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Anthropic's best AI model struggles to attract users as cheaper tools thrive

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Re: Anthropic's best AI model struggles to attract users as cheaper tools thrive

#541

Post by mark_l_watson »

adriand wrote: post #143
fluidcruft wrote: post #125

Earlier quoted context omitted.

Yeah, I agree with this. The constant state of "...will the rug be pulled?!?" does discourage relying on it as a model and building a workflow on it. Anthropic used to just be a reliable thing you could play with. Now it's this constant source of anxiety. It also didn't help that the government yanked it which adds another source of anxiety since OpenAI is on much better terms with the administration and the administ…

As soon as I started using Fable I was like, okay, this is probably as good a model as I will need for software engineering going forward. I still feel that way. I don’t need a better model, I need a faster Fable. The thing I miss most about programming is flow, and the constant bouncing between terminal tabs sucks. I’d love to do one thing at a time, with Fable, quickly.

I have lower standards than you: I pay for deepseek-v4-flash-0731 tokens from a fast and reliable US vendor and I feel like working on one task at a time is fast and gets almost everything done I need.

Re: Anthropic's best AI model struggles to attract users as cheaper tools thrive

#542

Post by throwaw12 »

a1371 wrote: post #113

Where Anthropic f'ed up was treating their monetization the way they treat model training. Turns out that success in experimentation is not transferrable. They have tried to find the highest that the market pays for sota models; however, on the consumer side, this is just too confusing and unsettling: "You can only use Fable for a week as a part of your plan" "Be ready! You have to start paying per token!" "Nevermind…

it also feels like they are optimizing their models to output more tokens, because everyone is saying inference is profitable, they wan't to close the gap between training and inference cost by increasing output token count (which also increases input tokens in agentic use cases), with 5 min TTL, this means you almost don't have a cache

Re: Anthropic's best AI model struggles to attract users as cheaper tools thrive

#543

Post by carlosjobim »

bluegatty wrote: post #305
carlosjobim wrote: post #251

Earlier quoted context omitted.

International trade is a giant sector already, and potentially much bigger than that, now that LLM assisted translation makes it easy to offer your products and services in any language, or make complicated and sensitive deals without a common language. Hackers always rage and down vote every time I mention this, because they are unable to see beyond their small world. Why didn't they learn that their part of the int…

Product marketing and contracts will be a 'common use case' we think of, but it will be 0.000001% of tokens consumed. A developer using sub-agents will consume more tokens 1 Day than a marketing manager will consume 1 Month, easily. Unless there is something inherently automated about the nature of the AI, it will be a tiny % use case. Even a lawyer, using AI daily for contracts - that will be relatively light use. T…

If a salesperson uses 100 000 tokes for translation, which gives him $10 000 in sales.

And a programmer uses one million tokes, which gives him $100 in sales (or value).

What is then the value of a token?

The comment I answered asked where there is an industry finding 10s or 100s of billion of dollars in value from LLMs. The answer is translation. It's the value they as customers get out of the LLMs, not what cost they are paying for the LLMs.

Value has to be counted in production, not consumption.

> Developers and Automation are the 'primary' uses cases for AI

Just like programmers and scientists were the primary users of the Internet when it began. But things change rapidly.

Re: Anthropic's best AI model struggles to attract users as cheaper tools thrive

#544

Post by ray_kay777 »

Zizizizz wrote: post #318
ray_kay777 wrote: post #227

Earlier quoted context omitted.

While there's no linter for writing contracts, my experience (as a commercial lawyer) is that frontier LLMs are far better and error checking and far quicker at writing than the average senior lawyer. The main thing holding back further deployment (in my jurisdiction) are concerns around data residency, privilege and how fundamentally it will break an industry that is so heavily reliant on time based billing.

I agree with you in respect to the greatest risks in that industry. Just thought it's worth mentioning that LLM's unsurprisingly are not immune to hallucinating cases. https://www.scientificamerican.com/article/why-lawyers-keep-... Using them for coding makes it easy to self check its work (assuming those pieces of work are "verifiable"). As proofreading will still need to happen, what do you think the appetite for l…

With access to good databases and tool use, hallucinations are basically a thing of the past (and very easy to verify). The hallucination issue typically comes from people using free ChatGPT or similar - tech usage and literacy is often poor and there's a lack of understanding of the risks of using something without proper legal database tools. Most lawyers would not have the faintest idea of what tool use in the context of an LLM even means. It's still seen as a magic box rather than a tool for real work.

Will it drive down fees significantly? Doubt it, there's not enough pressure on them, and the industry is resistant to change. Firms don't want to make a big deal about using it because clients will then ask why they're not getting a discount.

