Agentic Design Patterns
Overview
Agentic Design Patterns is an immersive three-day workshop that explores the essential design patterns that underpin modern agentic systems—AI agents capable of reasoning, planning, and collaborating dynamically. Participants begin with foundational concepts, learning to construct robust agent architectures through the Pipeline, Routing, and Parallelization patterns. Day-one sessions focus on structuring agent workflows for efficiency, adaptability, and scalability through guided hands-on labs.
Building on this base, the course advances into reflection, tool use, planning, and multi-agent collaboration patterns, enabling participants to create agents that plan intelligently, use external tools effectively, and coordinate with other agents to achieve complex objectives. The final day explores higher- order design strategies, including memory management, goal monitoring, exception recovery, and human-in-the-loop integration. Upon completion, participants will have both the conceptual framework and the applied skills to design and implement adaptable, pattern-driven AI agent systems.
Duration
3 Days
Who Should Take This Course
Audience
Developers, Data/DevOps/AIMLOps Engineers, Technical Managers and Analysts.
Prerequisites
Intermediate programming skills in Python and some prior experience with AI development.
Why You Should Take This Course
Upon completing Agent Driven SDLC, participants will be able to:
- Design & implement agentic solutions using design patterns in Python-based agent frameworks
- Gain experience implementing a wide range of agentic patterns
- Select and apply appropriate patterns to real-world agent scenarios
- Understand multi-pattern strategies and use cases
- Work with Langchain/graph, Crew AI, OpenAI, Google ADK and other agent frameworks