5 ms·

> We're already seeing large software companies figure out that they don't need 5,000 developers. They probably only need 1,000 or maybe even fewer. Long-term,

> We're already seeing large software companies figure out that they don't need 5,000 developers. They probably only need 1,000 or maybe even fewer. Long-term, they will need none. I believe that software will be made obsolete by AI. Why use AI to build software for automating specific tasks, when you can just have the AI automate those tasks directly? Why have AI build a Microsoft Excel clone, when you can just wave your receipts at the AI and say "manage my expenses"? Enjoy your "AI-boosted productivity" while it lasts.

pixelatedindex 7mo ago
> Long-term, they will need none. I believe that software will be made obsolete by AI. I think this is a bit hyperbolic. Someone still needs to review and test the code, and if the code is for embedded systems I find it unlikely. For SaaS platforms you’ll see a dramatic reduction, maybe like 80% but it’ll still have a handful of devs. Factories didn’t completely eliminate assembly line workers, you just need a far fewer number to make sure the cogs turn the way it should.
- hackyhacky 7mo ago
  > Someone still needs to review and test the code, and if the code is for embedded systems I find it unlikely. I feel like you didn't understand my comment. I am predicting that there is no code to review. You simply ask the AI to do stuff and it does it. Today, for example, you can ask ChatGPT to play chess with you, and it will. You don't need a "chess program," all the rules are built in to the LLM. Same goes for SaaS. You don't need HR software; you just need an LLM that remembers who is working for the company. Like what a "secretary" used to be.
  - pixelatedindex 7mo ago
    > I feel like you didn't understand my comment. I am predicting that there is no code to review. You simply ask the AI to do stuff and it does it. I didn’t, and thanks for clarifying for me. This doesn’t pass the sniff test for me though - someone needs to train the models, which requires code. If AI can do everything for you, then what’s the differentiator as a business? Everything can be in chatGPT but that’s not the only business in existence. If something goes wrong, who is gonna debug it? Instead of API requests you would debug prompt requests maybe. We already hate talking to a robot for waiting on calls, automated support agents, etc. I don’t think a paying customer would accept that - they want a direct line to a person. I can buy the argument that the backend will be entirely AI and you won’t need to be managing instances of servers and databases but the front end will absolutely need to be coded. That will need some software engineering - we might get a role that is a weird blend of product + design + coding but that transformation is already happening. Honestly the biggest change I see is that the chat interface will be on equal footing with the browser. You might have some app that can connect to a bunch of chat interfaces that is good at something, and specializations are going to matter even more. It was a bit of a word vomit so thanks for coming to my TED Talk.
    - throwaway173738 7mo ago
      We hate talking to robots because they are largely useless when we have anything out of routine. We love talking to robots when we would ordinarily wait 30 minutes for a 3-minute conversation.
    - hackyhacky 7mo ago
      > I don’t think a paying customer would accept that - they want a direct line to a person. What the customer wants only matters insofar as they are willing to pay for it. Sure, I'd rather talk to a person... But I'm not willing to pay 100x as much for a service that's only marginally better. Same reason I don't fly first class, as miserable as coach is. Someone may want to pay for a boutique human lawyer/banker/coder/professor, maybe as a status symbol, the same way people pay $20k for an ugly handbag. But I think most people will take the cheaper and almost as good option, when the difference in quality is far overshadowed by the difference in price. > someone needs to train the models, which requires code. I'm not sure that training llms is a coding problem, but it doesn't much matter: llms can train each other. > If AI can do everything for you, then what’s the differentiator as a business? Good question. My gut says there isn't: all money flows to the model providers, everyone else is a serf at best parasiting on someone else's model.
