago
  Great minds… that’s what I vibe coded with Claude couple of weeks ago.
- blfr 2mo ago
  Try Fable and make it write a ton of tests. I generally don't trust benchmarks, as they don't match my experience, but this one[1] very much does. [1] https://www.primeintellect.ai/research/nanogpt-speedrun https://www.primeintellect.ai/research/nanogpt-speedrun
inigyou 2mo ago
Is it really building your own if it's just rephrasing training data? Or is it license laundering?
- illuminator83 2mo ago
  People do the same. Everybody learns from what was there before and then added or changed things. No difference.
- Pannoniae 2mo ago
  Do you really care if it works?
br121 2mo ago
When I first started learning game engines there were a lot of "understend a game engine by building one" courses in various forms, and a lot of open source projects (plus the closed source/never published ones I don't know about) that where the implementation of an engine or a kernel or a database based on a known book on the field. So it's at least not entirely a result of agentic coding and AI in general, even tho it probably incentivized the phenomenon

superjose 2mo ago

I'd say it depends. On the degree the software evolves and will be used. The reason we've spent years discovering patterns, creating special syntaxes has been to tackle certain domain problems more efficiently and to have systems that can evolve through time. The only constant is change. Albeit LLMs chunk out code (and with great know how impressive output), the developer must have the know how to pass a certain threshold. Writing in unknown languages may seem fine at first. But once you go to the edge, you'll be finding certain quirks, inefficiencies along the way that the LLM may work around it instead of removing it from root. For example, I've been learning Effect.ts for some weeks now. I've used LLMs extensively, but before that there were a series of manual coding rounds first. To understand composability, the nitty gritty, where things break, how, how the syntax is formed, and how could I structure some observability challenges I had around the library. If I hadn't gone through that process, the code quality would be subpar. It wouldn't have been evident at first, but once the system would begin to evolve and adapt to feedback, things would be brittle, existing customers would be affected, and more. I like to move fast without breaking things

noduerme 2mo ago

As someone not in the know about cryptography, I know just enought that the words "custom cryptography" scare the hell out of me.

deadbabe 2mo ago
It's time to get over the "never roll your own crypto!" bs. AI can roll you crypto far better than what humans have built by hand. They can literally test things to an extent that no human ever would.
- Jhater 2mo ago
  Lmao, please go do that and get back to me. The Dunning Krueger in this day and age is alarming.
  - RunSet 2mo ago
    If no one rolled their own crypto then there would be none. "Don't roll your own crypto." sounds a lot like "Don't you worry about crypto. Let _me_ worry about crypto."
    - svpk 2mo ago
      That's not really the point of the saying though. The point is more so that if you are the kind of person who is in a position to roll your own crypto you probably have a PhD and have worked with cryptography for years. And the thing that you're setting out to do is to produce a cryptography library. If you're that kind of person, then sure go for it! But if you're a top person in the field of cryptography you didn't need anyone to tell you if you were fit to make a cryptography library anyway. And if you're not that kind of person you do need someone to tell you because the whole field is a minefield where subtle oversights break the whole thing. If you want to just implement cryptography as a fun learning experience that's great. But actual implementations that people will actually depend on need to be handled by experts.
      - 2mo ago

sorokod 2mo ago

Fast and Hard - very much like Zapp Brannigan's love

Jhater 2mo ago

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uygar 2mo ago

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jeffrallen 2mo ago

Fine article, though it ended on a low note with the comment about cryptography engineers gatekeeping the technology. I have worked on high stakes crypto code. Getting it right requires a level of knowledge, care and engineering conservativism that is very hard to come by. I was teaching students. I wasn't gatekeeping. But a vanishingly small percentage of them were able to make secure software, or analyze existing code to know if it was secure. In as much as AI coding makes testing or code verification cheaper, sure let's use it. But cryptography engineering is hard for reasons that are not "write moar code" and so AI coding should not be used on production crypto work.

