6 ms·

Can we get a video of a workday conducted by these people? Unless there's a significant sense of what people are working on, and how LLMs are helping -- there'

Can we get a video of a workday conducted by these people? Unless there's a significant sense of what people are working on, and how LLMs are helping -- there's no point engaging -- there's no detail here. Sure, if your job is to turn out tweaks to a wordpress theme, presumably that's now 10x faster. If its to work on a new in-house electric motor in C for some machine, presumably that's almost entirely unaffected. No doubt junior web programmers working on a task backlog, specifically designed for being easy for juniors, are loving LLMs. I use LLMs all the time, but each non-trivial programming project that has to move out of draft-stage needs rewriting. In several cases, to such a degree that the LLM was a net impediment.

jsnell 1y ago
Not exactly what you're asking for, but https://news.ycombinator.com/item?id=44159166 https://news.ycombinator.com/item?id=44159166 from today is not a junior web programmer working through the backlog, and the commit history contains all the prompts.
- mjburgess 1y ago
  Sure, thanks. I mean it's a typescript OAuth library, so perhaps we might say mid-level web programmer developing a library from scratch with excellent pre-existing references, and with a known good reference API to hand. I'd also count that as a good use case for an LLM.
  - ramraj07 1y ago
    [flagged]
    - mjburgess 1y ago
      I think you mistook my comment. Insofar as its anything, it was a concession to that use case. I gave an example below: debugging a microservice-based request flow from a front-end, thru various middle layers and services, to a back-end, perhaps triggering other systems along the way. Something similar to what I worked on in 2012 for the UK olympics. Unless I'm mistaken, and happy to be, I'm not sure where the LLM is supposed to offer a significant productivity factor here. Overall, my point is -- indeed -- that we cannot really have good faith conversations in blog posts and comment sections. These are empirical questions which need substantial evidence from both sides -- ideally, videos of a workday. Its very hard to guess what anyone is really talking about at the level of abstraction that all this hot air is conducted at. As far as i can tell the people hyping LLMs the most are juniors, data scientists who do not do software engineering, and people working on greenfield/blank-page apps. These groups never address the demand from these sceptical senior software engineers -- for obvious reasons.
      - ramraj07 1y ago
        I recently had to do something similar and pasted new relic logs for a trace id and copy pasted the swagger pages for all the microservices involved, and in round two the code for the service it suspected, and Gemini helped me debug without even putting my full head into the problem.
    - jcranmer 1y ago
      Most of my day job is worrying about the correctness of compiler optimizations. LLMs frequently can't even accurately summarize the language manual (especially on the level of detail I need).
    - deleted 1y ago
      [deleted]
  - citizenpaul 1y ago
    I watched someone do a similar demonstration( https://news.ycombinator.com/item?id=44159166 https://news.ycombinator.com/item?id=44159166)live at an event. They ended up doing something like 3 pull requests to get the original change. Then had to do 4 more to get it to fix and put back things it removed. Not exactly efficient, and it was painful to sit there and be like I could have had it done manually 20x by now while we painfully waited for the AI to do the changes. I've never been able to get it to work reliably myself either. The internet just tells me to prompt harder. Lots of "grind-set" mentality energy around AI if you ask me. Very little substance.
mgraczyk 1y ago
I have done everything from architecture design for a DSP (Qualcomm), to training models that render photos on Pixel phones, to redoing Instagrams comments ranking system. I can't imaging doing anything without LLMs today, they would have made me much more productive at all of those things, whether it be Verilog, C++, python, ML, etc. I use them constantly now.
- mjburgess 1y ago
  I use LLMs frequently also. But my point is, with respect to the scepticism from some engineers -- that we need to know what people are working on. You list what look like quite greenfield projects, very self-contained, and very data science oriented. These are quite significantly uncharacteristic of software engineering in the large. They have nothing to do with interacting systems each with 100,000s lines of code. Software engineers working on large systems (eg., many micro-services, data integration layers, etc.) are working on very different problems. Debugging a microservice system isn't something an LLM can do -- it has no ability, e.g., to trace a request through various apis from, eg., a front-end into a backend layer, into some db, to be transfered to some other db etc. This was all common enough stuff for software engineers 20 years ago, and was part of some of my first jobs. A very large amount of this pollyanna-LLM view, which isnt by jnr software engineers, is by data scientists who are extremely unfamiliar with software engineering.
  - mgraczyk 1y ago
    Hmm how did you get that from what I listed? Every codebase I listed was over 10 years old and had millions of lines of code. Instagram is probably the world's largest and most used python codebase, and the camera software I worked on was 13 years old and had millions of lines of c++ and Java. I haven't worked on many self contained things in my career. LLMs can help with these things if you know how to use them.
    - mjburgess 1y ago
      OK, great. All I'm saying is until we really have videos (or equivalent empirical analysis) of these use cases, it's hard to assess these claims. Jobs comprise different tasks, some more amenable to LLMs than others. My view is that where scepticism exists amongst professional senior engineers, its probably well-founded and grounded in the kinds of tasks that they are engaged with. I'd imagine everyone in the debate is using LLMs to some degree; and that it's mostly about what productivity factor we imagine exists.
ryukoposting 1y ago
I write embedded firmware for wireless mesh networks and satcom. Blend of Rust and C. I spent ~4 months using Copilot last year for hobby projects, and it was a pretty disappointing experience. At its best, it was IntelliSense but slower. At its worst, it was trying to inject 30 lines of useless BS. I only realized there was an "agent" in VS Code because they hijacked my ctrl+i shortcut in a recent update. You can't point it at a private API without doing some GitHub org-level nonsense. As far as my job is concerned, it's a non-feature until you can point it your own API without jumping through hoops.
- ramraj07 1y ago
  You used one AI tool that was never more than autocomplete a year ago and you think you have a full hold of all that AI offers today? That's like reviewing thai food when you've only had Chinese food.
  - ryukoposting 1y ago
    >you think you have a full hold of all that AI offers today? I absolutely don't, and I'd love if you could highlight a spot where I suggested I was. As I said, the problem isn't that I don't want to try using an agent, the problem is that I can't because one incredibly basic feature is missing from VS Code's agent thing. I'll occasionally use chatbots, mostly for spitballing non-professional stuff. They seem to do well with ideation questions like "I'm making X, what are some approaches I could take to do Y?" In other words, I've found that they're good at bullshitting and making lists. I like R1-1776, but that's only because Perplexity Playground seems less restricted than some of the other chatbots. It's also nice for generating some boilerplate bash stuff, when I need that kind of thing. I don't need that very often, though.
  - frutiger 1y ago
    > That's like reviewing thai food when you've only had Chinese food. What's the implication here? That Thai food was invented 1 year after Chinese food?
manmal 1y ago
Here's a 3+h video of the PSPDFKit (Nutrient) founder vibe-coding a Mac app. Can be watched at 2x: https://steipete.me/posts/2025/the-future-of-vibe-coding?utm_source=news.ycombinator.com https://steipete.me/posts/2025/the-future-of-vibe-coding?utm...

