The July Agent Analytics Playbook
A practical playbook for AI agent teams: measure production conversations, catch silent failures, prioritize fixes, and close the loop from user chat to shipped…
Building better AI agents.
Practical guides to monitoring, debugging, and improving agents in production.
Latest articles
1–12 of 117 articles
Stop Prompting From Opinions. Prompt From Production Conversations.
The best prompt improvements come from real conversations where users corrected, rephrased, abandoned, or revealed a new intent your agent missed.
The Agent Analytics Dashboard You Actually Need
Most AI agent dashboards show system health. Product teams also need intent, trust, friction, handoff, recovery, and improvement loop metrics.
Voice Agent Silence Is Usually Confusion, Not Patience
Voice agents fail when silence, interruptions, and hesitation are treated like clean turn-taking instead of signals of confusion, distrust, or task risk.
AI Sales Agents Fail Quietly During Qualification
AI sales agents do not only fail by losing leads. They fail by asking shallow questions, missing buying intent, and producing fake qualification confidence.
The First 5 Minutes of AI Agent Onboarding Matter More Than Your Demo
AI agent onboarding succeeds when users learn what to trust, what to delegate, and what the agent needs from them in the first few minutes.
Agent Memory Failures Show Up First in Production Conversations
AI agent memory failures rarely announce themselves as bugs. They show up as repeated questions, stale assumptions, weird personalization, and lost trust.
Failed Tool Calls Are a User Experience Problem
AI agent tool failures are not just backend errors. They shape user trust, conversation length, escalation, and whether the agent feels competent.
Session Replay for AI Agent Conversations
AI agent teams need the conversation version of session replay: not just what the user clicked, but where the agent lost intent, trust, or momentum.
Why Thumbs Down Feedback Is Not Enough for AI Agents
Thumbs down feedback catches only the users willing to complain. AI agent teams need conversation signals that reveal silent friction and quiet abandonment.
How AI Agents Can Repair Trust After a Bad Answer
AI agents will make mistakes in production. The question is whether the conversation repairs trust or makes the user supervise every future answer.
The Human Handoff Quality Score for AI Agents
Human handoff is not just whether an AI agent escalated. It is whether the handoff preserved context, trust, urgency, and user momentum.