This weekend, on a Sunday, I took our own AI models off our own app and replaced them with a competitor's.

We're an AI model company.

Or we were.

This is the story of how that decision happened in 24 hours - the four days before it, what it cost me to see it, and what I think other founders can take from it.

Day 1 - my own product told me the truth

We spent months training small open-weight models for honesty - models that say 'I don't know' instead of inventing answers.

I believed in them. I still do, for what they are.

Then I built our coding CLI and put our models inside it.

They failed. Our 4B failed. Our 9B failed.

Multi-step agentic work, the thing our flagship product needs - they couldn't hold it.

The worst part? Our own model card predicted it. We'd published 'not recommended for autonomous agentic loops' ourselves, weeks earlier.

I knew it on paper. Watching it happen is different.

Day 2 - I noticed my own behavior

That same week, a new frontier model came out.

Faster and better than the one I'd been using every day.

I switched my daily coding agent in one afternoon.

No hesitation. No loyalty. The old one was great last month - didn't matter.

Then it hit me: I am the market.

If I - a founder who runs an AI company, who has every reason to be loyal to tools and ecosystems - switch in an afternoon, everyone switches in an afternoon.

There is no loyalty anywhere in this industry right now.

Not from users, not from enterprises, not from me.

Whatever we built had to survive that fact, not deny it.

Day 3 - the spreadsheet

I looked up what the best open model in the world costs to run through American inference providers.

About $1 for a serious agentic coding task. Sometimes half that.

I'd loaded $100 into an API account on July 1 to build our CLI.

12 days of heavy testing later - full workloads, everything - I'd spent $31.

Meanwhile, we were paying about $5,000 a month per GPU to serve our own small models. To a handful of users. Models a laptop could run.

I sat with that for a while.

We weren't serving our models because it was right for users.

We were serving them because they were ours.

There's a word for that, and it isn't strategy.

Day 4 - the call

This morning, again a Sunday, I called Ayush, our engineer.

I laid it out: take our models off the GPUs, serve the best open model instead, cap our markup at 15%, publish everything - the costs, the prices, what's behind every product name.

Keep training our own models.

But set one rule: they only go back into the product by beating the best alternative in public, on published evals. If ours loses, we tell people to use the winner.

He agreed in 20 minutes.

When the strategy is honest, the meetings get short.

What I learned

Your own usage is the tell.

I could have read 100 market reports about model switching.

Watching myself dump my daily tool in an afternoon taught me more.

If you want to know where your market is going, watch what you do when nobody's watching.

Sunk cost arrives dressed as mission.

'We serve our own models' sounded like conviction.

It was $5,000 a month of not wanting to admit the benchmarks applied to us.

The more noble the reason sounds, the harder you should check it.

Nobody has a moat, and that's information, not doom.

Users switch overnight. Open weights collapse prices to cost.

The lab that made the best open model can't even win at serving it - American providers undercut them on their own weights.

Once you accept that nobody can hold territory, the game changes. You stop building walls and start building the things that survive every wave.

For us that's trust, cost discipline, and the ability to change our minds in four days.

Speed of surrender is an asset.

The pivot took 24 hours because we're three people with no investors to convince and no sunk narrative to protect.

A bigger company would still be scheduling the meeting.

Being small doesn't win you many fights - but it wins you this one, every time.

Where that leaves us

We're tiny. A handful of users. A few hundred model downloads.

This issue will be read by more people than use our product.

I'm fine saying that, because the entire company is now a bet on one thing: in a market with no loyalty and no moats, the only thing left worth building is a track record of telling the truth.

Cheapest possible prices, capped markup, honest meters, public evals - and when we get something wrong, you'll read it here first.

The CLI ships this week. I'll publish the numbers, including the bad ones.