Yup, I said that, and most teams only realize this when one customer suddenly scales usage in production and everything feels great until "someone" asks if that customer is profitable and nobody in the room can answer with confidence.

- Engineering sees higher throughput - Growth sees engagement

but under the hood, costs are coming from three different models, agents are retrying silently, credits are being deducted inconsistently and a discount someone promised over email is now baked into the invoice forever.

Nothing is technically broken here, yet the business feels brittle, right?

THIS is the new AI economy. It’s rich, dynamic, and constantly shifting.

Every model switch changes margins. Every agent loop is a pricing decision. Every new feature quietly alters unit economics.

If there's one thing talking to the biggest players in AI in SF has taught me in the past few months, it's that pricing is no longer a static config you set once. It’s part of the runtime whether you like it or not.

Treat pricing as an afterthought and it won’t crash loudly. It’ll punish you slowly.

What we have been building at flexprice has been built exactly to bridge this, to give AI teams a pricing system that behaves like their product does.

Programmable, usage-aware, and designed for change, so pricing stops being the weakest link in an otherwise modern stack. Act now, your product still has time!

Love the clarity. But how long is too long before everything goes south?

Spot on. The 'brittle' feeling usually comes from the disconnect between the engineering team shipping features and the finance team trying to project margins. When every agent loop is a pricing decision, you can't rely on a monthly billing cycle to tell you if you're profitable. Treating pricing as part of the runtime is the only way to scale without getting a nasty surprise on your compute bill.