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Gambling addition implies dopamine hits from irregular and uncertain outcomes: as I note in the post, I don't get a dopamine hit from running agents. I know peo

Gambling addition implies dopamine hits from irregular and uncertain outcomes: as I note in the post, I don't get a dopamine hit from running agents. I know people say "LLMs are just gambling because they're next-token-maximizers that can't write real code" but with GPT 5.6 Sol (and a few new tricks I discovered) the outputs are much less irregular and uncertain. It's just typical engineering. "Not wanting to waste money" is the polar opposite of gambling.

dehrmann 3mo ago
> dopamine hits from irregular and uncertain outcomes Like the LLM getting the solution right?
- minimaxir 3mo ago
  For the problems I work on with GPT 5.6 Sol and the checks and balances I have in place, I estimate: - 80% of prompts get everything correct and are confirmed correct with manual validation - 19% of prompts make a minor mistake based on an ambiguity of the original prompt (user error not LLM error), but then reliably fixed in a followup prompt - 1% of prompts causes more problems than it solves and is more pragmatic to just revert For 99% good output, there isn't much of a dopamine rush when there is good output. The dopamine rushes are for the <1% odds. From the other replies on this post, I suspect no one believes me, but I am offering these numbers in good faith.
  - SyneRyder 3mo ago
    I think those of us who are using AI consistently believe you and understand. I'd say roughly the same thing about Claude in terms of numbers. I think many people who don't believe you just haven't built-up the kind of prompt history & MCP / CLI tooling etc that lets you get to the point where things work at that level of accuracy. Hope it helps to know that at least some of us here understand and are seeing the same thing. And if it's anything like my experience with Fable, "always be more ambitious". The capabilities of the models are often limited only by what you're brave enough to ask for. I keep finding I'm not ambitious enough.
dlenski 3mo ago
> Gambling addition implies dopamine hits from irregular and uncertain outcomes Your post literally describes your fascination with trying to figure out the pattern of a "random" reward that you get, and trying to maximize the value you get out of it. I put "random" in scare quotes because I strongly believe that—just as slot machine payouts are carefully structured to keep you playing—these LLM resets are structured to keep heavy users like you coming back to max out their usage, and to progressively upgrade it. Several other commenters have also stated this same suspicion about the pattern of resets you're describing. > "Not wanting to waste money" is the polar opposite of gambling. From everything I've read about gambling addiction, particularly Jay Caspian Kang, that seems wrong. The desire to "not waste money" and "get back to even" seems like a huge part of what motivates gamblers to keep gambling.
- drekipus 3mo ago
  >The desire to "not waste money" and "get back to even" seems like a huge part of what motivates gamblers to keep gambling. As someone who had family members go through gambling addiction this is the primary mechanism behind it. Addicts don't see it as "cool fun dopamine kicks" but instead find it the only way they can get back to normal/where they are supposed to be
  - therealpygon 3mo ago
    Don’t worry, they have a system, they can’t lose, and honestly, it’s like the outcome is almost guaranteed.
  - win311fwg 3mo ago
    That seems like an incomplete explanation. Logically, gambling is like going to the movies. You expect to pay x currency for y value of entertainment. If y falls short of expectations you might feel like you wasted your money, but who becomes addicted to going to the movies to try to get even? There is probably someone who has, but I’ve never heard of it and it doesn’t seem to be common; not like gambling addictions. For all intents and purposes it doesn’t happen. But gambling addictions do happen, fairly regularly. Perhaps it is loss aversion coupled with the aforementioned dopamine hit associated with gambling that makes it so prevalent?
somewhereoutth 3mo ago
> and a few new tricks I discovered This right here. Any gambler would recognize that statement.
- minimaxir 3mo ago
  Said tricks improve the output in an objective measurable manner, not theoretical, vibes, or gambler's fallacy. (blog post forthcoming on that) I've been researching LLM prompt optimization for longer than ChatGPT has existed; I was successfully optimizing the output of GPT-2 back in 2019.
  - chaps 3mo ago
    Respectfully, a lot of what you're saying in this thread sounds a lot like the lies that gamblers tell themselves. Saying this as someone with a strong tendency towards addictions. Some of these things are only possible to really see in hindsight. Yes, you've been working on these things for a while, but these systems are notably different in their capacity and strings they pull on us. Be well, please.
    - minimaxir 3mo ago
      Yesterday (unrelated to quotamaxxing described in the article), I made an Apple TV macOS menu bar remote app: https://cdn.bsky.app/img/feed_fullsize/plain/did:plc:oxaernim5mj2mmy3ytrvb42n/bafkreigrmpdnb6wqw3uxkzbb67nttepruithw5ylzpmsjjfckwui67nmgm https://cdn.bsky.app/img/feed_fullsize/plain/did:plc:oxaerni... Every single prompt worked without issue, and it got most of the way on the first try with the initial prompt (+ a couple visibility bugs due to the agent not having Computer Vision to see said menu bar app) such as: > Create a SwiftUI menu bar app named `swiftmote` using theto create the most user friendly app following Apple's HID guidelines for creating a remote that can operate a Apple TV on a local network. Instead of reimplementing the protocols needs to interface with an Apple TV, use the Python package `pyatv` and host it within the SwiftUI app as a sidecar along with a Python installation. I have my own Apple TV I can manually verify that it worked as expected, which is notable because the agent can't test or lie about this pipeline because it does not have access to the Apple TV. That is not hallucination or psychosis. If you want, I can release all the prompts I used. (EDIT: Sure, why not, here are the prompts. If I don't complain about something in a followup prompt, assume it worked correctly: https://gist.github.com/minimaxir/30fa820daa1392da13026ec6aa4f8597 https://gist.github.com/minimaxir/30fa820daa1392da13026ec6aa... )
epitrochoid413 3mo ago
Yes I agree with you here. LLMs tend to be a bit random, but are still more consistent and predictable than slot-machines. Also, gambling tends to exert lower effort and higher dopamine hits than vibe-coding, making it way more addictive. But LLMs are still addictive to some extent. Maybe its around the same level as other behavioral addictions like food, social media, or gaming addictions.

