6 ms·

I’m very bought in to the idea that raw coding is now a solved problem with the current models and agentic harnesses. Let alone what’s coming in the near term.

by dchuk 9mo ago

I’m very bought in to the idea that raw coding is now a solved problem with the current models and agentic harnesses. Let alone what’s coming in the near term. That being said, I think we’re in a weird phase right now where people’s obvious mental health issues are appearing as “hyper productivity” due to the use of these tools to absolutely spam out code that isn’t necessarily broadly coherent but is locally impressive. I’m watching multiple people both publicly and privately clearly breaking down mentally because of the “power” AI is bestowing on them. Their wires are completely crossed when it comes to the value of outputs vs outcomes and they’re espousing generated nonsense as it’s thoughtful insight. It’s an interesting thing to watch play out.

hahahahhaah 9mo ago
Yeah I am definitely trying to stay off hype and just use the damn tool
petesergeant 9mo ago
> where people’s obvious mental health issues I think the kids would call this "getting one-shotted by AI"
bkolobara 9mo ago
There is a lot of research on how words/language influences what we think, and even what we can observe, like the Sapir-Whorf hypothesis. If in a langauge there is one word for 2 different colors, speakers of it are unable to see the difference between the colors. I have a suspicion that extensive use of LLMs can result in damage to your brain. That's why we are seeing so many mental health issues surfacing up, and we are getting a bunch of blog posts about "an agentic coding psychosis". It could be that llms go from bicycles for the brain to smoking for the brain, once we figure out the long term effects of it.
- jstanley 9mo ago
  > If in a langauge there is one word for 2 different colors, speakers of it are unable to see the difference between the colors. Perhaps you mean to say that speakers are unable to name the difference between the colours? I can easily see differences between (for example) different shades of red. But I can't name them other than "shade of red". I do happen to subscribe to the Sapir-Whorf hypothesis, in the sense that I think the language you think in constrains your thoughts - but I don't think it is strong enough to prevent you from being able to see different colours.
  - bkolobara 9mo ago
    No, if you show them two colors and ask them if they are different, they will tell you no. EDIT: I have been searching for the source of where I saw this, but can't find it now :( EDIT2: I found a talk touching in the topic with a study: https://youtu.be/I64RtGofPW8?si=v1FNU06rb5mMYRKj&t=889 https://youtu.be/I64RtGofPW8?si=v1FNU06rb5mMYRKj&t=889
    - cthalupa 9mo ago
      The ability for us to look at a gradient of color and differentiate between shades even without distinct names for them seems to disprove this on its face. Unless the question is literally the equivalent of someone showing you a swatch of crimson and a swatch of scarlet and being asked if both are red, in which case, well yeah sure.
    - JumpCrisscross 9mo ago
      > if you show them two colors and ask them if they are different, they will tell you no The experiments I've seen seem to interrogate what the culture means by colour (versus shade, et cetera) more than what the person is seeing. If you show me sky blue and Navy blue and ask me if they're the same colour, I'll say yes. If you ask someone in a different context if Russian violet and Midnight blue are the same colour, I could see them saying yes, too. That doesn't mean they literally can't see the difference. Just that their ontology maps the words blue and violet to sets of colours differently.
      - wongarsu 9mo ago
        If you asked me if a fire engine and a ripe strawberry are the same color I would say yes. Obviously, they are both red. If you held them next to each other I would still be able to tell you they are obviously different shades of red. But in my head they are both mapped to the red "embedding". I imagine that's the exact same thing that happens to blue and green in cultures that don't have a word for green. If on the other hand you work with colors a lot you develop a finer mapping. If your first instinct when asked for the name of that wall over there is to say it's sage instead of green, then you would never say that a strawberry and a fire engine have the same color. You might even question the validity of the question, since fire engines have all kinds of different colors (neon red being a trend lately)
