Building Smarter Analytics: From Prompt Engineering to Agent Systems

​What you'll learn

• ​Learn how to use Agent Skills to create business metrics directly from raw data sources

• ​See how dbt agent skills enforce analytics engineering best practices inside AI workflows

• ​Watch a demo that goes from a business question to a working metric without manual pipeline setup

​Why this matters

​Creating a new business metric shouldn't require a data engineering project. But today it usually does. Someone requests a metric, a data engineer builds a model, an analytics engineer creates the logic, and weeks later, the number shows up in a dashboard.

​Agent Skills collapse that process. Instead of building pipeline infrastructure by hand, the AI spins it up on the fly. In this session, you'll see how to go from a business question to a working metric without the usual overhead.

​Who you'll learn from

​Bijil Subhash is a fractional data engineer with 5+ years of experience helping enterprises and startups make better decisions with their data. He has partnered with teams across finance, HR, retail, energy, and marketing to build data platforms and lay the foundations that make analytics and AI work in practice. He believes no AI strategy succeeds without solid data foundations underneath it.