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Betting on prompt engineering seems like betting on hybrids.

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  • Betting on prompt engineering seems like betting on hybrids. Which are selling very well right now. But if you think you have a decade of career left, ask yourself this question:

    What is the value of “prompt engineering,” when we get to the following inflection point:

    “Siri, make me a copy of Salesforce for my business, and after consulting legal precedent, make the most minimally invasive changes to insulate me from accusations of theft.”

    Actually, that’s just the warm-up:

    1/2

  • Betting on prompt engineering seems like betting on hybrids. Which are selling very well right now. But if you think you have a decade of career left, ask yourself this question:

    What is the value of “prompt engineering,” when we get to the following inflection point:

    “Siri, make me a copy of Salesforce for my business, and after consulting legal precedent, make the most minimally invasive changes to insulate me from accusations of theft.”

    Actually, that’s just the warm-up:

    1/2

    What is the value of software companies when we reach that point?

    Sure, anyone will be able to prompt planet-scale SaaS into existence. Open AI, Google, and especially MSFT will see to that, while xAI is cornering the market on digital mail-order brides.

    But anyone includes customers, no? If the arc of LLMs bends towards being reliable enough to prompt production SaaS into existence, there is a business model problem to solve as well as a whither-labour problem to solve.

    2/2

  • What is the value of software companies when we reach that point?

    Sure, anyone will be able to prompt planet-scale SaaS into existence. Open AI, Google, and especially MSFT will see to that, while xAI is cornering the market on digital mail-order brides.

    But anyone includes customers, no? If the arc of LLMs bends towards being reliable enough to prompt production SaaS into existence, there is a business model problem to solve as well as a whither-labour problem to solve.

    2/2

    @raganwald I would have been extremely skeptical about LLMs being able to be cajoled into making software at scale a year ago, but I am pretty astounded by how good the best agentic AIs have gotten and how much they can do on their own...they look stupid while iterating and making tons of mistakes, but I also look stupid when I'm iterating and making tons of mistakes. Closing the loop and allowing them to read the errors, search, and try again really does unleash something impressive.

  • @raganwald I would have been extremely skeptical about LLMs being able to be cajoled into making software at scale a year ago, but I am pretty astounded by how good the best agentic AIs have gotten and how much they can do on their own...they look stupid while iterating and making tons of mistakes, but I also look stupid when I'm iterating and making tons of mistakes. Closing the loop and allowing them to read the errors, search, and try again really does unleash something impressive.

    @swelljoe And even if they weren’t that impressive, this use case is remarkably compelling:

    What if the AI companies become the only software companies? Think of their ability to rent-seek when all automation runs through them!

    It’s worth juggling and tuning and adjusting heuristics and hiring tens of thousands of humans to help fine-tune the results.

  • @swelljoe And even if they weren’t that impressive, this use case is remarkably compelling:

    What if the AI companies become the only software companies? Think of their ability to rent-seek when all automation runs through them!

    It’s worth juggling and tuning and adjusting heuristics and hiring tens of thousands of humans to help fine-tune the results.

    @raganwald the AI arms race starts to make sense. Why wouldn't you spend a trillion dollars if you can replace every software company forever?


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