Re:Leaked financial docs show OpenAI is losing billions of d...
by apatheticonion on Wednesday June 17, 2026 @08:11PM
(#48578805)
> You're pricing it wrong and looking at it wrong. First, the per token price doesn't consider that a smarter model can end up using fewer tokens overall to achieve a result. Secondly, if the difference is between failing to accomplish the task and accomplishing the task, suddenly that 50x can seem like a bargain.
Perhaps, yeah. Napkin math; if we go off of the assertion that DeepSeek makes me twice as productive for an extra $24 per year.
The same number of tokens with Fable would be around 50k/y. Say Fable uses half as many, that's still 25k
The question is then; How does Fable make an engineer more productive than DeepSeek?
- Prompt adherence?
- Inference speed?
- Can engineers delegate more work to unsupervised autonomous workflows?
Are unsupervised workflows suitable for production applications or does the review overhead erode the productivity benefits?
Perhaps a company could hire a mid level engineer + Fable to achieve senior engineer levels of productivity for the same price as a senior + deepseek.
Re:Leaked financial docs show OpenAI is losing billions of d...
by jurgenburgen on Monday June 22, 2026 @08:11AM
(#48629078)
> Even when you unlock AGI
Massive assumption there.
There's always working on improving the cost of inference, but I don't think this is an area of R&D that will slow down. The reason is:
1. A better competitor model risks eating away at how much they can charge for inference (i.e. revenue) 2. Whoever unlocks AGI will unlock even more growth 3. Even when you unlock AGI, you'll want to throw gobs of money at it to improve itself and all sorts of things.
> If Fable comes out and demands 50x the price of DeepSeek in order for Anthropic to make a profit on it, how much more productive would I be compared to my personal experience + DeepSeek? 3x? 50x?
You're pricing it wrong and looking at it wrong. First, the per token price doesn't consider that a smarter model can end up using fewer tokens overall to achieve a result. Secondly, if the difference is between failing to accomplish the task and accomplishing the task, suddenly that 50x can seem like a bargain.
> Is it cost effective for a business to hire someone without SWE experience + Fable verses hiring someone with SWE experience and DeepSeek? When does R&D hit diminishing returns?
At this time, someone without SWE experience + <name AI model> vs someone good with SWE experience and <name another AI model> is a no-brainer. The AI model is an accelerant but the "no SWE experience" will be accelerated into a wall. Now maybe that doesn't matter for prototyping and certain other things, but anything in production the lack of experience will hurt them with things they won't even know about or even know how to look for it (e.g. slow, insecure, etc).