Peter Werry

In this workshop we'll explore the importance of context engines in modern engineering workflows, and we'll look at why traditional RAG techniques are no longer enough to deliver the context agents need. We'll build a structured query engine that fills the gaps left by RAG, translating natural language into validated database queries over GitHub PR and Issue data. We'll implement schema-aware prompting, identity resolution, query validation, and error-driven retry loops, and you'll walk away with a working query engine for your GitHub repository.

Your agents are fast, capable, and completely context-blind. They generate code that compiles but doesn't reflect how your system actually works. You're likely already seeing the impact: ballooning token costs, longer review cycles, and inconsistent outputs. More MCPs, rules, and bigger context windows give agents access to information, but not understanding. In this session, we dissect how teams pulling ahead use a context engine to give agents exactly what they need for the task at hand. Includes a short demo showing the workflows a context engine can augment.