Alex Litvinov
Picked up a Master's in Bioengineering and Bioinformatics, followed by 15+ years as a backend/database engineer in Healthcare and Science domain. Currently a Data Engineer at Manychat, bridging platform data engineering with ML/AI.
Session
At Manychat, we built an analytics agent on top of Claude Code that lets non-data specialist teammates ask data questions in plain English. You type /ask followed by a question; the agent clarifies it if needed, routes it to the right business domain, queries curated data marts, and returns the numbers plus everything an analyst needs to verify them.
Connecting an agent to a data warehouse is easy, but without the right context, it can provide answers that seem plausible rather than correct. And a confidently wrong number doesn’t stay in the terminal - it ends up in someone’s all-hands deck.
This talk covers the layer that closes that gap: how we decide what the agent sees, how we keep that context from going stale, how the agent determines how much confidence to place in its own answer, and how we detect when a change quietly breaks something.