5 ms·

Domain discovery is so underrated. LLMs remove so much friction that makes everything so incredibly accessible. If LLMs couldn't do anything else then that alo

Domain discovery is so underrated. LLMs remove so much friction that makes everything so incredibly accessible. If LLMs couldn't do anything else then that alone would still warrant an invention of a century sticker.

jhancock 1y ago
No doubt. The tedious stuff is just a time saver. The domain discovery is often the difference between making progress and giving up.
epiccoleman 1y ago
Couldn't agree more. The first time I used Claude Code was for something very much like this. We had a PDF rendering issue with Unicode characters in one of our libraries. We ultimately needed to implement a sort of bespoke font fallback system. With the help of the agent, I was able to iterate through several potential approaches and find the gaps and limitations within the space of an afternoon. By the time we got to the end of that process the LLM wrote up a nice doc of notes on the experiments, and *I* knew what I wanted to do next. Knowing that, I was able to give a more detailed and specific prompt to Claude which then scaffolded out a solution. I spent probably another day tweaking, testing, and cleaning up. Overall I think it's completely fair to say that Claude saved me a week of dev time on this particular task. The amount of reading and learning and iterating I'd have had to do to get the same result would have just taken 3-4 days of work. (not to mention the number of hours I might have wasted when I got stuck and scrolled HN for an hour or whatever). So it still needed my discernment and guidance - but there's no question that I moved through the process much quicker than I would have unassisted. That's worth the $8 in API credit ten times over and no amount of parroting the "stochastic parrot" phrase (see what I did there?) would change my mind.
- whatnow37373 1y ago
  Yes, that’s true and very cool but you’re an expert. Where do the next generation you’s come from? The ones that did not do weeks of dead-end research which built resilience, skill and the experience to tell Claude now saves them time? You cannot skip that admittedly tedious part of life for free. I think pro-AI people sometimes forget/ignore the second order effects on society. I worry about that.
  - lukan 1y ago
    On the other hand, I remember lots of stupid beginners questions I had, when learning to programm. My peers did not know them either and I had to wait sometimes days for the opportunity to ask someone advanced who knew. Blocking my progress. (Asking online was a possibility, but instead of helpful answers, insults for being newb was the standard response) With a LLM I would have had a likely correct answer immediately. And yes, yes what if it is wrong? Well, I was also taught plenty of wrong stuff from human teachers as well. I learned to think for myself. I doubt anyone decently smart who now grews up with those tools, think they are flawless. In the end, you are responsible for the product. If it works, if it passes the tests, you succeeded. That did not change.
    - GenshoTikamura 1y ago
      > My peers did not know them either and I had to wait sometimes days for the opportunity to ask someone advanced who knew. Blocking my progress. Hypothetically, a solution to a problem that preoccupied you for days would translate into a more stable and long-lasting neuron configration in your brain (i.e. be remembered) than a solution to a problem that preoccupied you only for the time taken to type the prompt in.
      - lukan 1y ago
        That is somewhat true, figuring things out on my own makes me really understand something. But I don't have the time and energy to figure everything out on my own and I stopped learning many things, where some useful hints in time likely would have kept the joy for me to master that topic. So it is probably about the right balance.
        dematz 1y ago
        There's definitely a balance. Someone told me years ago that when they'd look for one bug to try and fix it, they'd realize a bunch of other stuff about their code along the way. You learn a lot by struggling with a problem exactly when it feels unproductive. On the other hand, there are cases when maybe it's better to get an answer today than spend a week really learning something. For example if you don't care about how a library itself works, AI helps abstract the details away and maybe there really is no cost to that as long as you can see it works.
aloha2436 1y ago
> Domain discovery is so underrated. LLMs remove so much friction that makes everything so incredibly accessible. And, unfortunately, a lot of friction from not having access to information in the first place. I've read a bunch of docs from people talking to Glean in order to explore a new topic; if it's a topic I'm actually very familiar with then four out of five times it is somewhere from misleading to catastrophically wrong. Any internal terminology that doesn't match the common usage outside of our organization poisons the whole session and it will make up things to join the meanings together, and the prompter is none the wiser. I trust AI only as a gap filler in domains that I'm already an expert in or where there's little internal context, anything else is intellectual suicide.
- awongh 1y ago
  I feel like if you're using it in the right way, asking the AI to write code, or give domain context in a specific way then the answers it gives are easily verifiable enough- and it's domain knowledge you wouldn't have gotten very easily through a series of google searches- LLMs as a kind of search can work great.