dehrmann 3mo ago

> dopamine hits from irregular and uncertain outcomes Like the LLM getting the solution right?

minimaxir 3mo ago
For the problems I work on with GPT 5.6 Sol and the checks and balances I have in place, I estimate: - 80% of prompts get everything correct and are confirmed correct with manual validation - 19% of prompts make a minor mistake based on an ambiguity of the original prompt (user error not LLM error), but then reliably fixed in a followup prompt - 1% of prompts causes more problems than it solves and is more pragmatic to just revert For 99% good output, there isn't much of a dopamine rush when there is good output. The dopamine rushes are for the <1% odds. From the other replies on this post, I suspect no one believes me, but I am offering these numbers in good faith.
- SyneRyder 3mo ago
  I think those of us who are using AI consistently believe you and understand. I'd say roughly the same thing about Claude in terms of numbers. I think many people who don't believe you just haven't built-up the kind of prompt history & MCP / CLI tooling etc that lets you get to the point where things work at that level of accuracy. Hope it helps to know that at least some of us here understand and are seeing the same thing. And if it's anything like my experience with Fable, "always be more ambitious". The capabilities of the models are often limited only by what you're brave enough to ask for. I keep finding I'm not ambitious enough.

dlenski 3mo ago

> Gambling addition implies dopamine hits from irregular and uncertain outcomes Your post literally describes your fascination with trying to figure out the pattern of a "random" reward that you get, and trying to maximize the value you get out of it. I put "random" in scare quotes because I strongly believe that—just as slot machine payouts are carefully structured to keep you playing—these LLM resets are structured to keep heavy users like you coming back to max out their usage, and to progressively upgrade it. Several other commenters have also stated this same suspicion about the pattern of resets you're describing. > "Not wanting to waste money" is the polar opposite of gambling. From everything I've read about gambling addiction, particularly Jay Caspian Kang, that seems wrong. The desire to "not waste money" and "get back to even" seems like a huge part of what motivates gamblers to keep gambling.

