Ideas for building a better agent experience.
Practical guides to understanding your AI agent, the people using it, and the conversations that connect them.
What is AI agent analytics?
A practical guide to reading live conversations: uncovering what people came to do, where the agent lost them, and why traces and latency aren't enough.
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Conversation analytics for AI agents: turn-level forensics
Why surface sentiment misses failure: how to deconstruct multi-turn dialogue, isolate deciding turns, and turn chat logs into engineering priorities.
Why traditional product analytics breaks for AI agents
Why clickstream events, pageviews, and session counts cannot tell you whether someone got what they came for.
What is AI agent analytics?
A practical guide to reading live conversations: uncovering what people came to do, where the agent lost them, and why traces and latency aren't enough.
What is AI agent observability?
A practical guide to the traces, evaluations, metrics, silent failures, user outcomes and investigation workflow behind an observable production agent.
How to measure AI agent performance in production
A practical guide to user requests, task outcomes, friction, policy signals, and the conversations behind them.
Claude Managed Agents: what they are and how to run one
The agent, environment, session and events model, working API calls, permissions, cost, and how to tell whether a session finished the person’s task.