Why it matters
Covers agents for pipeline generation, failure investigation, data quality monitoring, testing and documentation, plus the guardrails needed to scale that safely. Useful for data teams adopting agents in production.
The tokenmaxxing angle
Data pipelines are repetitive, high-volume work that is easy to over-automate with large models. An attendee could ask how Robinhood decides which pipeline tasks justify an agent run versus a cheaper deterministic job.
From the organizers
Run by the USF Data Science & AI Speaker Series (10,525 members) at 101 Howard St, Friday 12:30 pm PT. Speaker Deep Patel is a Staff Data Engineer at Robinhood; Meetup RSVP closes the morning of the event.