Your AI agent can already bankrupt you. You just haven't found the loop that does it yet.
Every agent framework shipping today optimizes for one thing: giving the model more autonomy, faster. Nobody's shipping the equivalent of a circuit breaker at the same pace. That gap is not theoretical — it's a single bad retry loop, a compromised prompt, or a bug with no backoff away from a five-figure bill with no clean record of what happened or why.
I got tired of that being someone's future incident report, so I built the layer that closes it: Valta — every AI agent gets its own wallet, a hard spending limit enforced before the call fires, and a cryptographically hash-chained audit trail that can't be edited after the fact. Not a monitor that notices you overspent. A gate that stops the call from happening at all.
I'm not asking you to trust that claim. Here's all of it, open source:
— the actual pattern: a pre-call spend gate + SHA-256 hash-chained audit log. Clone it, run the demo, watch a rogue agent get shut off mid-loop, verify the chain yourself. The README also names the one thing it doesn't solve yet (a concurrency race condition) instead of hiding it.
— the same spend gate exposed as MCP tools, so Claude Desktop, Cursor, or anything MCP-compatible can call it directly.
— a static analyzer that catches the exact bugs that cause runaway agent bills (missing backoff, unbounded loops, leaked token costs) before you ship them.
npx valta-leak ./src.The hosted version — valta.co — wires all of this into real wallets, real limits, and a dashboard, live now, free in beta.
Happy to go deep on any of the design decisions in the comments — including the ones I got wrong the first time.
The fact that you’re addressing the spend-control problem at the execution layer rather than just observing it makes the product distinction pretty clear. Curious how Valta has progressed since July — have you started seeing meaningful adoption from teams running agents in production?