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> Also, I've personally seen more interest in AI in devs that have little interest in technology, but a big interest in delivering. I found this too. But I als

> Also, I've personally seen more interest in AI in devs that have little interest in technology, but a big interest in delivering. I found this too. But I also found the opposite, including here on HN; people who are interested in technology have almost an aversion against using AI. I personally love tech and I would and do write software for fun, but even that is objectively more fun for me with AI. It makes me far more productive (very much more than what the article states) and, more importantly, it removes the procrastination; whenever I am stuck or procrastinating getting to work or start, I start talking with Aider and before I know it, another task was done that I probably wouldn't have done that day without. That way I now launch bi weekly open and closed source projects while before that would take months to years. And the cost of having this team of fast experienced devs sitting with me is max a few $ per day.

andybak 2y ago
Yeah. There is a psychological benefit to using AI that I find very beneficial. A lot of tasks that I would have avoided or wasted time doing task avoidance on suddenly become tractable. I think Simon Willison said something similar.
- jcgrillo 2y ago
  Are you just working on personal projects or in a shared codebase with tens or hundreds of other devs? If the latter, how do you keep your AI generated content from turning the whole thing into an incomprehensible superfund site of tech debt? I've gotten a lot of mileage in my career so far by paying attention when something felt tedious or mundane, because that's a signal you need some combination of refactoring, tooling, or automation. If instead you just lean on an LLM to brute-force your way through, sure, that accomplishes the short term goal of shipping your agile sprint deliverable or whatever, but what of the long term cost?
  - andybak 2y ago
    > Are you just working on personal projects or in a shared codebase with tens or hundreds of other devs? Like - I presume almost everyone - somewhere in the middle? That was a helluva dichotomy to offer me... > how do you keep your AI generated content from turning the whole thing into an incomprehensible superfund site of tech debt? By reading it, thinking about it and testing it? Did I somehow give the impression I'm cutting and pasting huge globs of code straight from ChatGPT into a git commit? There's a weird gulf of incomprehension between people that use AI to help them code and those that don't. I'm sure you're as confused by this exchange as I am.
    - jcgrillo 2y ago
      > That was a helluva dichotomy to offer me... I certainly didn't intend it that way, more like a continuum. O(1) --> O(10) --> O(100) --> ... > Did I somehow give the impression I'm cutting and pasting huge globs of code straight from ChatGPT into a git commit? Yes, a little. It seemed to me like you were advocating using the LLM to generate large amounts of tedious output.
      - andybak 2y ago
        I'm not sure where I said that but I certainly didn't intend to give that impression. I use AI either as an unblocker to get me started, or to write a handful of lines that are too complex to do from memory but not so complex that I can't immediately grok them. I find both types of usage very satisfying and helpful.
        jcgrillo 2y ago
        Interesting, thanks for clarifying.
      - anonzzzies 2y ago
        It does generate swats of code, however, you have to review and test it. But, depending on what you are working in/with, you would have to write this yourself anyway; for instance, Go has always so much plumbing, AI simply removes all those keystrokes. And very rigorously; it adds all the err and defer blocks in, which can be 100s and a large % of one go file: what is the point of writing that yourself? It does that very fast as well; if you write the main logic without any of that stuff and ask sonnet to make it 'good code', you write a few lines and get 100s back. But it is far more useful on verbose 'team written' corporate stuff than on the more reuse intensive tech: in CL or Haskell, the community is far more DRY than Go or JS/TS; you tend to create and reuse many things and your much of the end result is (basically) a DSL; current AI is not very good at that in my experience; it will recreate or hallucinate (when you pressure reuse of previously created things, if there are too many, even though it does fit in the context window) functions all over the place. But many people have the same issue; they don't know, cannot search or forget and will just redo things many times over; AI makes that far easier (as in, no work at all often), so that's the new reality.
  - Sakos 2y ago
    I'm not the same person but I share their perspective on this. I do it by treating AI written code the exact same way I treat mine. Extremely suspect and probably terrible on the first iteration, so I heavily test and iterate it until it's great code. If it's not up to my standards, I don't ever put it in a merge request, whether I handwrote it myself or had an AI write it for me.
trashtester 2y ago
> people who are interested in technology have almost an aversion against using AI I wonder if this is an age thing, for many people. I'm old enough to have started reading these discussions on Slashdot in the early 90s. But between 2000 and 2010, Slashdot changed and became much less open to new ideas. The same may be happening to HN right now. It feels like a lot of people are stuck in the tech of 10 years ago.
skydhash 2y ago
> people who are interested in technology have almost an aversion against using AI Personally, I don't use LLMs. But I don't mind people using them as interactive search engines or code/text manipulations as long as they're aware of the hallucination risks and took care of what they're copying into the project. My reasons for it is mostly that I'm a journey guy, not a destination guy. And I love reading books and manuals as they give me an extensive knowledge map. Using LLMs feels like taking guidance from someone who has not ventured 1km outside their village, but heard descriptions from passersby. Too much vigilance required for the occasional good stuff. And the truth is, there are a lot of great books and manuals out there. And while they teach you how to do stuff, they often teach you why you should not do it. I strongly doubt Copilot imparting architectural and technical reminders alongside the code.
- anonzzzies 2y ago
  > I'm a journey guy, not a destination guy For my never finishing side projects I am too; I enjoy my weekends tinkering on the 'final database' system I have been building in CL for over a decade and will probably never really 'finish'. But to make money, I launch things fast and promote them; AI makes that far easier. Especially for parts like fronted that I despise; I find 0 pleasure in working with css magic that even seasoned frontenders have to try/fail in a loop to create. I let Sonnet just struggle until it's good enough instead of me having to do that annoying chore; then I ask Aider to attach it to the backend and done.