jsnell 1y ago

Not exactly what you're asking for, but https://news.ycombinator.com/item?id=44159166 https://news.ycombinator.com/item?id=44159166 from today is not a junior web programmer working through the backlog, and the commit history contains all the prompts.

mjburgess 1y ago
Sure, thanks. I mean it's a typescript OAuth library, so perhaps we might say mid-level web programmer developing a library from scratch with excellent pre-existing references, and with a known good reference API to hand. I'd also count that as a good use case for an LLM.
- ramraj07 1y ago
  [flagged]
  - mjburgess 1y ago
    I think you mistook my comment. Insofar as its anything, it was a concession to that use case. I gave an example below: debugging a microservice-based request flow from a front-end, thru various middle layers and services, to a back-end, perhaps triggering other systems along the way. Something similar to what I worked on in 2012 for the UK olympics. Unless I'm mistaken, and happy to be, I'm not sure where the LLM is supposed to offer a significant productivity factor here. Overall, my point is -- indeed -- that we cannot really have good faith conversations in blog posts and comment sections. These are empirical questions which need substantial evidence from both sides -- ideally, videos of a workday. Its very hard to guess what anyone is really talking about at the level of abstraction that all this hot air is conducted at. As far as i can tell the people hyping LLMs the most are juniors, data scientists who do not do software engineering, and people working on greenfield/blank-page apps. These groups never address the demand from these sceptical senior software engineers -- for obvious reasons.
    - ramraj07 1y ago
      I recently had to do something similar and pasted new relic logs for a trace id and copy pasted the swagger pages for all the microservices involved, and in round two the code for the service it suspected, and Gemini helped me debug without even putting my full head into the problem.
  - jcranmer 1y ago
    Most of my day job is worrying about the correctness of compiler optimizations. LLMs frequently can't even accurately summarize the language manual (especially on the level of detail I need).
  - deleted 1y ago
    [deleted]
- citizenpaul 1y ago
  I watched someone do a similar demonstration( https://news.ycombinator.com/item?id=44159166 https://news.ycombinator.com/item?id=44159166)live at an event. They ended up doing something like 3 pull requests to get the original change. Then had to do 4 more to get it to fix and put back things it removed. Not exactly efficient, and it was painful to sit there and be like I could have had it done manually 20x by now while we painfully waited for the AI to do the changes. I've never been able to get it to work reliably myself either. The internet just tells me to prompt harder. Lots of "grind-set" mentality energy around AI if you ask me. Very little substance.

