6 ms·

I'd be ok with paying more if results were good, but it seems like Anthropic is going for the Tinder/casino intermittent reinforcement strategy: optimized to ke

by glerk 6mo ago

I'd be ok with paying more if results were good, but it seems like Anthropic is going for the Tinder/casino intermittent reinforcement strategy: optimized to keep you spending tokens instead of achieving results. And yes, Claude models are generally more fun to use than GPT/Codex. They have a personality. They have an intuition for design/aesthetics. Vibe-coding with them feels like playing a video game. But the result is almost always some version of cutting corners: tests removed to make the suite pass, duplicate code everywhere, wrong abstraction, type safety disabled, hard requirements ignored, etc. These issues are not resolved in 4.7, no matter what the benchmarks say, and I don't think there is any interest in resolving them.

xpe 6mo ago
> ... but it seems like Anthropic is going for the Tinder/casino intermittent reinforcement strategy: optimized to keep you spending tokens instead of achieving results. This part of the above comment strikes me as uncharitable and overconfident. And, to be blunt, presumptuous. To claim to know a company's strategy as an outsider is messy stuff. My prior: it is 10X to 20X more likely Anthropic has done something other than shift to a short-term squeeze their customers strategy (which I think is only around ~5%) What do I mean by "something other"? (1) One possibility is they are having capacity and/or infrastructure problems so the model performance is degraded. (2) Another possibility is that they are not as tuned to to what customers want relative to what their engineers want. (3) It is also possible they have slowed down their models down due to safety concerns. To be more specific, they are erring on the side of caution (which would be consistent with their press releases about safety concerns of Mythos). Also, the above three possibilities are not mutually exclusive. I don't expect us (readers here) to agree on the probabilities down to the ±5% level, but I would think a large chunk of informed and reasonable people can probably converge to something close to ±20%. At the very least, can we agree all of these factors are strong contenders: each covers maybe at least 10% to 30% of the probability space? How short-sighted, dumb, or back-against-the-wall would Anthropic have to be to shift to a "let's make our new models intentionally _worse_ than our previous ones?" strategy? Think on this. I'm not necessarily "pro" Anthropic. They could lose standing with me over time, for sure. I'm willing to think it through. What would the world have to look like for this to be the case. There are other factors that push back against claims of a "short-term greedy strategy" argument. Most importantly, they aren't stupid; they know customers care about quality. They are playing a longer game than that. Yes, I understand that Opus 4.7 is not impressing people or worse. I feel similarly based on my "feels", but I also know I haven't run benchmarks nor have I used it very long. I think most people viewed Opus 4.6 as a big step forward. People are somewhat conditioned to expect a newer model to be better, and Opus 4.7 doesn't match that expectation. I also know that I've been asking Claude to help me with Bayesian probabilistic modeling techniques that are well outside what I was doing a few weeks ago (detailed research and systems / software development), so it is just as likely that I'm pushing it outside its expertise.
- glerk 6mo ago
  > To claim to know a company's strategy as an outsider is messy stuff. I said "it seems like". Obviously, I have no idea whether this is an intentional strategy or not and it could as well be a side effect of those things that you mentioned. Models being "worse" is the perceived effect for the end user (subjectively, it seems like the price to achieve the same results on similar tasks with Opus has been steadily increasing). I am claiming that there is no incentive for Anthropic to address this issue because of their business model (maximize the amount of tokens spent and price per token).
  - xpe 6mo ago