jbstack 2mo ago

> one thing is pretty clear: the act of familiarizing yourself with a language no longer matters I completely disagree with this statement as a premise to the article. Sure, if you have zero care about whether the agent's work is reliable or not, then there's no need to learn a language. But if you're a developer who cares about their work and isn't just outputting 100% vibe code, then at a minimum you should be familiar enough with the language that you can review the agent's output ,follow along with the code, and make an informed decision about whether to commit. Interestingly, I've found that my approach to learning languages has fundamentally changed. Before, I'd study a book on the one or two languages which were important to me at that time. The goal was to become proficient. Now I choose to read about a variety of languages simply because they demonstrate some interesting paradigm that is new to me (e.g. Haskell -> functional, Elixir -> concurrency). I read a programming book like I'd read an engaging narrative non-fiction book: cover to cover relatively quickly, then I'm done. This gives me that "familiarity" which is useful for agentic coding, without bothering to learn every obscure bit of syntax or library call. My priority has become breadth (get an overview of many languages and paradigms) rather than depth (learn a language or two really well).

dpritchett 2mo ago
The author and his cited examples are folks with decades of experience shipping broadly used OSS so for them it’s probably a lot less of an issue to switch languages, even if the agent is papering over a lot of the details for them in the initial releases.

willtemperley 2mo ago

I think this is true to an extent, but it really depends on how much information the LLM has on a topic. They’re amazing at maths because maths has been open source since day 0. They’ve great at algorithms for similar reasons. C bindings are a doddle because there’s so much prior art available. They’re terrible at using cutting edge features in languages because there’s not much data yet. I think it’s fairly easy to predict what they’re good at on this basis. I’m not sure why they suck at UI design though.

ChrisMarshallNY 2mo ago
> I’m not sure why they suck at UI design though. I think they do OK, if you are fine with middle-of-the-road, default stuff. Also, I have found that it's important to provide guidance, constraints, and context to the LLM. I have been working on a native iOS Swift app, for the last few months, and our team consulted an LLM (might be ChatGPT, might be Claude -I wasn't the one that consulted it), for graphic and interaction design. Some context: We have written a 2.0/full rewrite of an existing app, that has been shipping for a couple of years. The 1.X version was designed by a professional graphic designer, but we didn't have him available for the rewrite, so we had to make do with our own guidance (questionable), and LLMs (also questionable, but for different reasons). Anyway, As I started on the project, I kept getting designs that were, quite frankly, awful. They looked like generic Apple SwiftUI app screens, or worse, old Facebook app screens, with absolutely no relation to the current app. I had to basically ignore most of the graphic layout, and use only the interaction design. After hearing complaints about "not making it look like the screens I sent you," I explained that they needed to train their LLM on the current design. There was no way that I was going to implement those ghastly graphics (It is so good to be able to do that. I'm retired, and working for free. In the old days, I would have had to take out a spoon, tuck in a bib, and eat shit). They did that, and suddenly, their submissions were great, and I could start using them.
- willtemperley 2mo ago
  Thanks that’s an interesting anecdote to me because I’m also developing SwiftUI apps. Claude will create something that technically works but looks terrible. I don’t have the luxury of a previously well designed app to train Claude on, but I’m finding just building the UI the old fashioned way then asking Claude to fix the bugs works to an extent. I’m hoping that creating a comprehensive design system with good semantic naming will help.

qsera 2mo ago

> All of a sudden I have seen people do some really impressive stuff with DWARF files, eBPF, custom network drivers, custom crypto and really old computing hardware. Many of these things were previously off-limits for lots of developers. In some cases (eg: crypto) you were even pushed away because those things were intentionally gatekept by the people in the know. Before at least some of us were forced to understand stuff, because without understanding it was not possible to do stuff that we really wanted to do, and some those got passionate and kept digging, and some of us even made even better stuff based on their experience. Now no one needs to understand anything, and now we will never have better stuff.

meowface 2mo ago
I'm not saying you're entirely wrong, but LLMs can actually be a way to create even better things than those better things. I've seen it in action.
- jstimpfle 2mo ago
  How do you judge "better" if you don't understand the LLM output?
  - bauerd 2mo ago
    By quantifying the result.
    - jstimpfle 2mo ago
      What are you talking about?
      - Bootvis 2mo ago
        You want to solve a family of problems using some tool. You measure the relevant solutions performance metrics. Now, you or someone else vibe-coded a new tool. You created new solutions and measure again. You have just quantified the result of using the new tool.

jhide 2mo ago

[dead]

andai 2mo ago

How do you check the code if you don't know the language?

