AI agents look magical in demos and messy in production. This talk distills how we operationalize AI agents for day-to-day analytics. We cover schema discovery for stable interfaces, structured outputs for evaluation, human-in-the-loop gates for quality, and intentional context hooks for reproducibility. In 10 minutes I will show the shapes that work, the failure modes that recur, and the smallest set of practices that make agents dependable for data science.
Sponsor(s):
Bullfrog AI
Time:
10:50AM - 11:00AM
Session Type:
General Session (Presentation)