It reminds me of this Steve Jobs Clip:

https://youtu.be/0lvMgMrNDlg?si=QkkOnngYTjaSPlIy

He said, so many years ago, that there will become a time where computing power is so prevalent that we will stop using the person to make the computers job easier and start using the computer to make the humans job of interfacing with it easier.

But in this context, it would mean the other side of increase productivity is decreased time to do the same work. These are the same thing.

Product market fit and profitability are two different things.

Arguably product market fit was fond last November already. I don't think agents were the turning point that caused this.

Profitability, not yet. For me, it depends on whether companies are seeing a positive ROI from their ai investments. This website is skewed more towards big tech companies, but everyone that's not big tech needs to see positive ROI with using ai tools. Short term might see a profit, but medium to long term we still need to wait a bit.

Well, good for them that they are charging enterprises API rates. Why in the world not do something similar for consumers? Use for free a few times a day, have a $5 dollar plan for light use, and perhaps $10 to $15 for heavier use. If 90% of consumers pay nothing then ‘drop them’ except for letting them have an account and a few queries a day.

It is easy for me to change providers. Right now I use the open source Claud Code harness with two paid API venders for DeepSeek v4 (flash and Pro). I like seeing how much each session costs.

This is great analysis but my first reaction was - is this trolling? The fact that we have to think about whether a $1TN company has achieved product-market fit both articulates 1/just how high the valuations are 2/How hard it is to pin down EXACTLY what PMF is. As a pre-revenue startup, I am laser focused on PMF and frankly if this is the bar, no one will achieve it. But OTOH its heartwarming that people are willing to value you at $1TN before you reach that. Guess everything is in the eye of the beholder?

this is an opinion and i would love to debate :) dont hate me too hard

i think the article is momentaneously correct but there are some things that smells to me about the situation overall (not the article!)

(1) i believe gpt 5.5 and opus 4.7 are not as good improvements as their predecessors and there has been not enough evolution in those models to justify the price increases. Unless something big changes in the next few years they will not be able to track these costs (unless A)

(2) they might not be able to keep up improving the data centers if their tech keeps demanding more and more hardware capability. even nvidia does not show signals that they will be able to beat too much their big GPUs and at some point this increased price will be passed to them anyway which will need to be put in the token price (unless A)

(3) i've been trying deepseek v4 and other models and honestly, they are more useful than gpt 5.5 and opus 4.7... i mean, there is still a difference, but it is so little that it does not make sense the cost of opus and gpt 5.5 (unless they are going to A too)

(A) I have the impression is that the plan was the whole time to sideline common folks like us and focus on gov, big techs and military. they only let us play with the toys to gather data and for people to not get mad because they stole the internet from us.

With respect to Simon, whose writing I've usually agreed with in the past and whose insights I've liked: this is a bad take that overlooks the extent to which corporations are imposing the use of AI on employees, and in particular ICs, who make up a majority of the AI-using workforce by headcount.

Many of us are either openly having our performance reviews tied to AI use, especially at larger enterprises. Whether that's measured by sheer token count or just "how many of your tasks are you using AI for these days" (combined with the implication that question carries at many orgs which are heavily invested in AI).

I think the third company (likely Google) is going to make LLMs financially feasible with:

- dedicated hardware (https://cloud.google.com/tpu)

- optimized models (https://research.google/blog/turboquant-redefining-ai-effici...)

I'm surprised by how good coding agents are. I think PMF was reached last year or the year before (at least for coding).

With current limits my 100/mo codex subscription is more than enough for the work I do.

However, I do worry about when does current subsidies are going to end? I can see myself paying up to 300/mo, but more than that will be prohibitive.

What's the long term plan here? Are OpenAI's and Anthropic's costs expected to increase/decrease?

The product-market fit question feels premature when most usage is still developers building on top of the APIs, not end users paying directly.

They have the whole software industry addicted to AI. They will be pushing the price continually up, and like addicts they will find a way to pay