Will it empower younger lawyers? Not as much as I'd like. I'm very fortunate to have an employer that lets me use Claude Code for my work (to a limited extent). I think for 99.9% of lawyers it's not an option available to them, through a mix of concerns around AI usage and concerned IT departments. There could be great benefits, but it would rely on having to break out of traditional private practice which would make it difficult to get enough work.

I think in the near term LLMs will have much the same impact on the legal industry as it has on the software industry.

Re: Anthropic's best AI model struggles to attract users as cheaper tools thrive

#545

Post by ray_v »

a1371 wrote: post #113

Where Anthropic f'ed up was treating their monetization the way they treat model training. Turns out that success in experimentation is not transferrable. They have tried to find the highest that the market pays for sota models; however, on the consumer side, this is just too confusing and unsettling: "You can only use Fable for a week as a part of your plan" "Be ready! You have to start paying per token!" "Nevermind…

Not only that but it appears as if they're also treating the platform that customers actively use in such a way as well - heavily A/B testing features and behavior of the platform with little regard for customer comfort in terms of platform use, moving targets for subscription limits, etc etc. I suppose most of us chalk it up to the technology being new and evolving, but I'm not so sure everyone shares that same sentiment clearly.

Re: Anthropic's best AI model struggles to attract users as cheaper tools thrive

#546

Post by skerit »

reticulates wrote: post #378
nl wrote: post #357

Earlier quoted context omitted.

I have no idea what you think violates the TOS here? I was doing work at work on a work task using a plan paid for by work.

The $200 max plan is for individuals. The individual plans are heavily subsidized. Employers should be using either the Team plan (which has much lower limits than max) or the Enterprise plan (which is entirely billed on usage). Anthropic know that lots of people are doing all sorts of “bad” things like employers paying for Individual plans, (and using multiple accounts to get more usage) and aren’t yet enforcing the…

> The individual plans are heavily subsidized

Not this again. There is not a single shred of evidence for this. In fact multiple times this year alone, people from Anthropic have said that inference and deployed models have positive margins. The big bucks are always being spent on training the next model.

Re: Anthropic's best AI model struggles to attract users as cheaper tools thrive

#547

Post by nik736 »

For me Opus 5 was the nail in the coffin. Fable without the restrictions was a great model, but became unusable with the security guardrails. Opus 5 became so bad and slow it's unbearable. And since Fable falls back to Opus all the time it was time to switch. Me and my friends are calling it Slowpus by now... Up until some weeks ago Anthropic was the king, but we all switched to Grok 4.6. It became slow as well but is not down all the time, is a solid model and paired with another reviewer model it's a great daily driver.

Re: Anthropic's best AI model struggles to attract users as cheaper tools thrive

#548

Post by jaapz »

a1371 wrote: post #113

Where Anthropic f'ed up was treating their monetization the way they treat model training. Turns out that success in experimentation is not transferrable. They have tried to find the highest that the market pays for sota models; however, on the consumer side, this is just too confusing and unsettling: "You can only use Fable for a week as a part of your plan" "Be ready! You have to start paying per token!" "Nevermind…

Also, for whatever software engineering work I throw at Fable 5, Opus 5 also does fine. Apparently Fable is supposed to do better at long running tasks (in other words - burning more tokens without interacting with the user), but that's not the kind of work I'm doing.

After Fable 5 launched, it was better than Opus 4.8 for sure. Then they rug-pulled Fable from me (EU), and later released Opus 5. Now I only reach for fable when Opus 5 API returns 529 for the millionth time this year.

Re: Anthropic's best AI model struggles to attract users as cheaper tools thrive

#549

Post by serial_dev »

antonvs wrote: post #516
anon373839 wrote: post #497

Earlier quoted context omitted.

This is such a tough problem. Anthropic would need access to some kind of technology that could, like, intelligently handle unforeseen circumstances and nuances. Yeah, that’s definitely not something we should expect of them.

It’s interesting how much Anthropic itself is a demonstration that its own hype is false.

Just use any product going all in on AI hype. In 5 minutes you will see annoying bugs, server is down, non-sensical press releases, confusing UI. This is GitHub, this is Cursor, this is Anthropic, this is Google, this is all of them.

Re: Anthropic's best AI model struggles to attract users as cheaper tools thrive

#550

Post by jghn »

azalemeth wrote: post #442
adriand wrote: post #143

Earlier quoted context omitted.

As soon as I started using Fable I was like, okay, this is probably as good a model as I will need for software engineering going forward. I still feel that way. I don’t need a better model, I need a faster Fable. The thing I miss most about programming is flow, and the constant bouncing between terminal tabs sucks. I’d love to do one thing at a time, with Fable, quickly.

I _still_ haven't actually been able to _use_ Fable at all. Those safeguards just refuse biology in general.

It changed for the better a few weeks ago. Obviously it depends on what one is doing but I haven’t had an issue with my biology related material since that update
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