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Designing Agentic AI Systems for Professional Workflows

7 chapters · 32 lessons

1. 1. Agent Architecture Fundamentals

   4 lessons

   Understand the core components of agentic systems and how they differ from single-turn LLM applications.

2. 2. Tool Integration and Function Calling

   5 lessons

   Connect agents to external systems, APIs, and specialized tools with structured calling patterns.

3. 3. Retrieval-Augmented Agent Design

   4 lessons

   Ground agent decisions in organizational knowledge using vector search and retrieval patterns.

4. 4. Evaluation and Quality Control

   5 lessons

   Build feedback loops that assess agent outputs and decide when to continue, revise, or escalate.

5. 5. Workflow Orchestration Patterns

   4 lessons

   Coordinate multi-step processes across systems while maintaining reliability and traceability.

6. 6. Domain-Specific Agent Applications

   5 lessons

   Apply agent patterns to engineering, software development, operations, and knowledge work scenarios.

7. 7. Production Deployment and Safety

   5 lessons

   Deploy agents reliably with monitoring, guardrails, and strategies for managing risk in live systems.