You know that feeling when you finally want to build something with AI agents but have no clue where to start? You've got OpenAI docs open, three conflicting tutorials in tabs, and a vague sense that you're missing something critical. Yeah, we've all been there. The thing is, setting up an agentic AI playground isn't actually complicated—but nobody talks about the right way to do it. Most guides skip over the infrastructure part and jump straight to "write your first agent." That's backwards. You need a solid foundation first, and that foundation is monitoring and observability from day one. Why Your Playground Needs Monitoring Here's the harsh truth: agents fail silently. An LLM might take an unexpected path through your code, retry logic might kick in unexpectedly, or your token counters could go haywire. Without visibility, you're debugging in the dark. This is why tools like ClawPulse exist—they let you see exactly what your agents are doing in real-time.…