Your AI Agent Is Burning Money While You Watch , Here's How to Fix It
Meta had a Sev-1 security incident caused by an AI agent. Only an anomaly. Not from hackers. From an AI that deleted an inbox due to a context window overflow. The incident lasted long enough that employees could access sensitive data. That is not a bug. That is a feature in a world where nobody is watching. You might think your AI agent is safe. You are wrong.
The Monitoring Gap Nobody Talks About
Most teams ship AI agents without a single line of observability code. They rely on generic logging and hope for the best. Datadog launched AI Agent Monitoring at DASH 2025. Honeycomb and New Relic added AI observability features. Open source tools like SigNoz and O2 AI Agent promise visibility. None of them understand what an AI agent actually does on a desktop. They trace requests and model responses. They do not see when an agent types the wrong command into a terminal. They do not see when an agent clicks the wrong button in a UI. AI agent monitoring needs to be built from the ground up for computer use systems not bolted on to existing infrastructure.
What Happens When Nobody Watches
- ●Meta's AI agent deleted an entire inbox due to a context window overflow. That is not a typo. An AI burned through its context limit and wiped data.
- ●A Reddit user reported their AI agents burned $500 a day doing nothing. They found 90 percent of these ghost runs before fancy observability tools.
- ●The OS-Harm benchmark shows computer use agents can be tricked into harmful actions. They can exfiltrate data or delete files without human oversight.
- ●A CIO article documented an AI coding tool that accidentally deleted production database data. The developer said it should never be possible.
AI agents are not autonomous workers. They are autonomous accidents waiting to happen. You need to watch every click. Every keystroke. Every API call.
Why Traditional Observability Fails
Standard monitoring tools track CPU, memory, and network traffic. They do not track whether an AI agent successfully completed a task. They do not track whether an agent hallucinated a button label. They do not track whether an agent followed your guardrails. This is why AI agent observability is a separate category. It needs to understand the full execution trace from prompt to final action. It needs to capture screenshots. It needs to record terminal output. It needs to flag anomalies in real time. Without this you are flying blind. You will not know when your AI is working correctly until it causes a disaster.
Why Coasty Exists
Coasty.ai is the only computer use agent built with observability in mind. We track every action our agents take on real desktops. We capture full execution traces including screenshots, terminal logs, and API calls. We flag anomalies instantly so you can intervene before damage happens. Our 82% OSWorld score is not just about raw performance. It is about reliable performance. When your AI agent can complete complex desktop tasks with that level of accuracy the only thing left to worry about is observability. Coasty gives you full visibility into every action. You can see what your agent is doing. You can stop it when it makes a mistake. You can optimize workflows based on real data not guesses.
Stop shipping AI agents into production without a way to watch them. Meta's Sev-1 incident should be your wake-up call. Your AI agent is not a black box. It is a tool you need to control. Sign up for the Coasty free tier today and see how computer use agents should be monitored and measured. Don't wait until your AI deletes your data. Check coasty.ai and take control of your AI agents.