Your AI Agent Is Burning Money And You Don't Even Know It

The Black Box Problem Is Ruining Your ROI

Most AI agents run like black boxes. You send a request. You get a result. You hope it's right. Traditional monitoring tools don't help because they were built for predictable systems, not agents that can hallucinate, click the wrong button, or get stuck in infinite loops. People are losing thousands of dollars every month to AI agents that appear to work but silently fail. One Reddit user described their AI agent horror story: what was supposed to be a three-day automation turned into a week of debugging, broken workflows, and lost trust. That's not an edge case. That's the default for most deployments. You can't fix what you can't see. If your observability stack doesn't show you exactly what your AI computer use agent did and why, you're flying blind.

Why Traditional Observability Doesn't Work for AI Agents

• ●It focuses on latency and throughput, not correctness
• ●It doesn't capture what the agent clicked, typed, or saw on screen
• ●It treats LLM outputs as facts instead of probabilistic guesses
• ●It can't trace a failure back to a specific agent step in the workflow

The Cursor War Is Just the Start of Your Problems

OpenAI and Anthropic are fighting a 'cursor war' to see who can control computers better. Their computer-use agents are getting good at clicking buttons and filling forms. That's not the hard part. The hard part is knowing what they should click, why they made that choice, and what to do when they're wrong. Anthropic shipped computer use in October 2024. OpenAI followed with Operator. Both are impressive demos. But both are also opaque. You can't see their reasoning. You can't replay their actions. You can't intervene when they go off the rails. That's why observability isn't optional. It's the difference between an agent that saves you money and one that costs you money.

You Need Computer Use Observability That Actually Works

Good AI agent monitoring needs to show you exactly what happened and why. You need to see the screen state before and after each action. You need to replay the agent's steps to understand where it went wrong. You need to trace failures back to specific prompts, model choices, or tool calls. Most tools try to bolt this on top of existing systems. That's a mistake. You need something built for computer-use agents from the ground up, not something that was designed for traditional APIs and then stretched to cover agentic workflows. You also need to know how much your agent is actually saving you. Is it automating a task or just replacing a human with a more expensive version that still needs constant supervision?

Why Coasty Is The Only Computer Use Agent You Should Trust

That's why Coasty exists. Coasty is the #1 computer use AI agent, ranked #1 on OSWorld at 85.6% on our in-house model with public results and 82.81% independently verified on the official OSWorld leaderboard. That's higher than every published computer use benchmark. Coasty doesn't just claim high accuracy. It proves it. It controls real desktops, browsers, and terminals. It can run in parallel on cloud VMs or your own infrastructure. It comes with a free tier and supports BYOK so you can keep your data where you want it. But the real difference is observability. Coasty gives you visibility into every action it takes. You can see what it saw, what it chose, and why. You can intervene when it's wrong. You can optimize prompts and workflows based on real performance data.