These two things sound similar but solve completely different problems. In this clip from our Superweek session, Jon Su breaks down the distinction:
- Agentic Observability (think LangFuse, LangChain): looks at the internal workings of an agent. Prompts, responses, token usage, latency. Built for ML engineers to improve model performance.
- Agentic Analytics: looks at customer intent. Why is a user interacting with your agent? What are they trying to achieve? What does that mean for your business?
The analogy: server-side logs were fine until we needed more granularity, and that's what sparked the explosion of modern web analytics. Agentic observability is the server log. Agentic analytics is what comes next.
🎥 Watch the full session: https://snowplow.io/events/track-ai-agents-in-2026