drekipus 3mo ago
>The desire to "not waste money" and "get back to even" seems like a huge part of what motivates gamblers to keep gambling. As someone who had family members go through gambling addiction this is the primary mechanism behind it. Addicts don't see it as "cool fun dopamine kicks" but instead find it the only way they can get back to normal/where they are supposed to be
- therealpygon 3mo ago
  Don’t worry, they have a system, they can’t lose, and honestly, it’s like the outcome is almost guaranteed.
- win311fwg 3mo ago
  That seems like an incomplete explanation. Logically, gambling is like going to the movies. You expect to pay x currency for y value of entertainment. If y falls short of expectations you might feel like you wasted your money, but who becomes addicted to going to the movies to try to get even? There is probably someone who has, but I’ve never heard of it and it doesn’t seem to be common; not like gambling addictions. For all intents and purposes it doesn’t happen. But gambling addictions do happen, fairly regularly. Perhaps it is loss aversion coupled with the aforementioned dopamine hit associated with gambling that makes it so prevalent?

somewhereoutth 3mo ago

> and a few new tricks I discovered This right here. Any gambler would recognize that statement.

minimaxir 3mo ago
Said tricks improve the output in an objective measurable manner, not theoretical, vibes, or gambler's fallacy. (blog post forthcoming on that) I've been researching LLM prompt optimization for longer than ChatGPT has existed; I was successfully optimizing the output of GPT-2 back in 2019.
- chaps 3mo ago
  Respectfully, a lot of what you're saying in this thread sounds a lot like the lies that gamblers tell themselves. Saying this as someone with a strong tendency towards addictions. Some of these things are only possible to really see in hindsight. Yes, you've been working on these things for a while, but these systems are notably different in their capacity and strings they pull on us. Be well, please.
  - minimaxir 3mo ago
    Yesterday (unrelated to quotamaxxing described in the article), I made an Apple TV macOS menu bar remote app: https://cdn.bsky.app/img/feed_fullsize/plain/did:plc:oxaernim5mj2mmy3ytrvb42n/bafkreigrmpdnb6wqw3uxkzbb67nttepruithw5ylzpmsjjfckwui67nmgm https://cdn.bsky.app/img/feed_fullsize/plain/did:plc:oxaerni... Every single prompt worked without issue, and it got most of the way on the first try with the initial prompt (+ a couple visibility bugs due to the agent not having Computer Vision to see said menu bar app) such as: > Create a SwiftUI menu bar app named `swiftmote` using theto create the most user friendly app following Apple's HID guidelines for creating a remote that can operate a Apple TV on a local network. Instead of reimplementing the protocols needs to interface with an Apple TV, use the Python package `pyatv` and host it within the SwiftUI app as a sidecar along with a Python installation. I have my own Apple TV I can manually verify that it worked as expected, which is notable because the agent can't test or lie about this pipeline because it does not have access to the Apple TV. That is not hallucination or psychosis. If you want, I can release all the prompts I used. (EDIT: Sure, why not, here are the prompts. If I don't complain about something in a followup prompt, assume it worked correctly: https://gist.github.com/minimaxir/30fa820daa1392da13026ec6aa4f8597 https://gist.github.com/minimaxir/30fa820daa1392da13026ec6aa... )

epitrochoid413 3mo ago

Yes I agree with you here. LLMs tend to be a bit random, but are still more consistent and predictable than slot-machines. Also, gambling tends to exert lower effort and higher dopamine hits than vibe-coding, making it way more addictive. But LLMs are still addictive to some extent. Maybe its around the same level as other behavioral addictions like food, social media, or gaming addictions.