jhancock 1y ago

No doubt. The tedious stuff is just a time saver. The domain discovery is often the difference between making progress and giving up.

epiccoleman 1y ago

Couldn't agree more. The first time I used Claude Code was for something very much like this. We had a PDF rendering issue with Unicode characters in one of our libraries. We ultimately needed to implement a sort of bespoke font fallback system. With the help of the agent, I was able to iterate through several potential approaches and find the gaps and limitations within the space of an afternoon. By the time we got to the end of that process the LLM wrote up a nice doc of notes on the experiments, and *I* knew what I wanted to do next. Knowing that, I was able to give a more detailed and specific prompt to Claude which then scaffolded out a solution. I spent probably another day tweaking, testing, and cleaning up. Overall I think it's completely fair to say that Claude saved me a week of dev time on this particular task. The amount of reading and learning and iterating I'd have had to do to get the same result would have just taken 3-4 days of work. (not to mention the number of hours I might have wasted when I got stuck and scrolled HN for an hour or whatever). So it still needed my discernment and guidance - but there's no question that I moved through the process much quicker than I would have unassisted. That's worth the $8 in API credit ten times over and no amount of parroting the "stochastic parrot" phrase (see what I did there?) would change my mind.

whatnow37373 1y ago
Yes, that’s true and very cool but you’re an expert. Where do the next generation you’s come from? The ones that did not do weeks of dead-end research which built resilience, skill and the experience to tell Claude now saves them time? You cannot skip that admittedly tedious part of life for free. I think pro-AI people sometimes forget/ignore the second order effects on society. I worry about that.
- lukan 1y ago
  On the other hand, I remember lots of stupid beginners questions I had, when learning to programm. My peers did not know them either and I had to wait sometimes days for the opportunity to ask someone advanced who knew. Blocking my progress. (Asking online was a possibility, but instead of helpful answers, insults for being newb was the standard response) With a LLM I would have had a likely correct answer immediately. And yes, yes what if it is wrong? Well, I was also taught plenty of wrong stuff from human teachers as well. I learned to think for myself. I doubt anyone decently smart who now grews up with those tools, think they are flawless. In the end, you are responsible for the product. If it works, if it passes the tests, you succeeded. That did not change.
  - GenshoTikamura 1y ago
    > My peers did not know them either and I had to wait sometimes days for the opportunity to ask someone advanced who knew. Blocking my progress. Hypothetically, a solution to a problem that preoccupied you for days would translate into a more stable and long-lasting neuron configration in your brain (i.e. be remembered) than a solution to a problem that preoccupied you only for the time taken to type the prompt in.
    - lukan 1y ago
      That is somewhat true, figuring things out on my own makes me really understand something. But I don't have the time and energy to figure everything out on my own and I stopped learning many things, where some useful hints in time likely would have kept the joy for me to master that topic. So it is probably about the right balance.
      - dematz 1y ago
        There's definitely a balance. Someone told me years ago that when they'd look for one bug to try and fix it, they'd realize a bunch of other stuff about their code along the way. You learn a lot by struggling with a problem exactly when it feels unproductive. On the other hand, there are cases when maybe it's better to get an answer today than spend a week really learning something. For example if you don't care about how a library itself works, AI helps abstract the details away and maybe there really is no cost to that as long as you can see it works.

aloha2436 1y ago

> Domain discovery is so underrated. LLMs remove so much friction that makes everything so incredibly accessible. And, unfortunately, a lot of friction from not having access to information in the first place. I've read a bunch of docs from people talking to Glean in order to explore a new topic; if it's a topic I'm actually very familiar with then four out of five times it is somewhere from misleading to catastrophically wrong. Any internal terminology that doesn't match the common usage outside of our organization poisons the whole session and it will make up things to join the meanings together, and the prompter is none the wiser. I trust AI only as a gap filler in domains that I'm already an expert in or where there's little internal context, anything else is intellectual suicide.

awongh 1y ago
I feel like if you're using it in the right way, asking the AI to write code, or give domain context in a specific way then the answers it gives are easily verifiable enough- and it's domain knowledge you wouldn't have gotten very easily through a series of google searches- LLMs as a kind of search can work great.