      - pixelatedindex 7mo ago
        Good points. People might not pay 100x for something but it’s all about perceived value. Part of a successful business is to identify the perceived value, and find out your PMF while being different enough from the competition. It’ll be interesting to see how things play out, we are in such early days still.
  - aurareturn 7mo ago
    Because AI agents are tool users. Why does AI need to research 2026 tax code changes and then try to one-shot your taxes when it can just use Turbotax to do it for you? Turbotax has the latest 2026 tax changes coded into the app. I'd feel much more confident if AI uses Turbotax to do my taxes than to try to one-shot it.
    - hackyhacky 7mo ago
      > Turbotax has the latest 2026 tax changes coded into the app. How does TurboTax implement the latest tax changes? My guess is that before the decade is over, the answer is "an LLM does it."
      - aurareturn 7mo ago
        Yes but I’ll be glad to pay for human oversight at TurboTax. Anyways, formulas are a lot better than one shot.
  - Jaygles 7mo ago
    LLM technology will never achieve 100% accuracy in its output. There is an inherent non-determinism. Tasks that require 100% accuracy cannot be handled by LLMs alone. If an LLM is used to replace HR, it will inevitably do something wrong, and a human will need to be in the loop to correct it. Same goes for chess, there will always be a chance that it makes an illegal move. Same goes for code, there will always be a chance that it produces the wrong code. Maybe a new AI technology will be developed that doesn't have the innate non-determinism, but we don't have that now.
    - hackyhacky 7mo ago
      Relevant to your comment is this link from today's HN front page, about adapting LLMs to perform deterministic calculations. https://www.percepta.ai/blog/can-llms-be-computers https://www.percepta.ai/blog/can-llms-be-computers
  - bigtex88 7mo ago
    So even in your example you still need to have someone to ask the AI to play chess. So there will still be a need for someone somewhere to ask the AI to do something and supervise it or guide it in the right direction.
    - hackyhacky 7mo ago
      You've misunderstood my position. My argument is not that "AIs can operate independently and don't need supervision," but rather that "AIs are able or will soon be able to perform complex behaviors directly without having to create traditional software first." The chess example is illustrative because you can play chess with the AI without first asking the AI to implement chess-playing software. This means that software is obsolete, not people.
esseph 7mo ago
> Why use AI to build software for automating specific tasks, when you can just have the AI automate those tasks directly? Speed, cost, security, job/task management Next question
- hackyhacky 7mo ago
  > Speed, cost, security, job/task management All of that will inevitably be solved. 50 years ago, using a personal computer was an extravagant luxury. Until it wasn't. 30 years ago, carrying a powerful computer in your pocket was unthinkable. Until it wasn't. Right now, it's cheaper to run your accounting math on dedicated adder hardware. But Llms will only get cheaper. When you can run massive LLMs locally on your phone, it's hard to justify not using it for everything.
  - esseph 7mo ago
    Not until power access/generation is MUCH cheaper. Long, long, long way off. If I can run 50,000 fixed tasks that cost me $0.834/hr but OpenAI is costing $37/hr and the automation takes 40x as long and can make TERRIBLE errors why the fuck would I not move to the deterministic system? Also, battery life of mobile devices.
    - hackyhacky 7mo ago
      These exact arguments could have been made 50 years ago about why laptops are impossible. But now, we not only have laptops, we run horribly inefficient GUIs in horribly inefficient VMs on them. The dollar-per-compute trend goes ever downward.
      - esseph 7mo ago
        It will never ever be as cheap as as cron job and a shell script. There is a certain limit to how efficient using an LLM to do a job vs using an LLM to create a job is. There is a large distinction in compute and power resources between the two. Don't mistake one for the other.

