I recently switched off Max flat rate to Enterprise API pricing and I went from 200/mo to 10k/mo with the same usage pattern on Opus. They don’t offer flat rate to enterprises.
So Fable would cost me 20k/mo at Enterprise rates. That’s around the average cost of a loaded SWE in the USA. “But I’m >2x more productive” doesn’t justify doubling the opex of the Software/IT department for most companies when revenue isn’t even up 10%.
I switched to DeepSeek v4 Pro with OpenCode and am on track for a few hundred dollars of spend this month.
Rewriting your stack from Ruby to Go in 2 days where it would’ve taken 6 months is impressive and fun. But that isn’t upping revenue.
Iterating on net new business features and ideas that are niche that the LLM isn’t trained for are much harder. Is 20x the token cost worth it there?
I don't live in USA. I'm getting paid around $2500/month and that's good salary for developers here, plenty of folks are getting below that number.
So this pricing is just completely outside of our economics and nobody I know would pay that, no company will justify spending $20k/month when they can hire 10 more developers instead.
It is very interesting unfolding of events. Can't wrap my head around it completely.
Not justifying AI expenses, but $2500/mo could easily cost employer close to 5000$/mo depending on country.
Not doubting this at all but could you (or someone else) break this down for the sake of my curiosity?
I understand pension contributions, but what are the other "hidden" costs that could equal the net salary?
In the UK, a £45k/yr employee pays their own tax and gets a take-home of £35k.
The employer pays £6k for National Insurance (atop the employee's NI contributions). Pension: 2-3k. Apprenticeship levy is £300. 3yr-amortised recruitment fee is £4000. Hardware costs: £1000. Office space £5000. Software/tools: £2500. Benefits: £1500. Training: £1000. Other admin overheads £500.
You pay that person for ~250 working-days, but they only attend for ~220, due to annual leave and sick pay, so you get around £62k worth of attendance out of that person in exchange for £70k, of which the employee sees £35k.
A quick google tells me that software devs usually count for 20% to 40% of the total workforce in a software company. The rest is overhead that increases with every added dev.
Example from Germany: Employer also pays a share of health insurance, unemployment insurance, public pension and elder care insurance.
This is not visible on your payslip, i.e. if you earn 5k€ brutto, the employer has to pay these shares on top of that.
But that is 20% not 100%. And in most non retarded countries brutto is actually brutto, because there is no need to lie to people about how much the government takes away
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I think you are broadly correct, but just to pushback on a few points: (1) Ability to solve hard problems in days vs weeks as immense value (2) Back-end improvements (if done right), should improve platform speed, stability, scalability etc. which should have revenue implication (3) Ability to on-board a SWE equivalent entity in minutes, have them work on a specific hard problem and then off-board them in minutes can have value
All of the above, of course, depends upon Fable consistently being a 2x-3x SWE at minimum.
You're not really solving problems, you're retrieving the best match of solved problems from compressed corpus. And that corpus is available to many companies, meaning "hard" problems stop having "hard problem" value the moment they enter the weights of any model via the internet ... or distill from one model to another. Anthropics business model is commoditising knowledge, but as we see with the Fable model card, they only want it done to the knowledge of other businesses, in their own field, they totally hate it.
I don’t think that’s an accurate or useful characterization of modern AI like Claude at all. It is not simply regurgitating knowledge. It applies its knowledge to create bespoke solutions to the problem you pose to it, and is able to self evaluate its progress towards the completion criteria. If you don’t think that counts as “problem solving”, your definition would exclude nearly all knowledge work and engineering.
> It applies its knowledge to create bespoke solutions to the problem you pose to it, and is able to self evaluate its progress towards the completion criteria.
It imitates applying knowledge. The imitation may be uncanny, but assigning LLMs intentionality and ToM is a category error.
> Back-end improvements (if done right), should improve platform speed, stability, scalability etc. which should have revenue implication
Depends entirely on the domain. If you're selling entreprise software, this kind of stuff barely matters for sales.
It can reduce operational costs which is good but there's a limit to how much that's worth.
Yep, there are many, many, non-niche domains in which this doesn’t mean much at all.
“Ability to solve hard problems in days vs weeks as immense value”. Citation needed.
LlMs are incredible don’t get me wrong, but they are good on tiny contexts (writing a script). Not on software engineering (adding features to Chrome).
Honestly, LLMs been OK at adding features to software since around Opus 4.5. From what I've tried of Fable, it's a decent step up from the Opus models and I can only see things getting better.
