Ingesting Agent Traces with dlthub

​In this hands-on workshop, we'll show you how to stop flying blind on your AI agents. Using dltHub Pro we'll build a pipeline that ingests agent traces (e.g. tool calls, intermediate steps, token usage, and outcomes) and transforms them into structured, queryable data. ​From there, we'll turn that data into reports that actually tell you what your agents are doing, where they're failing, and how to make them better. ​You'll learn how to: * ​Capture and normalize agent traces into a consistent schema * ​Transform and model nested, variable-length trace data with dltHub Pro * ​Deploy your pipeline and build reports that surface real insights about agent performance ​ By the end, you'll have a working reporting layer for your AI agents, so you can debug faster, optimize smarter, and ship with confidence. ​About the speaker: Alena is a DevRel at dltHub. She builds and optimizes data pipelines, engages with dltHub community, and creates educational content to make data processing more accessible. This event is sponsored by dltHub **Join our Slack: https://datatalks.club/slack.html**