    >>> ... but it seems like Anthropic is going for the Tinder/casino intermittent reinforcement strategy: optimized to keep you spending tokens instead of achieving results. >> This part of the above comment strikes me as uncharitable and overconfident. And, to be blunt, presumptuous. To claim to know a company's strategy as an outsider is messy stuff. > I said "it seems like". Sorry. I take back the "presumptuous" part. But part of my concern remains: of all the things you chose to wrote, you only mentioned "the Tinder/casino intermittent reinforcement strategy". That phrase is going to draw eyeballs, and you got mine at least. As a reader, it conveys you think it is the most likely explanation. I'm trying to see if there is something there that I'm missing. How likely do you think is? Do you think it is more likely than the other three I mentioned? If so, it seems like your thinking hinges on this: > I am claiming that there is no incentive for Anthropic to address this issue because of their business model (maximize the amount of tokens spent and price per token). No incentive? Hardly. First, Anthropic is not a typical profit-maximizing entity, it a Public Benefit Corporation [1] [2]. Yes, profits matter still, but there are other factors to consider if we want to accurately predict their actions. Second, even if profit maximization is the only incentive in play, profit-maximizing entities can plan across different time horizons. Like I mentioned in my above comment, it would be rather myopic to damage their reputation with a strategy that I summarize as a short-term customer-squeeze strategy. Third, like many people here on HN, I've lived in the Bay Area, and I have first-degree connections that give me high confidence (P>80%) that key leaders at Anthropic have motivations that go much beyond mere profit maximization. A\'s AI safety mission is a huge factor and not the PR veneer that pessimists tend to claim. Most people who know me would view me as somewhat pessimistic and anti-corporate and P(doomy). I say this to emphasize I'm not just casting stones at people for "being negative". IMO, failing to recognize and account for Anthropic's AI safety stance isn't "informed hard-hitting pessimism" so much as "limited awareness and/or poor analysis". I'm not naive. That safety mission collides in a complicated way with FU money potential. Still, I'm confident (P>60%) that a significant number (>20%) of people at Anthropic have recently "cerebrated bad times" [3] i.e. cogitated futures where most humans die or lose control due to AI within ~10 to ~20 years. Being filthy rich doesn't matter much when dead or dehumanized. [1]: https://law.justia.com/codes/delaware/title-8/chapter-1/subchapter-xv/section-362/ https://law.justia.com/codes/delaware/title-8/chapter-1/subc... [2]: https://time.com/6983420/anthropic-structure-openai-incentives/ https://time.com/6983420/anthropic-structure-openai-incentiv... [3]: Weird Al: please make "Cerebration" for us.
Bridged7756 6mo ago
Mirrors my sentiment. Those tools seem mostly useful for a Google alternative, scaffolding tedious things, code reviewing, and acting as a fancy search. It seems that they got a grip on the "coding LLM" market and now they're starting to seek actual profit. I predict we'll keep seeing 40%+ more expensive models for a marginal performance gain from now on.
- danny_codes 6mo ago
  I just don’t see how they’ll be able to make a profit. Open models have the same performance on coding tasks now. The incentives are all wrong. Why pay more for a model that’s no better and also isn’t open? It’s nonsense
  - braebo 6mo ago
    Which open model has the same performance as Opus 4.7?
    - 3dfd 6mo ago
      They dont have to be parity today. If the frontier models reach a point of barely any noticeable improvements the trade off changes. You do not need a perfect substitute if you are getting it for free... People will factor in future expectations about the development of open source vs frontier models. Why do you think OAI and anthropic are pushing hard on marketing? its for this reason. They want to get contractual commitments that firms have to honour whilst open source closes the gap.
      - retsibsi 6mo ago
        The person they were responding to said "Open models have the same performance on coding tasks now." AFAIK this is bullshit, but I'd love to be corrected if I'm wrong.
  - Bridged7756 6mo ago
    I wouldn't say the same but it's pretty close. At this point I'm convinced that they'll continue running the marketing machine and people due to FOMO will keep hopping onto whatever model anthropic releases.
holoduke 6mo ago
You have to guide an ai. Not let roam freely. If you got skills to guide you can make it output high quality
- the_gipsy 6mo ago
  > skills to guide Is that what the soul is?
- glerk 6mo ago
  Of course, and I feel like Codex/GPT is generally better at following instructions and implementing a step-by-step plan and at a lower cost. Opus still has an edge in writing, brainstorming, and open-ended frontend vibe-coding. I’m definitely not coming to this from a “AI is useless” angle. I’ve been using these tools extensively over the past year and they are providing a massive productivity boost.
- wallst07 6mo ago
  That is 100% correct as a foundation. However when you guide the AI as a constant, and the model behaves MUCH differently (given a baseline guide), that is where the problem lies. It's as if your 'guidance' has to be variable on how well the model is behaving. Analogy is a junior dev who is sometimes excellent, and sometimes shows up drunk for work and you have no breathalyzer.
3dfd 6mo ago
[dead]

