Behind the build:  How Ticketmaster is scaling an AI agent (and how you can too)
WEBINAR

Behind the build: How Ticketmaster is scaling an AI agent (and how you can too)

Behind the build: How Ticketmaster is scaling an AI agent (and how you can too)

Building an AI agent has become the easy part. Knowing whether it's actually delivering value, and convincing leadership it is, is where most teams now get stuck.

In this webinar, Ticketmaster PM Brian Muehlenkamp breaks down what building and scaling an AI agent looks like once you move past digging through audit logs and start measuring with Agent Analytics. He'll walk through the insights that took him from a cautious 30-person pilot to a larger employee rollout faster than expected—–plus how he uses Pendo's MCP server to continuously flow agent data directly into Claude Code for automated improvements.

Whether you're pre-launch or already in production, you'll leave with a practical framework for measuring agent impact and scaling with confidence.

You'll learn how to:

  1. Find out what your users are actually asking your agent (and why it’s probably not what you built it for)
  2. Catch and diagnose agent issues at scale before they hurt adoption
  3. Know exactly which metrics to show leadership to get buy-in for your next rollout phase

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