Startups in San Francisco raise $18 million just to afford the compute.
Some raise hundreds of millions.
We're doing the same kind of work bootstrapped. No venture capital. Essentially no leverage.
I want to be honest about why we can even attempt that, because the honest version is uncomfortable.
We got lucky, and luck isn't a strategy
Before this, we built a fintech company. It made money.
We still earn monthly revenue from a SaaS business we wound down.
That cushion is the only reason we could absorb what building AI costs.
Without it, we would not have started. Full stop.
The cost is the gate
People assume the hard part of AI is the ideas, or the engineering talent.
For a growing number of teams, it isn't. It's the bill.
To fine-tune real models you need GPUs. Renting them - if you can even get a quota - runs into thousands of dollars a week.
We were quoted $14,000 a week by one provider.
That cost lands before you ship a single feature. Before you even know if the thing works.
So the question stops being "can you build it?"
It becomes "can you afford to find out?"
This isn't an anti-VC rant
Venture capital isn't the villain here.
For a lot of companies it's the right tool, and the best investors earn their keep many times over.
The problem is narrower, and more structural than "VC bad."
When the cheapest way to learn whether your idea works costs more than most people will ever raise, the decision about what gets built moves upstream - to whoever controls the capital.
The model doesn't get a vote. Neither does the market.
The check does.
What that does to who gets to build
When the entry fee is millions, the field narrows to people who already have millions - or who can convince someone with millions to write a check.
That isn't a meritocracy.
It's a filter on access to capital, dressed up as a filter on ability.
The most capable builder in a mid-size Canadian city, or in Lagos, or in São Paulo, may simply never get to try.
Not because they can't.
Because they can't afford the room.
Why this matters even if you'll never train a model
If only the well-funded can build AI, then AI gets built by a very narrow slice of the world.
And it inherits that slice's blind spots.
The tools everyone ends up depending on get shaped by whoever could afford to make them.
That should bother you even if you never plan to touch a model yourself.
What we're trying to do about it
We can't fix the cost of GPUs.
But we can refuse to hoard what we learn paying it.
Everything we build ships open weight and open source at getsimpledirect.com - models, datasets, and the methods we figured out the expensive way.
The goal is simple: lower the entry fee for the next team by as much as we possibly can.
We made it into the room the slow way.
The least we can do is leave the door open behind us.
The line I keep coming back to
The barrier to building AI isn't talent.
It's whether you can afford to be in the room.
Until that changes, the most useful thing the people already inside can do is hand the next person a key.