The Testing Problem Nobody Prepared You For: Software QA is built on a simple premise: correct behavior is stable. You write a test, it passes, and if the test fails tomorrow, you know something broke. This doesn't work for data analytics agents.

Why Your Agent Observability Stack Is Incomplete: Every AI engineering team knows they need observability. They instrument their LLM calls, track token usage, log prompts and completions.

The Problem Everyone Underestimates: When engineering teams build their first AI agent, they typically think it's a harder version of building a microservice. Add some LLM calls, implement retry logic, maybe throw in RAG, ship it. They're wrong, but they don't know it yet.

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