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Designing AI Agent Workflows for Production Systems

7 chapters · 35 lessons

1. 1. Agent Architecture Fundamentals

   5 lessons

   Understand the core loop of planning, retrieval, tool use, checking, and state updates that distinguishes agents from chatbots.

2. 2. Retrieval and Context Systems

   5 lessons

   Build retrieval-augmented generation pipelines that ground agent decisions in relevant documents, code, and knowledge bases.

3. 3. Tool Integration and Execution

   5 lessons

   Design safe tool interfaces for agents to interact with APIs, terminals, databases, and external systems.

4. 4. Governance and Safety Controls

   5 lessons

   Implement monitoring, evaluation, permissions, and human oversight to prevent uncontrolled automation.

5. 5. Multi-Agent Orchestration

   5 lessons

   Coordinate specialized agents with task assignment, conflict prevention, and result aggregation strategies.

6. 6. Domain-Specific Agent Workflows

   5 lessons

   Apply agent patterns to software engineering, operations, data analysis, and security use cases.

7. 7. Production Deployment and Iteration

   5 lessons

   Deploy agent systems with monitoring, cost management, and continuous improvement based on real usage.