pixelatedindex 7mo ago

> Long-term, they will need none. I believe that software will be made obsolete by AI. I think this is a bit hyperbolic. Someone still needs to review and test the code, and if the code is for embedded systems I find it unlikely. For SaaS platforms you’ll see a dramatic reduction, maybe like 80% but it’ll still have a handful of devs. Factories didn’t completely eliminate assembly line workers, you just need a far fewer number to make sure the cogs turn the way it should.

hackyhacky 7mo ago
> Someone still needs to review and test the code, and if the code is for embedded systems I find it unlikely. I feel like you didn't understand my comment. I am predicting that there is no code to review. You simply ask the AI to do stuff and it does it. Today, for example, you can ask ChatGPT to play chess with you, and it will. You don't need a "chess program," all the rules are built in to the LLM. Same goes for SaaS. You don't need HR software; you just need an LLM that remembers who is working for the company. Like what a "secretary" used to be.
- pixelatedindex 7mo ago
  > I feel like you didn't understand my comment. I am predicting that there is no code to review. You simply ask the AI to do stuff and it does it. I didn’t, and thanks for clarifying for me. This doesn’t pass the sniff test for me though - someone needs to train the models, which requires code. If AI can do everything for you, then what’s the differentiator as a business? Everything can be in chatGPT but that’s not the only business in existence. If something goes wrong, who is gonna debug it? Instead of API requests you would debug prompt requests maybe. We already hate talking to a robot for waiting on calls, automated support agents, etc. I don’t think a paying customer would accept that - they want a direct line to a person. I can buy the argument that the backend will be entirely AI and you won’t need to be managing instances of servers and databases but the front end will absolutely need to be coded. That will need some software engineering - we might get a role that is a weird blend of product + design + coding but that transformation is already happening. Honestly the biggest change I see is that the chat interface will be on equal footing with the browser. You might have some app that can connect to a bunch of chat interfaces that is good at something, and specializations are going to matter even more. It was a bit of a word vomit so thanks for coming to my TED Talk.
  - throwaway173738 7mo ago
    We hate talking to robots because they are largely useless when we have anything out of routine. We love talking to robots when we would ordinarily wait 30 minutes for a 3-minute conversation.
  - hackyhacky 7mo ago
    > I don’t think a paying customer would accept that - they want a direct line to a person. What the customer wants only matters insofar as they are willing to pay for it. Sure, I'd rather talk to a person... But I'm not willing to pay 100x as much for a service that's only marginally better. Same reason I don't fly first class, as miserable as coach is. Someone may want to pay for a boutique human lawyer/banker/coder/professor, maybe as a status symbol, the same way people pay $20k for an ugly handbag. But I think most people will take the cheaper and almost as good option, when the difference in quality is far overshadowed by the difference in price. > someone needs to train the models, which requires code. I'm not sure that training llms is a coding problem, but it doesn't much matter: llms can train each other. > If AI can do everything for you, then what’s the differentiator as a business? Good question. My gut says there isn't: all money flows to the model providers, everyone else is a serf at best parasiting on someone else's model.
    - pixelatedindex 7mo ago
      Good points. People might not pay 100x for something but it’s all about perceived value. Part of a successful business is to identify the perceived value, and find out your PMF while being different enough from the competition. It’ll be interesting to see how things play out, we are in such early days still.
- aurareturn 7mo ago
  Because AI agents are tool users. Why does AI need to research 2026 tax code changes and then try to one-shot your taxes when it can just use Turbotax to do it for you? Turbotax has the latest 2026 tax changes coded into the app. I'd feel much more confident if AI uses Turbotax to do my taxes than to try to one-shot it.
  - hackyhacky 7mo ago
    > Turbotax has the latest 2026 tax changes coded into the app. How does TurboTax implement the latest tax changes? My guess is that before the decade is over, the answer is "an LLM does it."
    - aurareturn 7mo ago
      Yes but I’ll be glad to pay for human oversight at TurboTax. Anyways, formulas are a lot better than one shot.
- Jaygles 7mo ago
  LLM technology will never achieve 100% accuracy in its output. There is an inherent non-determinism. Tasks that require 100% accuracy cannot be handled by LLMs alone. If an LLM is used to replace HR, it will inevitably do something wrong, and a human will need to be in the loop to correct it. Same goes for chess, there will always be a chance that it makes an illegal move. Same goes for code, there will always be a chance that it produces the wrong code. Maybe a new AI technology will be developed that doesn't have the innate non-determinism, but we don't have that now.
  - hackyhacky 7mo ago
    Relevant to your comment is this link from today's HN front page, about adapting LLMs to perform deterministic calculations. https://www.percepta.ai/blog/can-llms-be-computers https://www.percepta.ai/blog/can-llms-be-computers
- bigtex88 7mo ago
  So even in your example you still need to have someone to ask the AI to play chess. So there will still be a need for someone somewhere to ask the AI to do something and supervise it or guide it in the right direction.
  - hackyhacky 7mo ago
    You've misunderstood my position. My argument is not that "AIs can operate independently and don't need supervision," but rather that "AIs are able or will soon be able to perform complex behaviors directly without having to create traditional software first." The chess example is illustrative because you can play chess with the AI without first asking the AI to implement chess-playing software. This means that software is obsolete, not people.

esseph 7mo ago

> Why use AI to build software for automating specific tasks, when you can just have the AI automate those tasks directly? Speed, cost, security, job/task management Next question

hackyhacky 7mo ago
> Speed, cost, security, job/task management All of that will inevitably be solved. 50 years ago, using a personal computer was an extravagant luxury. Until it wasn't. 30 years ago, carrying a powerful computer in your pocket was unthinkable. Until it wasn't. Right now, it's cheaper to run your accounting math on dedicated adder hardware. But Llms will only get cheaper. When you can run massive LLMs locally on your phone, it's hard to justify not using it for everything.
- esseph 7mo ago
  Not until power access/generation is MUCH cheaper. Long, long, long way off. If I can run 50,000 fixed tasks that cost me $0.834/hr but OpenAI is costing $37/hr and the automation takes 40x as long and can make TERRIBLE errors why the fuck would I not move to the deterministic system? Also, battery life of mobile devices.
  - hackyhacky 7mo ago
    These exact arguments could have been made 50 years ago about why laptops are impossible. But now, we not only have laptops, we run horribly inefficient GUIs in horribly inefficient VMs on them. The dollar-per-compute trend goes ever downward.
    - esseph 7mo ago
      It will never ever be as cheap as as cron job and a shell script. There is a certain limit to how efficient using an LLM to do a job vs using an LLM to create a job is. There is a large distinction in compute and power resources between the two. Don't mistake one for the other.