by glerk 6mo ago

xpe 6mo ago

> ... but it seems like Anthropic is going for the Tinder/casino intermittent reinforcement strategy: optimized to keep you spending tokens instead of achieving results. This part of the above comment strikes me as uncharitable and overconfident. And, to be blunt, presumptuous. To claim to know a company's strategy as an outsider is messy stuff. My prior: it is 10X to 20X more likely Anthropic has done something other than shift to a short-term squeeze their customers strategy (which I think is only around ~5%) What do I mean by "something other"? (1) One possibility is they are having capacity and/or infrastructure problems so the model performance is degraded. (2) Another possibility is that they are not as tuned to to what customers want relative to what their engineers want. (3) It is also possible they have slowed down their models down due to safety concerns. To be more specific, they are erring on the side of caution (which would be consistent with their press releases about safety concerns of Mythos). Also, the above three possibilities are not mutually exclusive. I don't expect us (readers here) to agree on the probabilities down to the ±5% level, but I would think a large chunk of informed and reasonable people can probably converge to something close to ±20%. At the very least, can we agree all of these factors are strong contenders: each covers maybe at least 10% to 30% of the probability space? How short-sighted, dumb, or back-against-the-wall would Anthropic have to be to shift to a "let's make our new models intentionally _worse_ than our previous ones?" strategy? Think on this. I'm not necessarily "pro" Anthropic. They could lose standing with me over time, for sure. I'm willing to think it through. What would the world have to look like for this to be the case. There are other factors that push back against claims of a "short-term greedy strategy" argument. Most importantly, they aren't stupid; they know customers care about quality. They are playing a longer game than that. Yes, I understand that Opus 4.7 is not impressing people or worse. I feel similarly based on my "feels", but I also know I haven't run benchmarks nor have I used it very long. I think most people viewed Opus 4.6 as a big step forward. People are somewhat conditioned to expect a newer model to be better, and Opus 4.7 doesn't match that expectation. I also know that I've been asking Claude to help me with Bayesian probabilistic modeling techniques that are well outside what I was doing a few weeks ago (detailed research and systems / software development), so it is just as likely that I'm pushing it outside its expertise.

