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As a person replying to your comment in the era of generative AI, I'm inclined to agree the hype is a bit much, even considering how impressive the technology c

As a person replying to your comment in the era of generative AI, I'm inclined to agree the hype is a bit much, even considering how impressive the technology can (sometimes) be. Another big area of hype is "prompt engineering." That one seems to have calmed down slightly, but for a while, there were large swaths of the Internet who were amazed that the set intersection of "talk like a decent human being" and "be precise in your communication" could generally lead to good results. In many ways, "AI" right now is magic marketing sprinkles that you can put on anything to make it more delicious. (Or, if you're inside a big company, it's magic prioritization sprinkles.)

bongodongobob 2y ago
Maybe the prompt engineering should have caught on more. I'm convinced that the large swaths of people commenting here and elsewhere "I don't get AI, it's just a parrot and it's always wrong and hallucinates, it's not useful" just don't understand that the prompt matters and the idea isn't to one shot everything. It writes good code for me every day, so I can only assume they're asking "Write me an OS from scratch" and then throwing their hands up when it obviously fails.
- lolinder 2y ago
  I think that calling it "prompt engineering" is what made it fail to catch on. We didn't call it "Google engineering" back in the day when you could actually craft a Google search to turn up useful results, we called it "Google-fu" [0]. "Google-fu" sounds like a fun skill to learn and acquire, where "prompt engineering" sounds either like something well out of reach or like pretentious nonsense depending on the audience. [0] https://blog.codinghorror.com/google-fu/ https://blog.codinghorror.com/google-fu/
  - fzzzy 2y ago
    Prompt-fu sounds cool
    - dvfjsdhgfv 2y ago
      Arguably you could charge more money from courses on prompt engineering than on prompt-fu.
  - fuzztester 2y ago
    >"Google-fu" sounds like a fun skill to learn and acquire, where "prompt engineering" sounds either like something well out of reach or like pretentious nonsense depending on the audience. More likely, "prompt engineering" is a marketing term made up by AI marketroids (cf. androids) hoping to make developers feel better about their reduced roles in this "grand new AI age".
  - chipdart 2y ago
    > I think that calling it "prompt engineering" is what made it fail to catch on. I don't think so. I mean, clearly calling it "engineering" threw some people off, in the same blend as some gatekeepers cringe at calling train drivers "railroad engineers". But that's puerile gatekeeping that misses the whole reason why there is a vast need to know how to "engineer prompts". The truth of the matter is that the focus of "prompt engineering" is being able to put together inputs that solve business problems in professional settings. You need to have full control over the generative process to integrate it's output in a business setting. That requires specialized knowledge way beyond naive requests expressed in natural language. Complaining about "prompt engineering" because that only focuses on specifying queries and operating a specific service makes as much sense as complaining about SQL/database/postgres engineering because that only focuses on specifying queries and operating a specific service. Before trying to dismiss "prompt engineering" through gatekeeping logic, first you need to justify why there is no need to know what you're doing to get outputs by feeding the right inputs. Even in subreddits dedicated to using generative AI to create images and videos,they started to outright ban posts where the contents are posted without the prompts used to create it.
- refulgentis 2y ago
  Been quietly wondering something similar to you for a year: I've ended up 95% confident that phenomena is due to people evaluating it in terms of "does it replace me?" Cosign prompt engineering. My startup is tl;dr "what if i made a on-every-platform app that can sync and let you choose whatever ai provider, and you pay at cost. and then give you a simple UI for piecing together steps like dialogue / ai chat / search / retrieve / use files" Seems to me the bigs are completely off the mark, lets cede the idea there's an omniscient AI available. Literally right now. Cool. It still has no idea how you work. you could see 42, in hitchhiker's guide the galaxy, as a deep parody of this category error
