Your AI Agent Is Probably Watching You. Are You Watching It?
Your AI agent is clicking. It's typing. It's making decisions. And you probably don't know what it's doing half the time. A recent Splunk report shows organizations are deploying agentic AI faster than they can build monitoring for it. That's not innovation. That's a recipe for disaster.
Traditional Observability Fails Agentic AI
Enterprise monitoring tools like Datadog and Splunk were built for servers, not agents. They track CPU, memory, and network latency. They don't track whether your computer use agent actually solved the task, or whether it hallucinated a success. Arize and Grafana are trying to close this gap with AI-aware observability, but most tools still miss the fundamentals. They can't see inside the agent's decision loop. They can't replay actions. They can't tell you when an agent drifted from its intended behavior. The result is blind spots that stay hidden until something breaks.
The Blind Spot That Costs You Millions
- ●Agentic AI can perform actions without human approval in minutes.
- ●Traditional logging captures what was requested, not what was actually accomplished.
- ●Security teams can't audit agent actions without custom instrumentation.
- ●Most companies have no way to predict when an agent will fail.
Splunk's 2026 AI observability report found that 63% of organizations lack visibility into their agentic AI's decision-making process. That's not a small oversight. That's a massive risk.
Evaluations Are Not Observability
Anthropic and other vendors talk about evals like they solve the problem. Evals tell you how an agent performed on a test set. They don't tell you how it behaves in production at scale. An agent that passes 90% of evals can still fail in the wild because of edge cases, environment changes, or drifted behavior. Observability needs to be real-time, contextual, and tied to the actual actions your computer use agent takes. It needs to show you what the agent saw, what it chose, and what it actually accomplished.
What You're Missing With RPA And Old Automation
UiPath and other RPA platforms have been around for years. They excel at structured workflows, but they struggle with unstructured computer use tasks like navigating complex web interfaces or handling unexpected errors. Agentic automation promises to solve this, but without proper monitoring you're flying blind. You can't scale what you can't see. You can't fix what you can't detect. And you can't trust a system you don't understand.
Why Coasty Exists (And Why It Matters)
Coasty.ai is different because it's built for real computer use, not just API calls. It runs actual desktop and browser interactions, and it gives you full observability into every action. You can see what your agent clicked, what it typed, and what it accomplished. You can replay sessions to understand failures. You can set guardrails to keep agents within bounds. Coasty's 82% OSWorld benchmark score isn't just a number. It's proof that real computer use agents can succeed at complex tasks. And that success only matters if you can monitor and control them. Coasty gives you the visibility you need to deploy agents confidently at scale. Start with the free tier and bring your own keys. See what your agents are actually doing.
Don't deploy AI agents without visibility. That's how you lose data, money, or reputation. Get Coasty.ai and start watching your agents today.