This works for a PLG motion with credit top-ups and for complex enterprise contracts alike.
You can change your monetization as fast as you ship, without the engineering overhead.
Full announcement on our blog π https://t.co/bIqUzLgvzu
AI-native companies ship features weekly.
Their monetization infrastructure usually canβt keep up. Every pricing change means more custom code and more engineering time. π οΈ
So we partnered with @Airwallex. π§΅
And the closing warning: don't over-engineer for every imaginable future.
Name the knobs you'll actually need in the next 6-12 months. Build those with correctness first.
"Watch out for those trapdoors. That's where you ask the hard questions."
https://t.co/ow60Db5su5
Almost every team builds rate limiting and billing as two separate systems. Different owners, different code paths, different problems entirely.
AI collapses them into one.
Here's what OpenAI learned rebuilding the system that decides, in real time, whether to serve your request. π§΅
The irreducible core, for any team shipping AI:
Your DB must give you transactions (single-shard, multi-record, non-negotiable)
Unify product usage events + billing into ONE system
Bonus: usage events prove you delivered the service (hello, ASC 606)
@DorSasson 's talk packed the room at AI Engineer World's Fair in SF last week. Missed it? Here are the highlights.
April 2026: every AI pricing plan broke at once. 3 labs, 5 panicked billing moves in 4 weeks, all tracing back to one thing. Nobody knew what a request actually cost until the invoice showed up.
That's not a pricing problem. It's a bank without a ledger.
https://t.co/itQaGgXTtL
An agent stuck in a retry loop can burn a customer's entire monthly AI budget in an hour.
Most teams' fix: pad the limits above what customers paid for, and hope. That's not governance.