- skywhopper 2y ago
  To me it’s more like, if I have to carefully craft English language prompts in a conversational back-and-forth to get things done, then I am not really interested in doing that job, which sounds like being a manager or a teacher, and in practice just makes me feel totally dead, sad, and quite frankly bored. That’s just not an interesting or rewarding way to interact with a computer, and the last thing I want to do is add long wait times and nickel-and-dime cost to the process. Layer on using different LLMs for different tasks or trying them out against each other and cross-checking output and it’s a mind-numbingly indirect way to get anything accomplished that in the end teaches me nothing and develops no useful skill that I enjoy practicing. If it works for you, great, but even the most honest and genuine fans make it sound like a nightmare to me.
  - trog 2y ago
    Could not agree more. If the utility of this thing is based entirely on the right sequence of magic words why aren't we calling it "prompt wizardry" or something that better encapsulates the nature of it.
    - evilduck 2y ago
      If the utility of all computers is based on the right sequence of magic words why do we call them software engineers instead of something better like "code wizards" that encapsulates the nature of it?
      - trog 2y ago
        I guess the difference is code is (almost always) totally deterministic. Or at the very least, they're designed so that is a mostly safe assumption. It doesn't seem likely an LLM will ever do that. Maybe at a certain point of sophistication? But if the model is regularly changing - which they almost all will be, if they're expected to be up-to-date - there is a strong change they'll be different every time they're used. (I've been getting different behaviour in even relatively narrow ML-based systems for years. Google Assistant is my prime example - I regularly use the phrase "add to my calendar on the 20th of September at 5pm, go to the park". Almost all the time, it works perfectly. But a couple times a year at least, it won't process this as an action - it just does a Google web search for this string.)
- BlackFly 2y ago
  If it only solves the problems I already find trivial then it is a parrot. Nowadays we all have a calculator with us but if you emphasize that fact and choose to not practice and excel at basic arithmetic then you will be unable to perform higher mathematics that require it at every step. Of course if your problem is always already a solved problem then sure a parrot can be convinced to spit it out. So yes, the actual question for software engineering would be how to get AI to produce and iterate on an OS. The hallucinations aren't the only problem then, the lack of predictability in the answers is the biggest issue.
curiouscavalier 2y ago
I appreciate this perspective on prompt engineering. I’d love to think that one of the great outcomes of LLMs are people returning to more decent and precise forms of communicating. Imagine the progress if we could get that to transfer to human-human communication as well.
chipdart 2y ago
> Another big area of hype is "prompt engineering." That one seems to have calmed down slightly, but for a while, there were large swaths of the Internet who were amazed that the set intersection of "talk like a decent human being" and "be precise in your communication" could generally lead to good results. I think your comment conveys your obliviousness of the problem domain. The main driving need for prompt engineering is not an inability to "talk like a decent human being". That's just your personal need to insult and demean people who are interested in a problem domain you know nothing about. The main driving need for prompt engineering is aspects like not being able to control how context is formed and persisted in a particular model, and how to form the necessary and sufficient context to get a model to output anything interesting. Some applications require computationally expensive and time-consuming runs, and knowing what inputs to provide to a system which by it's very mature is open-ended is a critical skill to adequately use the system in professional settings. Let's put it like this: GitHub copilot is a LLM service which is extremely narrow in what are their applications and use cases. Yet, you can't even get it to add unit tests to a function following a specific style without putting the effort to build up the context it needs to output what you expect.