- BrenBarn 9mo ago
  > If in a langauge there is one word for 2 different colors, speakers of it are unable to see the difference between the colors. That is quite untrue. It is true that people may be slightly slower or less accurate in distinguishing colors that are within a labeled category than those that cross a category boundary, but that's far from saying they can't perceive the difference at all. The latter would imply that, for instance, English speakers cannot distinguish shades of blue or green.
  - bkolobara 9mo ago
    The point I was trying to make is that the way our brain works is deeply connected to language and words, including how fast and how accurate you perceive colors [0][1]. And interacting with an LLM could have unexpected side effects on it, because we were never before exposed to "statistically generated language" in such amounts. [0]: https://youtu.be/RKK7wGAYP6k?si=GK6VPP0yoFoGyOn3 https://youtu.be/RKK7wGAYP6k?si=GK6VPP0yoFoGyOn3 [1]: https://youtu.be/I64RtGofPW8?si=v1FNU06rb5mMYRKj&t=889 https://youtu.be/I64RtGofPW8?si=v1FNU06rb5mMYRKj&t=889
    - deleted 9mo ago
      [deleted]
- skywhopper 9mo ago
  But the color thing is self-evidently untrue. It’s not even hard to talk about. Unless you yourself are colorblind I think that would be obvious?
  - bonzini 9mo ago
    Sort of, at least some degree of relativism exists though how much is debated. Would you ever talk about sea having the same color as wine? But that's exactly what Homer called it. https://en.wikipedia.org/wiki/Wine-dark_sea https://en.wikipedia.org/wiki/Wine-dark_sea https://en.wikipedia.org/wiki/Linguistic_relativity_and_the_color_naming_debate https://en.wikipedia.org/wiki/Linguistic_relativity_and_the_...
    - cthalupa 9mo ago
      This is still quite clearly something different than being unable to see the different colors, though. Their mental model, sure. The way they convey it to others, sure. But you can easily distinguish between two colors side by side that are even closer in appearance than wine and the sea, even if you only know one name for them. We can differentiate between colors before we even know the words for them when we're young, too.
yetihehe 9mo ago
If you give every idiot a worldwide heard voice, you will hear every idiot from the whole world. If you give every idiot a tool to make programs, you will see a lot of programs made by idiots.
- meowface 9mo ago
  Steve Yegge is not an idiot or a bad programmer. Possibly just hypomanic at most. And a good, entertaining writer. https://en.wikipedia.org/wiki/Steve_Yegge https://en.wikipedia.org/wiki/Steve_Yegge Gas Town is ridiculous and I had to uninstall Beads after seeing it only confuse my agents, but he's not completely insane or a moron. There may be some kernels of good ideas inside of Gas Town which could be extracted out into a better system.
  - yetihehe 9mo ago
    > Steve Yegge is not an idiot or a bad programmer. I don't think he's an idiot, there are almost no actual idiots here on HN in my opinion and they don't write such articles or make systems like Steve Yegge. I'm only commenting about giving more tools to idiots. Even tools made by geniuses will give you idiotic results when used by actual idiots, but a lot of smart people want to lower barriers of entry so that idiots can use more tools. And there are a lot of idiots who were inactive just because they didn't have the tools. Famous quote from a famous Polish essayist/futurist Stanisław Lem: "I didn't know there are so many idiots in this world until I got internet".
  - fegd85 8mo ago
