Your AI Agent Is a Black Hole of Costs and Nobody's Watching

What They're Tracking vs. What Matters

Most observability tools track the wrong things. You'll see latency and token counts. You won't see that an agent deleted a production database. You won't see that it filled a customer's inbox with spam. You won't see that it hallucinated credentials and logged them in plain text. The tools track the inputs and outputs. They ignore the state changes. They miss the side effects. That's why you get horror stories like the United Healthcare AI with a 90% error rate or the McDonald's hiring bot that used '123456' as an admin password. Those failures weren't invisible. They were just not being monitored in the right way.

The Hidden Cost of Failed Tool Calls

• ●One Fortune 500 company spent $2.3M in 2025 fixing tool call failures that should have been caught in monitoring.
• ●Agents making 15+ failed tool calls per hour mean your costs are 3x what they should be.
• ●Most companies don't track 'tool success rate' as a core metric. They track 'agent uptime.'
• ●A single undetected tool failure can cascade into data corruption, security breaches, or customer churn.

Why Traditional Monitoring Doesn't Work for Computer Use

Traditional monitoring is built for structured data. APIs. HTTP requests. Databases. Computer use agents operate in unstructured environments. They click buttons. They fill forms. They navigate complex UIs. They struggle with dynamically changing layouts. They get confused by CAPTCHAs. They hallucinate button labels. A dashboard that shows 'HTTP 200 OK' doesn't tell you that your agent clicked the wrong button and submitted a customer's credit card number to the wrong endpoint. Traditional tools also miss the human-in-the-loop signals. When does an agent get stuck? When does it need a human intervention? Most companies have no process to detect and respond to those moments.

Monitoring Computer Use Agents Requires a Different Mindset

• ●Track step-by-step actions. Clicks, form fills, file reads, API calls.
• ●Monitor state changes. What data was updated? Where did it go?
• ●Track semantic intent. Did the agent actually accomplish what it thought it did?
• ●Set guardrails for dangerous actions. Deleting files, sending emails, modifying production data.

Why Coasty Exists (and Why Your Current Stack Is Failing You)

Most observability tools were built for chatbots. They track prompts and responses. They ignore the fact that Coasty controls real desktops, browsers, and terminals. It sees what the agent sees. It knows which buttons were clicked. It knows which files were opened. It knows which APIs were called. Coasty's computer use agent is different because its observability is built into the agent itself. You get real-time visibility into every action without building custom integrations or stitching together disparate tools. It works with desktop apps, cloud VMs, and agent swarms running in parallel. You can monitor multiple agents across environments from a single dashboard. You can set guardrails, review actions, and intervene when needed. This isn't an afterthought. It's how Coasty handles 82% OSWorld benchmarks and outperforms every competitor. Other tools might give you data. Coasty gives you control.