bongodongobob 2y ago

Maybe the prompt engineering should have caught on more. I'm convinced that the large swaths of people commenting here and elsewhere "I don't get AI, it's just a parrot and it's always wrong and hallucinates, it's not useful" just don't understand that the prompt matters and the idea isn't to one shot everything. It writes good code for me every day, so I can only assume they're asking "Write me an OS from scratch" and then throwing their hands up when it obviously fails.

lolinder 2y ago
I think that calling it "prompt engineering" is what made it fail to catch on. We didn't call it "Google engineering" back in the day when you could actually craft a Google search to turn up useful results, we called it "Google-fu" [0]. "Google-fu" sounds like a fun skill to learn and acquire, where "prompt engineering" sounds either like something well out of reach or like pretentious nonsense depending on the audience. [0] https://blog.codinghorror.com/google-fu/ https://blog.codinghorror.com/google-fu/
- fzzzy 2y ago
  Prompt-fu sounds cool
  - dvfjsdhgfv 2y ago
    Arguably you could charge more money from courses on prompt engineering than on prompt-fu.
- fuzztester 2y ago
  >"Google-fu" sounds like a fun skill to learn and acquire, where "prompt engineering" sounds either like something well out of reach or like pretentious nonsense depending on the audience. More likely, "prompt engineering" is a marketing term made up by AI marketroids (cf. androids) hoping to make developers feel better about their reduced roles in this "grand new AI age".
- chipdart 2y ago
  > I think that calling it "prompt engineering" is what made it fail to catch on. I don't think so. I mean, clearly calling it "engineering" threw some people off, in the same blend as some gatekeepers cringe at calling train drivers "railroad engineers". But that's puerile gatekeeping that misses the whole reason why there is a vast need to know how to "engineer prompts". The truth of the matter is that the focus of "prompt engineering" is being able to put together inputs that solve business problems in professional settings. You need to have full control over the generative process to integrate it's output in a business setting. That requires specialized knowledge way beyond naive requests expressed in natural language. Complaining about "prompt engineering" because that only focuses on specifying queries and operating a specific service makes as much sense as complaining about SQL/database/postgres engineering because that only focuses on specifying queries and operating a specific service. Before trying to dismiss "prompt engineering" through gatekeeping logic, first you need to justify why there is no need to know what you're doing to get outputs by feeding the right inputs. Even in subreddits dedicated to using generative AI to create images and videos,they started to outright ban posts where the contents are posted without the prompts used to create it.
refulgentis 2y ago
Been quietly wondering something similar to you for a year: I've ended up 95% confident that phenomena is due to people evaluating it in terms of "does it replace me?" Cosign prompt engineering. My startup is tl;dr "what if i made a on-every-platform app that can sync and let you choose whatever ai provider, and you pay at cost. and then give you a simple UI for piecing together steps like dialogue / ai chat / search / retrieve / use files" Seems to me the bigs are completely off the mark, lets cede the idea there's an omniscient AI available. Literally right now. Cool. It still has no idea how you work. you could see 42, in hitchhiker's guide the galaxy, as a deep parody of this category error
skywhopper 2y ago
To me it’s more like, if I have to carefully craft English language prompts in a conversational back-and-forth to get things done, then I am not really interested in doing that job, which sounds like being a manager or a teacher, and in practice just makes me feel totally dead, sad, and quite frankly bored. That’s just not an interesting or rewarding way to interact with a computer, and the last thing I want to do is add long wait times and nickel-and-dime cost to the process. Layer on using different LLMs for different tasks or trying them out against each other and cross-checking output and it’s a mind-numbingly indirect way to get anything accomplished that in the end teaches me nothing and develops no useful skill that I enjoy practicing. If it works for you, great, but even the most honest and genuine fans make it sound like a nightmare to me.
- trog 2y ago
  Could not agree more. If the utility of this thing is based entirely on the right sequence of magic words why aren't we calling it "prompt wizardry" or something that better encapsulates the nature of it.
  - evilduck 2y ago
    If the utility of all computers is based on the right sequence of magic words why do we call them software engineers instead of something better like "code wizards" that encapsulates the nature of it?
    - trog 2y ago
      I guess the difference is code is (almost always) totally deterministic. Or at the very least, they're designed so that is a mostly safe assumption. It doesn't seem likely an LLM will ever do that. Maybe at a certain point of sophistication? But if the model is regularly changing - which they almost all will be, if they're expected to be up-to-date - there is a strong change they'll be different every time they're used. (I've been getting different behaviour in even relatively narrow ML-based systems for years. Google Assistant is my prime example - I regularly use the phrase "add to my calendar on the 20th of September at 5pm, go to the park". Almost all the time, it works perfectly. But a couple times a year at least, it won't process this as an action - it just does a Google web search for this string.)
BlackFly 2y ago
If it only solves the problems I already find trivial then it is a parrot. Nowadays we all have a calculator with us but if you emphasize that fact and choose to not practice and excel at basic arithmetic then you will be unable to perform higher mathematics that require it at every step. Of course if your problem is always already a solved problem then sure a parrot can be convinced to spit it out. So yes, the actual question for software engineering would be how to get AI to produce and iterate on an OS. The hallucinations aren't the only problem then, the lack of predictability in the answers is the biggest issue.

curiouscavalier 2y ago

I appreciate this perspective on prompt engineering. I’d love to think that one of the great outcomes of LLMs are people returning to more decent and precise forms of communicating. Imagine the progress if we could get that to transfer to human-human communication as well.

chipdart 2y ago

> Another big area of hype is "prompt engineering." That one seems to have calmed down slightly, but for a while, there were large swaths of the Internet who were amazed that the set intersection of "talk like a decent human being" and "be precise in your communication" could generally lead to good results. I think your comment conveys your obliviousness of the problem domain. The main driving need for prompt engineering is not an inability to "talk like a decent human being". That's just your personal need to insult and demean people who are interested in a problem domain you know nothing about. The main driving need for prompt engineering is aspects like not being able to control how context is formed and persisted in a particular model, and how to form the necessary and sufficient context to get a model to output anything interesting. Some applications require computationally expensive and time-consuming runs, and knowing what inputs to provide to a system which by it's very mature is open-ended is a critical skill to adequately use the system in professional settings. Let's put it like this: GitHub copilot is a LLM service which is extremely narrow in what are their applications and use cases. Yet, you can't even get it to add unit tests to a function following a specific style without putting the effort to build up the context it needs to output what you expect.