How to Track AI Usage Without Losing Revenue (Complete Guide)

Ciroandrea Posted on May 25 How to Track AI Usage Without Losing Revenue (Complete Guide) # ai # saas # systemdesign # tutorial Most AI products eventually run into the same problem: Tracking usage sounds simple. Until it isn't. At first, all you need is a counter. A request comes in. You decrement a credit. You process the request. Done. Or at least that's what most teams think. As usage grows, things start breaking: duplicate requests retries race conditions timeout failures inconsistent balances billing mismatches And suddenly a simple counter becomes a revenue problem. The Naive Implementation Most products start with something similar to this: if ( credits > 0 ) { credits -- ; executeRequest (); } Enter fullscreen mode Exit fullscreen mode Looks harmless. The user has credits. A request arrives. A credit is consumed. The request is executed. Simple. The problem is that real-world systems are rarely this simple. What Starts Breaking The moment real users start using your product at scale, unexpected situations appear. Retries Networks fail. Browsers retry requests. Mobile apps resend actions. Background jobs run again. A single user action can generate multiple identical requests. Without protection, credits may be consumed multiple times. Race Conditions Imagine a user has one credit remaining. Two requests arrive at exactly the same time. Both processes check the balance. Both see one available credit. Both proceed. Now the user consumed two requests while paying for one. Or worse: Your balance becomes negative. Partial Failures One of the most dangerous situations looks like this: Consume credit ↓ Call AI provider ↓ Timeout Enter fullscreen mode Exit fullscreen mode Did the AI provider process the request? Maybe. Did the user receive the result? Maybe not. Should you refund the credit? Should you charge again? These situations become surprisingly difficult to handle consistently. How Revenue Leaks Happen Most revenue leaks don't come from pricing mistakes.