    Even if I looked past the overwrought, self-indulgent Mad Max LARP (and the poor judgment evidenced by the prioritization of world-building minutia while the basic architecture is imploding), the cost of finding those kernels in a monstrosity of this size negates any ROI. 189k lines in four weeks will inevitably surface interesting pattern combinations — that's not merit, that's sample size. You might as well search the Library of Babel; at least the patterns are guaranteed to exist there. The other problem with that reasoning is that whatever patterns ARE interesting are more likely to be new to AI-assisted coding generally – meaning a cleaner system built for the same use case will surface them without the archaeological dig, just by virtue of its builder having the skill to design it (and crucially, being more interested in designing it than in creating AI drawings of polecats in steampunk-adjacent garb). I'm also a bit curious about at which point you start considering someone an idiot when they keep making objectively idiotic moves – the whimsical Disneyfied presentation, the "please don't download this" false modesty while keeping the repo public, the inexplicable code growth all come from the same place. They're not separate quirks: they're the same inability to edit, the same need for immediate audience validation, the same substitution of volume and narrative for actual engineering discipline. Someone who thinks "Polecats" and "Guzzoline" are good names for production abstractions is not suddenly going to develop the editorial rigor to scrap a codebase and rebuild. Which is why it's worth remembering that Yegge's one successful shipped project was Grok, an internal tool used by Google engineers, so Yegge seems to have bought his own hype, missing how much of that project's success was likely subsidized by its user base comprising people skilled enough to route around its limitations. These days he seems to be building for developers in general, but critically might be missing that actual developers immediately clock the project's ineptitude + Yegge's immature, narcissistic prioritization and peace the fuck out. The end result of this is filtering for the self-described vibe-coder types, people already Dunning-Krugered enough to believe you can prompt your way into a complete system without knowing how to reason about that system in order to guide the AI. Which, fittingly, is how you end up with users who can't even follow "please don't download this yet".
GrowingSideways 9mo ago
> raw coding is now a solved problem Surely this was solved with fortran. What changed? I think most people just don't know what program they want.
- lordnacho 9mo ago
  You no longer have to be very specific about syntax. There's now an AI that can translate your idea into whatever language you want. Previously, if you had an idea of what the program needed to do, you needed to learn a new language. This is so hard that we use language itself as a metaphor: It's hard to learn a new language, only a few people can translate from French to English, for example. Likewise, few people can translate English to Fortran. Now, you can just think about your program in English, and so long as you actually know what you want, you can get a Fortran program. The issue is now what it was originally for senior programmers: to decide what to make, not how to make it.
  - hnlmorg 9mo ago
    The hard part of software development is equivalent to the hard part of engineering: Anyone can draw a sketch of what a house should look like. But designing a house that is safe, conforms to building regulations, and which wouldn't be uncomfortable to live in (for example, poor choice of heat insulation for the local climate) is the stuff people train on. Not the sketching part. It's the same for software development. All we've done is replace FORTRAN / Javascript / whatever with a subset of a natural language. But we still need to thoroughly understand the problem and describe it to the LLM. Plus the way we format these markdown prompts, you're basically still programming. Albeit in a less strict syntax and the "compiler" is non-deterministic. This is why I get so mythed by comments about AI replacing programmers. That's not what's happening. Programming is just shifting to a language that looks more like Jira tickets than source code. And the orgs that think they can replace developers with AI (and I don't for one second believe many of the technology leaders think this, but some smaller orgs likely do) are heading for a very unpleasant realisation soon. I will caveat this by saying: there are far too many naff developers out there that genuinely aren't any better than an LLM. And maybe what we need is more regulation around software development, just like there is in proper engineering professions.
