Full course coming soon

Designing Reliable Autonomous Agent Systems

7 chapters · 30 lessons

1. 1. Agent Architecture Fundamentals

   4 lessons

   Understand the control loop, tool integration, memory systems, and state management that differentiate agents from single-turn LLM applications.

2. 2. Policy and Permission Controls

   4 lessons

   Design authorization layers, approval workflows, and least-privilege access to limit agent actions to safe, intended operations.

3. 3. Defending Against Adversarial Inputs

   4 lessons

   Protect agents from prompt injection, goal hijacking, and malicious instructions embedded in documents, web pages, or user inputs.

4. 4. Sandboxing and Environment Isolation

   4 lessons

   Run agent actions in controlled environments to contain failures, prevent unintended side effects, and enable safe rollback.

5. 5. Observability and Audit Trails

   5 lessons

   Build logging, tracing, and monitoring systems to understand agent decisions, diagnose failures, and maintain accountability.

6. 6. Retrieval and Knowledge Integration

   4 lessons

   Connect agents to current, internal knowledge through retrieval-augmented generation and vector search to ground reasoning in facts.

7. 7. Evaluating Agent Reliability

   5 lessons

   Test agents on full workflows, measure success across multi-step tasks, and identify failure modes before production deployment.