Data Context Layer with Bruin

​About the webinar

​A live, technical session streamed on 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