Agentic AI need more than a capable model. They need established patterns that govern agentic behavior, pipelines that manage data and knowledge, and reliable tools that make each answer useful and traceable.
Over four hours, we move from the building blocks of Agentic AI through the front-end and back-end of the Enterprise AI stack. We will code along to build a working application, exploring retrieval, knowledge management, tools, pipelines, and logging as we go. You will leave with practical blueprints for extending the same approach to your own AI use cases.

Agentic Patterns e-book included
Register early to receive the 60-page e-book on Agentic Patterns, revised for Q1 2026. This practical reference helps connect the patterns covered in class to your own AI applications.
Building Blocks and Agentic Patterns
Established paradigms for building robust Agentic AI systems.
- Building Blocks of Agentic AI Systems.
- Six Agentic AI Patterns and when to apply them.
- Practical examples and case studies from enterprise AI implementations.
The Enterprise AI Implementation Blueprint
Grouping AI implementation into front-end and back-end phases.
- Backend: ingestion, retrieval, and knowledge management.
- Front-end: enterprise chatbots, AI Search, report generators, and more.
- Four Enterprise AI Implementation Models.
Engineering Practices and Code-Along
An inside-out approach to building enterprise AI applications.
- Four kinds of pipelines: initialization, trigger, periodic, and on-demand.
- Memory-capable, retrieval-augmented, and logged AI applications.
- AI servers, LLM-powered APIs, vectors, and databases.
- Build and extend a working Agentic AI application with guidance.