jgalt212 2mo ago

> the act of familiarizing yourself with a language no longer matters Not so fast. I've seen all sorts of LLM-generated code that was not not inline with a what a human would write if such a human were familiar with the sharp edges of the language in question.

leecommamichael 2mo ago

> One of the memes on Twitter is that “programming is solved now.” I’m not sure to what degree it is, but one thing is pretty clear: the act of familiarizing yourself with a language no longer matters and some of the friction that mattered for humans does not matter for agents. > > As a result, LLMs make language choice much less consequential than it used to be. If you don’t like the choice, you can seemingly rewrite it in another language and you can make it pick a language that you, as a programmer, are entirely unfamiliar with. ... > I’m not sure to what degree it (programming) is (solved.) > the act of familiarizing yourself with a language no longer matters > LLMs make language choice much less consequential than it used to be. ... You're reasoning as if you think it's mostly solved. How the hell are you going to read the code with any reliability or speed if you aren't familiar with the language? I realize languages have broad similarities.

RetroTechie 2mo ago

I have difficulty grasping how one would call a software project theirs, without understanding the meat of how it's put together & how it works. Or having done a good chunk of the grunt work. Without such understanding, how is it 'your' project? Simply because you started it? Your taste / selection of design choices? Your "grand vision"? Your work in setting up some coding agent(s)? The prompt(s) you devised? Ideas are cheap. But good software comes from good understanding of the problem. Good understanding comes from analyzing the issues in detail. Knowing the trade-offs between different solutions. All of which is not cheap. It is that expertise & experience which earns experts their paycheck. When you did that, then sure, go ahead & have coding agents implement using a structure you designed, algorithms you picked, reviewing the code and test results. But just vibe-code a whole project & kick it out the door? Result might work but I'd be more impressed by the coding agents' capabilities than your input. Article does give a nice hint about how the software landscape may change: "Many of these things were previously off-limits for lots of developers (..) So maybe the world will have more slop, but it might also have more developers in it, that want things to be fast and small."

librasteve 2mo ago

as a test of the proposition that human oriented software languages are redundant, I asked my favourite agent to rewrite some code in asm … and yes, it ran and it was fast conclusion… well, it’s scary but actually I think it’s a bit useless too … it’ll never catch on

llleeeoooh 2mo ago
I am confused. It succeeded at the task, why is the conclusion that it will never catch on ?

brainless 2mo ago

I do not know where things will go but here are some things I have been feeling: - We have tons of languages (and libraries/frameworks on top) because we, humans, have too many preferences - Many of these preferences are also abstractions because of how quickly (and with less knowledge of the underlying systems) we wanted to build things - LLMs can operate on most (any?) of these layers and the results we get depend on how much high level knowledge the operator has - LLMs + agents are able to do more and more of the digging, experimenting and ranking of different paths on their own to select good paths - As someone who is assisted by LLMs, I can focus on codifying my internal process into custom agent/harness while also building end-user software (build the shipyard while building ships) - I can reach out to any language (I am one of those who do not know Rust deeply but use it all the time) or any part of the stack now

yipinwong 2mo ago

What I got was, be more generalist and become a polymath. My thoughts below --- This means, we need to read more to produce more in many different fields, and domains. The idea is also captured in today's top 10 article, "To become a better writer, read as much as you can" (https://news.ycombinator.com/item?id=49405870 https://news.ycombinator.com/item?id=49405870) where if you want to produce good writings, read more. Reading more here means, familiarizing/learning/understanding many different fields/domains. I have never heard of "DWARF files, eBPF," and at least reading gave me an idea on what to learn about, so that when I work on projects, I can consider them by guiding AIs to even consider them. Until today, I'd never woulda have though to even consider "DWARF files, eBPF,". Now I can dig deeper into them and see what they are, and at least know what they used for and how they are used in practice.

hakesson 2mo ago

For the "harder tech" part: I played around with a "vibe code" project to see how far it gets. It's a cargo workspace linter that does things like find unused feature flags, unused pub, etc. Guiding it only on high-level feature-set requirements, it ended up doing workspace-wide lints backed by rustc's name resolution, not a parser. Something I would never have done myself. I picked that project because a missed lint costs nothing - I still wouldn't work this way on anything where a wrong answer hurts - yet.