ben_w 9mo ago
Mm. I'd agree, the code "isn’t necessarily broadly coherent but is locally impressive". However, I've seen some totally successful, even award-winning, human-written projects where I could say the same. Ages back, I heard a woodworking analogy: LLM code is like MDF. Really useful for cheap furniture, massively cheaper than solid wood, but it would be a mistake to use it as a structural element in a house. Now, I've never made anything more complex than furniture, so I don't know how well that fit the previous models let alone the current ones… but I've absolutely seen success coming out of bigger balls of mud than the balls of mud I got from letting Claude loose for a bit without oversight. Still, just because you can get success even with sloppy code, doesn't mean I think this is true everywhere. It's not like the award was for industrial equipment or anything, the closest I've come to life-critical code is helping to find and schedule video calls with GPs.
- theshrike79 9mo ago
  "Without oversight" is the key here. You need to define the problem space so that the agent knows what to do. Basically give it the tools to determine when it's "done" as defined by you.
deleted 9mo ago
[deleted]
sonnig 9mo ago
Well put. I can't help thinking of this every time I see the 854594th "agent coordination framework" in GitHub. They all look strangely similar, are obviously themselves vibe-coded, and make no real effort to present any type of evidence that they can help development in any way.
spmurrayzzz 9mo ago
This has also been an interesting social experiment in that we get to see what work people think is actually impressive vs trivial. Folks who have spent years effectively snapping together other people’s APIs like LEGOs (and being well-compensated for it) are understandably blown away by the current state of AI. Compare that to someone writing embedded firmware for device microcontrollers, who would understandably be underwhelmed by the same. The gap in reactions says more about the nature of the work than it does about the tools themselves.
- aaronblohowiak 9mo ago
  >Compare that to someone writing embedded firmware for device microcontrollers, who would understandably be underwhelmed by the same. One datum for you: I recently asked Claude to make a jerk-limited and jerk-derivative-limited motion planner and to use the existing trapezoidal planner as reference for fuzzy-testing various moves (to ensure total pulses sent was correct) and it totally worked. Only a few rounds of guidance to get it to where I wanted to commit it.
  - spmurrayzzz 9mo ago
    My comment above I hope wasn't read to mean "LLMs are only good at web dev." Only that there are different capability magnitudes. I often do experiments where I will clone one of our private repos, revert a commit, trash the .git path, and then see if any of the models/agents can re-apply the commit after N iterations. I record the pass@k score and compare between model generations over time. In one of those recent experiments, I saw gpt-oss-120b add API support to swap tx and rx IQ for digital spectral inversion at higher frequencies on our wireless devices. This is for a proprietary IC running a quantenna radio, the SDK of which is very likely not in-distribution. It was moderately impressive to me in part because just writing the IQ swap registers had a negative effect on performance, but the model found that swapping the order of the IQ imbalance coefficients fixed the performance degradation. I wouldn't say this was the same level of "impressive" as what the hype demands, but I remain an enthusiastic user of AI tooling due to somewhat regular moments like that. Especially when it involves open weight models of a low-to-moderate param count. My original point though is that those moments are far more common in web dev than they are elsewhere currently. EDIT: Forgot to add that the model also did some work that the original commit did not. It removed code paths that were clobbering the rx IQ swap register and instead changed it to explicitly initialize during baseband init so it would come up correct on boot.

