3 ms·

What business process do you want to hook to?

bnchrch 2y ago
What dont you? 1. Report generation 2. Knowledge search 3. Email / Message drafting and auto response 4. Support 5. Small bug fixes 6. Minor design changes 7. Wireframe first drafts 8. Research assistant 9. Executive assistant 10. Outreach 11. User interviews 12. Personalized ads 13. Voice to code I mean these arent even the theoretical stuff. These (and more) are all happening right now.
- Gerardo1 2y ago
  1. yes, with reservations 2. yes! but I'd like specific things that a lot of models don't do well quite yet, like accurate, complete citing and contextualizing with quotes across sources, etc. 3. Eh, pretty unexcited but I can see some limited utility. 4. 100% no. 5. Skeptical but there's definitely some good use cases here: smaller bug fixes and linting/vuln/anit-pattern scanning could be good applications, but I'm not sure if its better than the existing non-ai tools. 6. Maybe? If you mean code, existing refactor tools are pretty darn good and are deterministic, they do the thing or they don't. If the tool can't make strong guarantees about that, I'm not interested. 7. Yeah I think that's pretty good. Related: I think there's an application for detecting consistency issues between products/pages/etc that should have a unified design and UX. 8. That's basically #2? 9. I think execs will dump the tool the first time it makes the wrong decision, and I think people the tool reaches out to on behalf of the exec won't take those communications as seriously. 10. No. That's spam, full-stop. 11. No. User's aren't going to take it seriously and aren't going to respond in the same way. Will also be a reputational risk. "Would you mind taking a survey about your experience with our product?" followed by a chat conversation with an AI is going to be dragged online. 12. Absolutely no one wants this. 13. You mean as an accessibility feature? Because I could definitely see that. I'll bring up that the original question was what ways would you want AI integrated into products. Not "what ways are people integrating AI in a desperate chance to hop on the boat" (to borrow the metaphor from the article).
  - ponector 2y ago
    >> 12. Absolutely no one wants this. And yet, absolutely everyone will get this.
    - Gerardo1 2y ago
      I agree, but I think there's good reason to be skeptical of the effectiveness of current targeted online ads (in terms of actually getting people to buy products and services that are advertised), and I don't see how AI could make that better. That being said, so far the people who buy online ads don't seem to actually care if they're effective or a worthwhile investment, so that may not actually matter.
  - rsynnott 2y ago
    > but I'd like specific things that a lot of models don't do well quite yet, like accurate, complete citing and contextualizing with quotes across sources, etc. Er, yeah, good luck with that. You're not going to get than from an LLM.
    - Gerardo1 2y ago
      Some of them do citation okay-ish (which isn't sufficient, but suggests some ability). But I more or less agree with your skepticism. If you looked over my comments on HN, you'd probably think I was a die-hard AI skeptic, but I'm really not, I just think the vast majority of people's understanding of and expectations of AI are disconnected from reality. I think people are viewing AI (and products, tools, innovations built with/around AI) as they hope it will be in 5 years, and not as it is right now.
- coldtea 2y ago
