AI Agent Observability Checklist for SaaS Builders: Stop Token Leaks Before They Become Incidents

AI agents rarely fail like normal web apps. They do not always crash, throw a clean 500, or point you to one broken line of code. They quietly loop, call the wrong tool, retrieve stale context, spend 8x tokens than expected, and still return an answer that looks confident enough to ship. That is why AI agent observability is becoming a core skill for SaaS builders in 2026. If your product uses LLM agents, RAG, tool calling, workflow automation, or multi-step assistants, basic logs are not enough. You need to see the full path from user request to model call to tool action to final output.