by dchuk 9mo ago

hahahahhaah 9mo ago

Yeah I am definitely trying to stay off hype and just use the damn tool

petesergeant 9mo ago

> where people’s obvious mental health issues I think the kids would call this "getting one-shotted by AI"

bkolobara 9mo ago

There is a lot of research on how words/language influences what we think, and even what we can observe, like the Sapir-Whorf hypothesis. If in a langauge there is one word for 2 different colors, speakers of it are unable to see the difference between the colors. I have a suspicion that extensive use of LLMs can result in damage to your brain. That's why we are seeing so many mental health issues surfacing up, and we are getting a bunch of blog posts about "an agentic coding psychosis". It could be that llms go from bicycles for the brain to smoking for the brain, once we figure out the long term effects of it.

jstanley 9mo ago
> If in a langauge there is one word for 2 different colors, speakers of it are unable to see the difference between the colors. Perhaps you mean to say that speakers are unable to name the difference between the colours? I can easily see differences between (for example) different shades of red. But I can't name them other than "shade of red". I do happen to subscribe to the Sapir-Whorf hypothesis, in the sense that I think the language you think in constrains your thoughts - but I don't think it is strong enough to prevent you from being able to see different colours.
- bkolobara 9mo ago
  No, if you show them two colors and ask them if they are different, they will tell you no. EDIT: I have been searching for the source of where I saw this, but can't find it now :( EDIT2: I found a talk touching in the topic with a study: https://youtu.be/I64RtGofPW8?si=v1FNU06rb5mMYRKj&t=889 https://youtu.be/I64RtGofPW8?si=v1FNU06rb5mMYRKj&t=889
  - cthalupa 9mo ago
    The ability for us to look at a gradient of color and differentiate between shades even without distinct names for them seems to disprove this on its face. Unless the question is literally the equivalent of someone showing you a swatch of crimson and a swatch of scarlet and being asked if both are red, in which case, well yeah sure.
  - JumpCrisscross 9mo ago
    > if you show them two colors and ask them if they are different, they will tell you no The experiments I've seen seem to interrogate what the culture means by colour (versus shade, et cetera) more than what the person is seeing. If you show me sky blue and Navy blue and ask me if they're the same colour, I'll say yes. If you ask someone in a different context if Russian violet and Midnight blue are the same colour, I could see them saying yes, too. That doesn't mean they literally can't see the difference. Just that their ontology maps the words blue and violet to sets of colours differently.
    - wongarsu 9mo ago
      If you asked me if a fire engine and a ripe strawberry are the same color I would say yes. Obviously, they are both red. If you held them next to each other I would still be able to tell you they are obviously different shades of red. But in my head they are both mapped to the red "embedding". I imagine that's the exact same thing that happens to blue and green in cultures that don't have a word for green. If on the other hand you work with colors a lot you develop a finer mapping. If your first instinct when asked for the name of that wall over there is to say it's sage instead of green, then you would never say that a strawberry and a fire engine have the same color. You might even question the validity of the question, since fire engines have all kinds of different colors (neon red being a trend lately)
BrenBarn 9mo ago
> If in a langauge there is one word for 2 different colors, speakers of it are unable to see the difference between the colors. That is quite untrue. It is true that people may be slightly slower or less accurate in distinguishing colors that are within a labeled category than those that cross a category boundary, but that's far from saying they can't perceive the difference at all. The latter would imply that, for instance, English speakers cannot distinguish shades of blue or green.
- bkolobara 9mo ago
  The point I was trying to make is that the way our brain works is deeply connected to language and words, including how fast and how accurate you perceive colors [0][1]. And interacting with an LLM could have unexpected side effects on it, because we were never before exposed to "statistically generated language" in such amounts. [0]: https://youtu.be/RKK7wGAYP6k?si=GK6VPP0yoFoGyOn3 https://youtu.be/RKK7wGAYP6k?si=GK6VPP0yoFoGyOn3 [1]: https://youtu.be/I64RtGofPW8?si=v1FNU06rb5mMYRKj&t=889 https://youtu.be/I64RtGofPW8?si=v1FNU06rb5mMYRKj&t=889
  - deleted 9mo ago
    [deleted]
skywhopper 9mo ago
But the color thing is self-evidently untrue. It’s not even hard to talk about. Unless you yourself are colorblind I think that would be obvious?
- bonzini 9mo ago
  Sort of, at least some degree of relativism exists though how much is debated. Would you ever talk about sea having the same color as wine? But that's exactly what Homer called it. https://en.wikipedia.org/wiki/Wine-dark_sea https://en.wikipedia.org/wiki/Wine-dark_sea https://en.wikipedia.org/wiki/Linguistic_relativity_and_the_color_naming_debate https://en.wikipedia.org/wiki/Linguistic_relativity_and_the_...
  - cthalupa 9mo ago
    This is still quite clearly something different than being unable to see the different colors, though. Their mental model, sure. The way they convey it to others, sure. But you can easily distinguish between two colors side by side that are even closer in appearance than wine and the sea, even if you only know one name for them. We can differentiate between colors before we even know the words for them when we're young, too.

yetihehe 9mo ago

If you give every idiot a worldwide heard voice, you will hear every idiot from the whole world. If you give every idiot a tool to make programs, you will see a lot of programs made by idiots.