  1. Generate reports nobody will read, or will feed to another LLM to pretend they read. 2. Sorta, with people taking both the accurate parts and the hallucinations as truth 3. See 1 4. Yet another regression from talking to actual humans for support 5. And small bug introductions 6. Code design (ie architecture)? Hopefully not 7. For things their creator never really loved and nobody wants 8. See 2 10. God, please no! 11. See 10 12. See 10 and 11 13. Alright
  - ponector 2y ago
    >>God, please no! This is the part which will be implemented for sure as soon as possible and exploited as much as possible.
  - bnchrch 2y ago
    This is the thing. Many of these Ive tried successfully. You need human oversight but as of today Ive been able to consistently: 1. Debug k8s and implement niche fixes 2. Write code faster 3. Fill out a slack update template from just talking to an LLM 4. Made a system for my partner to generate the first draft of her standardized report (required for assessment) 5. Draft email responses to clients, customers, strata council, lawyers. 6. Turn docs into mermaid diagrams 7. POC new features 8. Write api integration code from a docs url The obvious caveat is you do need to still act as QA and know what your doing. But the general improvements, productivity gains, and new possibilities are all real. I think your (hard earned) engineer cynicism is now getting in your way.
- deadbabe 2y ago
  None of that is really contributing to revenue, and AI isn’t cheap to run. How is any of that worth it?
  - bnchrch 2y ago
    AI for the majority of these tasks is pretty damn cheap to run
talles 2y ago
None. But companies are doing regardless of what we think. If it works, it works. Verification of customer documents, monitoring and interpreting regulatory changes, matching resumes to open positions, support ticket triage, better automated customer support, ...
- cratermoon 2y ago
  > If it works, it works. For very small values of "works".
- rsynnott 2y ago
  > If it works, it works. This is the critical bit, though. > Verification of customer documents There are quite serious consequences for getting this wrong, especially systematically (making a few mistakes, you may get away with, but you don't want to be the bank of choice for the North Korean secret service, say), so, if it turns out not to work well, "but the magic robot said so" will not be seen as an excuse, and there will be fines and maybe prison sentences. > monitoring and interpreting regulatory changes As above. "We're too cheap to ask a lawyer so we had a magic robot tell us if it was okay" _absolutely_ will not fly. > matching resumes to open positions "Half of the people we've hired for the last two years are totally useless, how are we screening these resumes again?" The customer support stuff is the only thing you've listed where a certain amount of failure is tolerable for many businesses (most customer support is already quite bad and often already uses questionable automation; if you have _good_ customer support you should be more cautious, but most companies don't). But using current LLMs for the important stuff? Nah, that's not going to go well.
  - talles 2y ago
    I think you're misreading the situation by treating it as 'all or nothing'. If I'm not mistaken, it's common for a legal team to analyze documents in an hierarchical fashion. A less senior person reads and highlights part of a document, and later a more senior one carefully analyze those points. The 'easy' part of the job that is the target for automation. As for the verification of customer documents, oh boy, I've seem some stuff first hand and I can tell you that they are definitely not that careful.

