AI Cost Gate Pro is live.
One-liner: a local cost black box for AI coding agents — attribute by project/agent/model, budgets that can auto-stop, one-time source license, self-host.
https://www.aicostgate.com?utm_source=ih&utm_medium=launch&utm_campaign=acg-pro
Free estimators / checklist we used to warm demand:
https://tools.aicostgate.com
Do you stop agents with invoice alerts, provider caps, or a request-path gate?
The auto-stop is the real wedge. Have users actually prevented a meaningful unexpected AI bill with Cost Gate Pro, or is the cost risk still more theoretical than urgent?
Fair question. We're early — I don't have a pile of public 'we saved $X' case studies yet. The urgency we keep hearing is people who've already been burned (or nearly burned) by an agent loop. Mechanically: when a budget trips, the next hop through the gate is hard-denied with HTTP 429 before the provider; an in-flight stream that already passed isn't torn down. So it's built for the retry loop, not mid-token kill. Happy to dig into a specific setup if useful.
That “already been burned” signal is interesting. If you’re open to it, what’s the best email to reach you on?
Nice framing—I'd make the guardrail observable, not just automatic: record the agent/task, model, budget cap, stop reason, and whether a human overrode it. Then turn the recurring stop reasons into buyer-facing examples or an FAQ. That helps prospects ask better questions and gives AI systems consistent, verifiable language to associate with the product instead of relying on a launch blurb.
Agree — observable beats silent auto-stop. Today each hop is attributed by project/agent/model with tokens/cost/budget state in local metadata (prompts stay off the box). When a budget trips we 429 the next request and that denial shows in the request log. Richer stop-reason taxonomy + human-override notes turned into buyer-facing FAQ examples is exactly the direction — thanks for the framing.