What It Takes to Run Agents on Billions of Messages: Kevin Stanton, Sprout Social

Kevin Stanton has spent 13 years at Sprout Social, most recently running infrastructure for a platform that processes billions of social posts. When generative AI emerged, their team saw an opportunity to solve one of their hardest problems: helping customers make sense of massive amounts of unstructured social data.

Now Kevin is building Trellis, Sprout's AI agent for social listening and competitive intelligence. In this conversation, he shares what it's looked like to shift an engineering team toward building agents — and the practical lessons they've learned shipping to thousands of customers.

We cover details like why MCP felt more natural than RAG for their architecture, how they use chat as a strategy for seeding eval datasets, when to let agents reason versus when to collapse tools and write deterministic code, and why they pulled evals out of CI/CD after learning the hard way how non-deterministic tests can break things.

Links from our conversation:

• Sprout Social: https://sproutsocial.com
• Sprout Social Insights Blog: https://sproutsocial.com/insights
• Trellis: https://sproutsocial.com/insights/press/sprout-social-unveils-trellis-its-ai-agent-that-turns-social-data-into-instant-enterprise-intelligence/
• Find Kevin on LinkedIn: https://www.linkedin.com/in/kevinstanton/