Official Session Summary
Pulled from the live conference page.
Most AI agents never make it past the experiment phase, especially when they touch sensitive data and regulated workflows. At Pinterest, we built Agent Snowy, a LangGraph‑based agent that automates routine Snowflake data warehouse operational requests end‑to‑end, designed to cut median resolution time from hours down to minutes for supported flows. The agent takes requests from Slack and Jira ticket intake through to generating auditable SQL and GitHub PRs, all without direct write access to production. This talk will walk through how we wired LLMs, the Model Context Protocol (MCP), and existing CI/CD pipelines together, and the concrete guardrails we put in place to keep the system secure and compliant. Attendees will leave with a practical blueprint for turning their own routine operational tickets into safe, auditable agent workflows—without handing the keys to production over to an LLM.
Speaker Background
Quick context on the person or people on stage.
Senior Software Engineer at Pinterest, bringing an enterprise systems perspective on governed agents, infra safety, and operational automation.
Why This Slot Matters
A compact framing layer for navigating the conference.
This is one of the more substantive abstract-backed sessions on the schedule; worth opening when you need enough context to decide whether to stay in the room.