meowface 9mo ago
Steve Yegge is not an idiot or a bad programmer. Possibly just hypomanic at most. And a good, entertaining writer. https://en.wikipedia.org/wiki/Steve_Yegge https://en.wikipedia.org/wiki/Steve_Yegge Gas Town is ridiculous and I had to uninstall Beads after seeing it only confuse my agents, but he's not completely insane or a moron. There may be some kernels of good ideas inside of Gas Town which could be extracted out into a better system.
- yetihehe 9mo ago
  > Steve Yegge is not an idiot or a bad programmer. I don't think he's an idiot, there are almost no actual idiots here on HN in my opinion and they don't write such articles or make systems like Steve Yegge. I'm only commenting about giving more tools to idiots. Even tools made by geniuses will give you idiotic results when used by actual idiots, but a lot of smart people want to lower barriers of entry so that idiots can use more tools. And there are a lot of idiots who were inactive just because they didn't have the tools. Famous quote from a famous Polish essayist/futurist Stanisław Lem: "I didn't know there are so many idiots in this world until I got internet".
- fegd85 8mo ago
  Even if I looked past the overwrought, self-indulgent Mad Max LARP (and the poor judgment evidenced by the prioritization of world-building minutia while the basic architecture is imploding), the cost of finding those kernels in a monstrosity of this size negates any ROI. 189k lines in four weeks will inevitably surface interesting pattern combinations — that's not merit, that's sample size. You might as well search the Library of Babel; at least the patterns are guaranteed to exist there. The other problem with that reasoning is that whatever patterns ARE interesting are more likely to be new to AI-assisted coding generally – meaning a cleaner system built for the same use case will surface them without the archaeological dig, just by virtue of its builder having the skill to design it (and crucially, being more interested in designing it than in creating AI drawings of polecats in steampunk-adjacent garb). I'm also a bit curious about at which point you start considering someone an idiot when they keep making objectively idiotic moves – the whimsical Disneyfied presentation, the "please don't download this" false modesty while keeping the repo public, the inexplicable code growth all come from the same place. They're not separate quirks: they're the same inability to edit, the same need for immediate audience validation, the same substitution of volume and narrative for actual engineering discipline. Someone who thinks "Polecats" and "Guzzoline" are good names for production abstractions is not suddenly going to develop the editorial rigor to scrap a codebase and rebuild. Which is why it's worth remembering that Yegge's one successful shipped project was Grok, an internal tool used by Google engineers, so Yegge seems to have bought his own hype, missing how much of that project's success was likely subsidized by its user base comprising people skilled enough to route around its limitations. These days he seems to be building for developers in general, but critically might be missing that actual developers immediately clock the project's ineptitude + Yegge's immature, narcissistic prioritization and peace the fuck out. The end result of this is filtering for the self-described vibe-coder types, people already Dunning-Krugered enough to believe you can prompt your way into a complete system without knowing how to reason about that system in order to guide the AI. Which, fittingly, is how you end up with users who can't even follow "please don't download this yet".

GrowingSideways 9mo ago

> raw coding is now a solved problem Surely this was solved with fortran. What changed? I think most people just don't know what program they want.

lordnacho 9mo ago
You no longer have to be very specific about syntax. There's now an AI that can translate your idea into whatever language you want. Previously, if you had an idea of what the program needed to do, you needed to learn a new language. This is so hard that we use language itself as a metaphor: It's hard to learn a new language, only a few people can translate from French to English, for example. Likewise, few people can translate English to Fortran. Now, you can just think about your program in English, and so long as you actually know what you want, you can get a Fortran program. The issue is now what it was originally for senior programmers: to decide what to make, not how to make it.
- hnlmorg 9mo ago
  The hard part of software development is equivalent to the hard part of engineering: Anyone can draw a sketch of what a house should look like. But designing a house that is safe, conforms to building regulations, and which wouldn't be uncomfortable to live in (for example, poor choice of heat insulation for the local climate) is the stuff people train on. Not the sketching part. It's the same for software development. All we've done is replace FORTRAN / Javascript / whatever with a subset of a natural language. But we still need to thoroughly understand the problem and describe it to the LLM. Plus the way we format these markdown prompts, you're basically still programming. Albeit in a less strict syntax and the "compiler" is non-deterministic. This is why I get so mythed by comments about AI replacing programmers. That's not what's happening. Programming is just shifting to a language that looks more like Jira tickets than source code. And the orgs that think they can replace developers with AI (and I don't for one second believe many of the technology leaders think this, but some smaller orgs likely do) are heading for a very unpleasant realisation soon. I will caveat this by saying: there are far too many naff developers out there that genuinely aren't any better than an LLM. And maybe what we need is more regulation around software development, just like there is in proper engineering professions.