mgraczyk 1y ago

I have done everything from architecture design for a DSP (Qualcomm), to training models that render photos on Pixel phones, to redoing Instagrams comments ranking system. I can't imaging doing anything without LLMs today, they would have made me much more productive at all of those things, whether it be Verilog, C++, python, ML, etc. I use them constantly now.

mjburgess 1y ago
I use LLMs frequently also. But my point is, with respect to the scepticism from some engineers -- that we need to know what people are working on. You list what look like quite greenfield projects, very self-contained, and very data science oriented. These are quite significantly uncharacteristic of software engineering in the large. They have nothing to do with interacting systems each with 100,000s lines of code. Software engineers working on large systems (eg., many micro-services, data integration layers, etc.) are working on very different problems. Debugging a microservice system isn't something an LLM can do -- it has no ability, e.g., to trace a request through various apis from, eg., a front-end into a backend layer, into some db, to be transfered to some other db etc. This was all common enough stuff for software engineers 20 years ago, and was part of some of my first jobs. A very large amount of this pollyanna-LLM view, which isnt by jnr software engineers, is by data scientists who are extremely unfamiliar with software engineering.
- mgraczyk 1y ago
  Hmm how did you get that from what I listed? Every codebase I listed was over 10 years old and had millions of lines of code. Instagram is probably the world's largest and most used python codebase, and the camera software I worked on was 13 years old and had millions of lines of c++ and Java. I haven't worked on many self contained things in my career. LLMs can help with these things if you know how to use them.
  - mjburgess 1y ago
    OK, great. All I'm saying is until we really have videos (or equivalent empirical analysis) of these use cases, it's hard to assess these claims. Jobs comprise different tasks, some more amenable to LLMs than others. My view is that where scepticism exists amongst professional senior engineers, its probably well-founded and grounded in the kinds of tasks that they are engaged with. I'd imagine everyone in the debate is using LLMs to some degree; and that it's mostly about what productivity factor we imagine exists.

ryukoposting 1y ago

I write embedded firmware for wireless mesh networks and satcom. Blend of Rust and C. I spent ~4 months using Copilot last year for hobby projects, and it was a pretty disappointing experience. At its best, it was IntelliSense but slower. At its worst, it was trying to inject 30 lines of useless BS. I only realized there was an "agent" in VS Code because they hijacked my ctrl+i shortcut in a recent update. You can't point it at a private API without doing some GitHub org-level nonsense. As far as my job is concerned, it's a non-feature until you can point it your own API without jumping through hoops.

ramraj07 1y ago
You used one AI tool that was never more than autocomplete a year ago and you think you have a full hold of all that AI offers today? That's like reviewing thai food when you've only had Chinese food.
- ryukoposting 1y ago
  >you think you have a full hold of all that AI offers today? I absolutely don't, and I'd love if you could highlight a spot where I suggested I was. As I said, the problem isn't that I don't want to try using an agent, the problem is that I can't because one incredibly basic feature is missing from VS Code's agent thing. I'll occasionally use chatbots, mostly for spitballing non-professional stuff. They seem to do well with ideation questions like "I'm making X, what are some approaches I could take to do Y?" In other words, I've found that they're good at bullshitting and making lists. I like R1-1776, but that's only because Perplexity Playground seems less restricted than some of the other chatbots. It's also nice for generating some boilerplate bash stuff, when I need that kind of thing. I don't need that very often, though.
- frutiger 1y ago
  > That's like reviewing thai food when you've only had Chinese food. What's the implication here? That Thai food was invented 1 year after Chinese food?

manmal 1y ago

Here's a 3+h video of the PSPDFKit (Nutrient) founder vibe-coding a Mac app. Can be watched at 2x: https://steipete.me/posts/2025/the-future-of-vibe-coding?utm_source=news.ycombinator.com https://steipete.me/posts/2025/the-future-of-vibe-coding?utm...