Finance AI agents break differently. Here's the 6-check production framework I built.

I've been running AI agents in production for months. Most failure modes are universal — context window bloat, session drift, loop reinvention. But finance environments have a different failure taxonomy. A developer named Vic left a comment on my last article that crystallized it: he'd been running finance AI agents and let the nightly review fix 5-10 things at once. Cascading regressions every morning. "The stakes of a regression are higher in finance than most." He's right. And it made me think about the specific checks that matter for finance AI agents that don't matter as much for, say, a content scheduling agent or a customer support bot. Here's what I run. Why finance agents fail differently A customer support agent that hallucinates recommends the wrong product. Annoying. Recoverable. A finance agent that hallucinates executes the wrong trade, generates a compliant report with wrong numbers, or miscategorizes a transaction. Not recoverable. The failure modes cluster around three