ben_w 9mo ago

Mm. I'd agree, the code "isn’t necessarily broadly coherent but is locally impressive". However, I've seen some totally successful, even award-winning, human-written projects where I could say the same. Ages back, I heard a woodworking analogy: LLM code is like MDF. Really useful for cheap furniture, massively cheaper than solid wood, but it would be a mistake to use it as a structural element in a house. Now, I've never made anything more complex than furniture, so I don't know how well that fit the previous models let alone the current ones… but I've absolutely seen success coming out of bigger balls of mud than the balls of mud I got from letting Claude loose for a bit without oversight. Still, just because you can get success even with sloppy code, doesn't mean I think this is true everywhere. It's not like the award was for industrial equipment or anything, the closest I've come to life-critical code is helping to find and schedule video calls with GPs.

theshrike79 9mo ago
"Without oversight" is the key here. You need to define the problem space so that the agent knows what to do. Basically give it the tools to determine when it's "done" as defined by you.

deleted 9mo ago

[deleted]

sonnig 9mo ago

Well put. I can't help thinking of this every time I see the 854594th "agent coordination framework" in GitHub. They all look strangely similar, are obviously themselves vibe-coded, and make no real effort to present any type of evidence that they can help development in any way.

spmurrayzzz 9mo ago

This has also been an interesting social experiment in that we get to see what work people think is actually impressive vs trivial. Folks who have spent years effectively snapping together other people’s APIs like LEGOs (and being well-compensated for it) are understandably blown away by the current state of AI. Compare that to someone writing embedded firmware for device microcontrollers, who would understandably be underwhelmed by the same. The gap in reactions says more about the nature of the work than it does about the tools themselves.

aaronblohowiak 9mo ago
>Compare that to someone writing embedded firmware for device microcontrollers, who would understandably be underwhelmed by the same. One datum for you: I recently asked Claude to make a jerk-limited and jerk-derivative-limited motion planner and to use the existing trapezoidal planner as reference for fuzzy-testing various moves (to ensure total pulses sent was correct) and it totally worked. Only a few rounds of guidance to get it to where I wanted to commit it.
- spmurrayzzz 9mo ago
  My comment above I hope wasn't read to mean "LLMs are only good at web dev." Only that there are different capability magnitudes. I often do experiments where I will clone one of our private repos, revert a commit, trash the .git path, and then see if any of the models/agents can re-apply the commit after N iterations. I record the pass@k score and compare between model generations over time. In one of those recent experiments, I saw gpt-oss-120b add API support to swap tx and rx IQ for digital spectral inversion at higher frequencies on our wireless devices. This is for a proprietary IC running a quantenna radio, the SDK of which is very likely not in-distribution. It was moderately impressive to me in part because just writing the IQ swap registers had a negative effect on performance, but the model found that swapping the order of the IQ imbalance coefficients fixed the performance degradation. I wouldn't say this was the same level of "impressive" as what the hype demands, but I remain an enthusiastic user of AI tooling due to somewhat regular moments like that. Especially when it involves open weight models of a low-to-moderate param count. My original point though is that those moments are far more common in web dev than they are elsewhere currently. EDIT: Forgot to add that the model also did some work that the original commit did not. It removed code paths that were clobbering the rx IQ swap register and instead changed it to explicitly initialize during baseband init so it would come up correct on boot.