What dont you? 1. Report generation 2. Knowledge search 3. Email / Message drafting and auto response 4. Support 5. Small bug fixes 6. Minor design changes 7. Wireframe first drafts 8. Research assistant 9. Executive assistant 10. Outreach 11. User interviews 12. Personalized ads 13. Voice to code I mean these arent even the theoretical stuff. These (and more) are all happening right now.

Gerardo1 2y ago
1. yes, with reservations 2. yes! but I'd like specific things that a lot of models don't do well quite yet, like accurate, complete citing and contextualizing with quotes across sources, etc. 3. Eh, pretty unexcited but I can see some limited utility. 4. 100% no. 5. Skeptical but there's definitely some good use cases here: smaller bug fixes and linting/vuln/anit-pattern scanning could be good applications, but I'm not sure if its better than the existing non-ai tools. 6. Maybe? If you mean code, existing refactor tools are pretty darn good and are deterministic, they do the thing or they don't. If the tool can't make strong guarantees about that, I'm not interested. 7. Yeah I think that's pretty good. Related: I think there's an application for detecting consistency issues between products/pages/etc that should have a unified design and UX. 8. That's basically #2? 9. I think execs will dump the tool the first time it makes the wrong decision, and I think people the tool reaches out to on behalf of the exec won't take those communications as seriously. 10. No. That's spam, full-stop. 11. No. User's aren't going to take it seriously and aren't going to respond in the same way. Will also be a reputational risk. "Would you mind taking a survey about your experience with our product?" followed by a chat conversation with an AI is going to be dragged online. 12. Absolutely no one wants this. 13. You mean as an accessibility feature? Because I could definitely see that. I'll bring up that the original question was what ways would you want AI integrated into products. Not "what ways are people integrating AI in a desperate chance to hop on the boat" (to borrow the metaphor from the article).
- ponector 2y ago
  >> 12. Absolutely no one wants this. And yet, absolutely everyone will get this.
  - Gerardo1 2y ago
    I agree, but I think there's good reason to be skeptical of the effectiveness of current targeted online ads (in terms of actually getting people to buy products and services that are advertised), and I don't see how AI could make that better. That being said, so far the people who buy online ads don't seem to actually care if they're effective or a worthwhile investment, so that may not actually matter.
- rsynnott 2y ago
  > but I'd like specific things that a lot of models don't do well quite yet, like accurate, complete citing and contextualizing with quotes across sources, etc. Er, yeah, good luck with that. You're not going to get than from an LLM.
  - Gerardo1 2y ago
    Some of them do citation okay-ish (which isn't sufficient, but suggests some ability). But I more or less agree with your skepticism. If you looked over my comments on HN, you'd probably think I was a die-hard AI skeptic, but I'm really not, I just think the vast majority of people's understanding of and expectations of AI are disconnected from reality. I think people are viewing AI (and products, tools, innovations built with/around AI) as they hope it will be in 5 years, and not as it is right now.
coldtea 2y ago
1. Generate reports nobody will read, or will feed to another LLM to pretend they read. 2. Sorta, with people taking both the accurate parts and the hallucinations as truth 3. See 1 4. Yet another regression from talking to actual humans for support 5. And small bug introductions 6. Code design (ie architecture)? Hopefully not 7. For things their creator never really loved and nobody wants 8. See 2 10. God, please no! 11. See 10 12. See 10 and 11 13. Alright
- ponector 2y ago
  >>God, please no! This is the part which will be implemented for sure as soon as possible and exploited as much as possible.
- bnchrch 2y ago
  This is the thing. Many of these Ive tried successfully. You need human oversight but as of today Ive been able to consistently: 1. Debug k8s and implement niche fixes 2. Write code faster 3. Fill out a slack update template from just talking to an LLM 4. Made a system for my partner to generate the first draft of her standardized report (required for assessment) 5. Draft email responses to clients, customers, strata council, lawyers. 6. Turn docs into mermaid diagrams 7. POC new features 8. Write api integration code from a docs url The obvious caveat is you do need to still act as QA and know what your doing. But the general improvements, productivity gains, and new possibilities are all real. I think your (hard earned) engineer cynicism is now getting in your way.
deadbabe 2y ago
None of that is really contributing to revenue, and AI isn’t cheap to run. How is any of that worth it?
- bnchrch 2y ago
  AI for the majority of these tasks is pretty damn cheap to run

talles 2y ago

None. But companies are doing regardless of what we think. If it works, it works. Verification of customer documents, monitoring and interpreting regulatory changes, matching resumes to open positions, support ticket triage, better automated customer support, ...

cratermoon 2y ago
> If it works, it works. For very small values of "works".
rsynnott 2y ago
> If it works, it works. This is the critical bit, though. > Verification of customer documents There are quite serious consequences for getting this wrong, especially systematically (making a few mistakes, you may get away with, but you don't want to be the bank of choice for the North Korean secret service, say), so, if it turns out not to work well, "but the magic robot said so" will not be seen as an excuse, and there will be fines and maybe prison sentences. > monitoring and interpreting regulatory changes As above. "We're too cheap to ask a lawyer so we had a magic robot tell us if it was okay" _absolutely_ will not fly. > matching resumes to open positions "Half of the people we've hired for the last two years are totally useless, how are we screening these resumes again?" The customer support stuff is the only thing you've listed where a certain amount of failure is tolerable for many businesses (most customer support is already quite bad and often already uses questionable automation; if you have _good_ customer support you should be more cautious, but most companies don't). But using current LLMs for the important stuff? Nah, that's not going to go well.
- talles 2y ago
  I think you're misreading the situation by treating it as 'all or nothing'. If I'm not mistaken, it's common for a legal team to analyze documents in an hierarchical fashion. A less senior person reads and highlights part of a document, and later a more senior one carefully analyze those points. The 'easy' part of the job that is the target for automation. As for the verification of customer documents, oh boy, I've seem some stuff first hand and I can tell you that they are definitely not that careful.