>pushback on a few points
Claude keeps telling me this when I argue with it. LMAO.
“gently push back”
> Is 20x the token cost worth it there?
No it doesn’t and will not be. Companies have not realised the cost yet, wait till the end of the financial year and you’ll see a different direction.
DeepSeek v4 is pretty decent, and probably on par with sonnet. I see a future of hybrid models where opus or fable might be used only for complicated features or bugs, but general day to day would be DeepSeek or whatever good models that will be released later.
With GPT 5.5 on the $100 plan, it's hard to hit any 5h/7d limits - while allegedly being better than DeepSeek 4 pro. Not sure why, or how you spend "a few hundred dollars of spend".
With that said, I still had the Pro plan on Claude, I didn't expect much, but it blew up my 5h allowance on Fable with one simple single prompt, and it didn't even complete lmao
Important to note that both OpenAI and Anthropic do not allow the subsidized monthly subscriptions for enterprises.
Companies have to pay monthly for the harness app (codex, claude code) and the tokens are priced separately based on standard API pricing.
I'm on $200 plan which is supposedly 20x usage of $20 plan. With few Fable prompts (I'm working on u-boot port) I got 10% of my 5h usage, so that's already 2x of $20 plan usage and that would be 40% of $100 plan.
So Fable is just not usable for $20 plan and barely usable for $100 plan.
>I switched to DeepSeek v4 Pro with OpenCode and am on track for a few hundred dollars of spend this month.
I was about to say that. Deepseek is just magnitudes cheaper and absolutely good enough for most things. Anthropic and co just try to milk the cow while its possible. If they cant compete with Deepseek pricing I do not see a bright future for them.
Not only Deepseek, other providers such as Xiaomi MiMo are excellent as well and offer fast token modes and other perks.
Its too bad my boss views China as the big evil country so he wont ever make the switch to Deepseek but then proceeds to throw all our data to US companies like OpenAI or Anthropic...
There are US providers for DeepSeek v4, MiMo 2.5 and GLM 5.1.
Do you understand that, for 10-20k a month, you can hire 1-2 senior engineers AND give them Claude subscriptions?
will they be a better investment than your current staff engineer with fable token allowance?
Are you seriously asking if employing people, for the same cost, is a better ‘investment’ than relying on LLMs? Jesus Christ.
I am because CEOs are. Look where the puck is going. Sorry to update your p(doom) priors in this way, it was obvious to anyone paying attention years ago conditioned on uplift trend persisting. Trend persisted and here we are.
Welcome to the new world. People start to repeat what tech founders preach. They do not require humans in the mix. Peter Thiel gave a good example of that mindset in a (mostly) recent interview where he didn't have an answer on "Should humanity survive?"
https://youtu.be/ngtp3v1_nCI
Yes. Hiring people has various benefits, I will lay them out for you:
- They learn the domain of your product, which means long term ownership and knowledge establishes itself. If you've only ever shipped SaaS slop, you might not know, but lots of companies are solving real world problems that have no better solution. Owning and understanding the code and the domain is key.
- They will learn from their mistakes (no LLM does this).
- Human skill is a REAL moat. Once you build a team that fully understands and is skilled in the domain you work in, these people are going to be the thing that sets you apart. If some of them are particularly social or charming, let them sit in with you for meetings and watch them provide loads of value, for no added cost.
- If Claude or OpenAI is down, they will continue thinking. In fact, they will continue thinking even when off the clock! This is a neat little hack called "consciousness" where you get a lot of work for free!
- You can hire people who punch above their weight; not everyone you hire needs to be a 500k/year staff software prime engineer of doom, you can just spend some time and effort to hire good juniors/competent mediors who will think for themselves (gasp!) and get work done.
- You still get ALL THE BENEFITS OF AI!!!! They can use AI just like you can, or better!
- You get people who you can brainstorm with, which is distinctly different from LLMs because your employees are less likely to want to suck you dry in every sentence just to make sure you spend more tokens. Employees don't care if you love them, they care about the quality of their work if you manage them correctly and reward that.
- They are quite loyal if you treat them right; spend a little more on their well-being, and they will stick around, come in to work every day and deliver cool things with you.
- Humans can only manage, review and give tasks to so many agents. If you add more humans, you can handle more agents.
An expensive LLM and a lot of extra tooling gets you some of this, yes, but not all of it. With humans you can still do the expensive LLM and extra tooling if you end up making enough money anyway.
I’m sorry sir this is HN, your post is too sensible.