Comment by neilv
8 hours ago
Yet the new AI startups I'm seeing are only offering terrible deals to early hires who could improve their chances of a nice exit.
In this crazy environment -- in which money is flying around over AI much like the dotcom boom, but startup founders are using the last-decade playbook of not sharing the wealth with early hires -- I'm starting to think that smart AI job-seekers need to either:
* get hired by a company that is willing to invest in hiring (i.e., reasonable salary and/or meaningful equity); or
* build some AI application IP at their kitchen table, to sell to a company that's flush with cash, and wants to invest in AI acquisitions.
You've stumbled upon the same trade Matt Levine has been pointing out for a few months now.
If you're good at AI, you could get hired at a top-tier company for 1-2M annual comp, and expect to stay there for at most five (5) years. That's a maximum of 10M pre-tax, and you'd be still on the receiving end of employment gauntlet.
Alternatively you could spin up an AI startup, and get acquired for 75M+ in less than 2 years.
In less surprising news, Matt has pointed out a number of deals that look quite a bit like that throughout 2025.
Bubble aside, it feels AI is by nature a less democratic tech.
The need for stupid amounts of data and hardware make it less likely that a really talented person can outcompete companies from their basement. That probably influences culture.
It's why these people love AI so much. Less of a competition to worry about.
True, but I think there's kitchen table opportunity in applications that don't need to do a big training, and that have tractable inferencing requirements.
The challenges I see are: (1) there's a lot of competition in the gold rush; (2) there's a lot of noise of AI slop implementations, including by anyone who sees your demo.
You also can fine tuned LLMs. For that, you don't need big money. You also can pick up a fine tuned LLM and go from there and make it better ( for your use case)