Data Context Layer with Bruin
About the webinar
A live, technical session streamed on Youtube & LinkedIn:
https://www.linkedin.com/events/7502993550553288704
An AI agent needs context to work with your data. We walk through how to build that context, step by step, and how to keep it up to date.
We use Bruin for the examples and show snippets of code along the way, but the same approach applies to any tool or platform.
It works for a data engineering, analytics engineering, or data analyst agent.
What we will cover
The layers of context an agent reads: repo, pipeline, asset, semantic, and glossary.
Tools that give the agent more context and let it take action: skills, MCP, and CLI.
How to stop the layers from clashing, then join them into one.
How to build it and keep it fresh: start with AI, improve it, test it locally, let real users try it, then let it update on its own.
Agenda
Intro ~5 min
Layers of context ~10 min
Types of tools ~5 min
Build the context ~15 min
Make it self-heal and improve ~10 min
Final thoughts and Q&A ~15 min
Join our Slack for free learning material and resources:
https://join.slack.com/t/bruindatacommunity/shared_invite/zt-3cymzktqu-bvFxPGyQHpvi~dok_W0L3w