andybak 2y ago

Yeah. There is a psychological benefit to using AI that I find very beneficial. A lot of tasks that I would have avoided or wasted time doing task avoidance on suddenly become tractable. I think Simon Willison said something similar.

jcgrillo 2y ago
Are you just working on personal projects or in a shared codebase with tens or hundreds of other devs? If the latter, how do you keep your AI generated content from turning the whole thing into an incomprehensible superfund site of tech debt? I've gotten a lot of mileage in my career so far by paying attention when something felt tedious or mundane, because that's a signal you need some combination of refactoring, tooling, or automation. If instead you just lean on an LLM to brute-force your way through, sure, that accomplishes the short term goal of shipping your agile sprint deliverable or whatever, but what of the long term cost?
- andybak 2y ago
  > Are you just working on personal projects or in a shared codebase with tens or hundreds of other devs? Like - I presume almost everyone - somewhere in the middle? That was a helluva dichotomy to offer me... > how do you keep your AI generated content from turning the whole thing into an incomprehensible superfund site of tech debt? By reading it, thinking about it and testing it? Did I somehow give the impression I'm cutting and pasting huge globs of code straight from ChatGPT into a git commit? There's a weird gulf of incomprehension between people that use AI to help them code and those that don't. I'm sure you're as confused by this exchange as I am.
  - jcgrillo 2y ago
    > That was a helluva dichotomy to offer me... I certainly didn't intend it that way, more like a continuum. O(1) --> O(10) --> O(100) --> ... > Did I somehow give the impression I'm cutting and pasting huge globs of code straight from ChatGPT into a git commit? Yes, a little. It seemed to me like you were advocating using the LLM to generate large amounts of tedious output.
    - andybak 2y ago
      I'm not sure where I said that but I certainly didn't intend to give that impression. I use AI either as an unblocker to get me started, or to write a handful of lines that are too complex to do from memory but not so complex that I can't immediately grok them. I find both types of usage very satisfying and helpful.
      - jcgrillo 2y ago
        Interesting, thanks for clarifying.
    - anonzzzies 2y ago
      It does generate swats of code, however, you have to review and test it. But, depending on what you are working in/with, you would have to write this yourself anyway; for instance, Go has always so much plumbing, AI simply removes all those keystrokes. And very rigorously; it adds all the err and defer blocks in, which can be 100s and a large % of one go file: what is the point of writing that yourself? It does that very fast as well; if you write the main logic without any of that stuff and ask sonnet to make it 'good code', you write a few lines and get 100s back. But it is far more useful on verbose 'team written' corporate stuff than on the more reuse intensive tech: in CL or Haskell, the community is far more DRY than Go or JS/TS; you tend to create and reuse many things and your much of the end result is (basically) a DSL; current AI is not very good at that in my experience; it will recreate or hallucinate (when you pressure reuse of previously created things, if there are too many, even though it does fit in the context window) functions all over the place. But many people have the same issue; they don't know, cannot search or forget and will just redo things many times over; AI makes that far easier (as in, no work at all often), so that's the new reality.
- Sakos 2y ago
  I'm not the same person but I share their perspective on this. I do it by treating AI written code the exact same way I treat mine. Extremely suspect and probably terrible on the first iteration, so I heavily test and iterate it until it's great code. If it's not up to my standards, I don't ever put it in a merge request, whether I handwrote it myself or had an AI write it for me.

trashtester 2y ago

> people who are interested in technology have almost an aversion against using AI I wonder if this is an age thing, for many people. I'm old enough to have started reading these discussions on Slashdot in the early 90s. But between 2000 and 2010, Slashdot changed and became much less open to new ideas. The same may be happening to HN right now. It feels like a lot of people are stuck in the tech of 10 years ago.

skydhash 2y ago

> people who are interested in technology have almost an aversion against using AI Personally, I don't use LLMs. But I don't mind people using them as interactive search engines or code/text manipulations as long as they're aware of the hallucination risks and took care of what they're copying into the project. My reasons for it is mostly that I'm a journey guy, not a destination guy. And I love reading books and manuals as they give me an extensive knowledge map. Using LLMs feels like taking guidance from someone who has not ventured 1km outside their village, but heard descriptions from passersby. Too much vigilance required for the occasional good stuff. And the truth is, there are a lot of great books and manuals out there. And while they teach you how to do stuff, they often teach you why you should not do it. I strongly doubt Copilot imparting architectural and technical reminders alongside the code.

anonzzzies 2y ago
> I'm a journey guy, not a destination guy For my never finishing side projects I am too; I enjoy my weekends tinkering on the 'final database' system I have been building in CL for over a decade and will probably never really 'finish'. But to make money, I launch things fast and promote them; AI makes that far easier. Especially for parts like fronted that I despise; I find 0 pleasure in working with css magic that even seasoned frontenders have to try/fail in a loop to create. I let Sonnet just struggle until it's good enough instead of me having to do that annoying chore; then I ask Aider to attach it to the backend and done.