glerk 6mo ago
> To claim to know a company's strategy as an outsider is messy stuff. I said "it seems like". Obviously, I have no idea whether this is an intentional strategy or not and it could as well be a side effect of those things that you mentioned. Models being "worse" is the perceived effect for the end user (subjectively, it seems like the price to achieve the same results on similar tasks with Opus has been steadily increasing). I am claiming that there is no incentive for Anthropic to address this issue because of their business model (maximize the amount of tokens spent and price per token).
- xpe 6mo ago
  >>> ... but it seems like Anthropic is going for the Tinder/casino intermittent reinforcement strategy: optimized to keep you spending tokens instead of achieving results. >> This part of the above comment strikes me as uncharitable and overconfident. And, to be blunt, presumptuous. To claim to know a company's strategy as an outsider is messy stuff. > I said "it seems like". Sorry. I take back the "presumptuous" part. But part of my concern remains: of all the things you chose to wrote, you only mentioned "the Tinder/casino intermittent reinforcement strategy". That phrase is going to draw eyeballs, and you got mine at least. As a reader, it conveys you think it is the most likely explanation. I'm trying to see if there is something there that I'm missing. How likely do you think is? Do you think it is more likely than the other three I mentioned? If so, it seems like your thinking hinges on this: > I am claiming that there is no incentive for Anthropic to address this issue because of their business model (maximize the amount of tokens spent and price per token). No incentive? Hardly. First, Anthropic is not a typical profit-maximizing entity, it a Public Benefit Corporation [1] [2]. Yes, profits matter still, but there are other factors to consider if we want to accurately predict their actions. Second, even if profit maximization is the only incentive in play, profit-maximizing entities can plan across different time horizons. Like I mentioned in my above comment, it would be rather myopic to damage their reputation with a strategy that I summarize as a short-term customer-squeeze strategy. Third, like many people here on HN, I've lived in the Bay Area, and I have first-degree connections that give me high confidence (P>80%) that key leaders at Anthropic have motivations that go much beyond mere profit maximization. A\'s AI safety mission is a huge factor and not the PR veneer that pessimists tend to claim. Most people who know me would view me as somewhat pessimistic and anti-corporate and P(doomy). I say this to emphasize I'm not just casting stones at people for "being negative". IMO, failing to recognize and account for Anthropic's AI safety stance isn't "informed hard-hitting pessimism" so much as "limited awareness and/or poor analysis". I'm not naive. That safety mission collides in a complicated way with FU money potential. Still, I'm confident (P>60%) that a significant number (>20%) of people at Anthropic have recently "cerebrated bad times" [3] i.e. cogitated futures where most humans die or lose control due to AI within ~10 to ~20 years. Being filthy rich doesn't matter much when dead or dehumanized. [1]: https://law.justia.com/codes/delaware/title-8/chapter-1/subchapter-xv/section-362/ https://law.justia.com/codes/delaware/title-8/chapter-1/subc... [2]: https://time.com/6983420/anthropic-structure-openai-incentives/ https://time.com/6983420/anthropic-structure-openai-incentiv... [3]: Weird Al: please make "Cerebration" for us.

Bridged7756 6mo ago

Mirrors my sentiment. Those tools seem mostly useful for a Google alternative, scaffolding tedious things, code reviewing, and acting as a fancy search. It seems that they got a grip on the "coding LLM" market and now they're starting to seek actual profit. I predict we'll keep seeing 40%+ more expensive models for a marginal performance gain from now on.

danny_codes 6mo ago
I just don’t see how they’ll be able to make a profit. Open models have the same performance on coding tasks now. The incentives are all wrong. Why pay more for a model that’s no better and also isn’t open? It’s nonsense
- braebo 6mo ago
  Which open model has the same performance as Opus 4.7?
  - 3dfd 6mo ago
    They dont have to be parity today. If the frontier models reach a point of barely any noticeable improvements the trade off changes. You do not need a perfect substitute if you are getting it for free... People will factor in future expectations about the development of open source vs frontier models. Why do you think OAI and anthropic are pushing hard on marketing? its for this reason. They want to get contractual commitments that firms have to honour whilst open source closes the gap.
    - retsibsi 6mo ago
      The person they were responding to said "Open models have the same performance on coding tasks now." AFAIK this is bullshit, but I'd love to be corrected if I'm wrong.
- Bridged7756 6mo ago
  I wouldn't say the same but it's pretty close. At this point I'm convinced that they'll continue running the marketing machine and people due to FOMO will keep hopping onto whatever model anthropic releases.

holoduke 6mo ago

You have to guide an ai. Not let roam freely. If you got skills to guide you can make it output high quality

the_gipsy 6mo ago
> skills to guide Is that what the soul is?
glerk 6mo ago
Of course, and I feel like Codex/GPT is generally better at following instructions and implementing a step-by-step plan and at a lower cost. Opus still has an edge in writing, brainstorming, and open-ended frontend vibe-coding. I’m definitely not coming to this from a “AI is useless” angle. I’ve been using these tools extensively over the past year and they are providing a massive productivity boost.
wallst07 6mo ago
That is 100% correct as a foundation. However when you guide the AI as a constant, and the model behaves MUCH differently (given a baseline guide), that is where the problem lies. It's as if your 'guidance' has to be variable on how well the model is behaving. Analogy is a junior dev who is sometimes excellent, and sometimes shows up drunk for work and you have no breathalyzer.

3dfd 6mo ago

[dead]