Designing Reliable AI Agents: Architecture, Control, and Evaluation
Design agents that use narrow tools, preserve durable state, stop on clear conditions, and act only within granted authority. The course covers retries, approvals, sandboxing, evaluation, incident stops, and the cases where a fixed workflow is the better design.
- Sections
- 10
- Lessons
- 49
- Study time
- 29 Hours
- Learner rating
- New course
Your route
Course map
Move through the sections in order. Start with any open previews, then continue with the premium lessons when you are ready.
- 1
Agent Foundations, Architecture, and Guardrails
6 lessons Free preview
- 2
Conversational Recommender Agents
5 lessons Premium
- 3
Autonomous Reward Design with Eureka
7 lessons Premium
- 4
Reward Agent Loops, Reflection, and Control
5 lessons Premium
- 5
Smart Parking Agent System
1 lesson Premium
- 6
Pipeline Design and Research Agents
5 lessons Premium
- 7
Multimodal Web Agents
9 lessons Premium
- 8
Multimodal Generation Agents
4 lessons Premium
- 9
Healthcare and Personal Agents
2 lessons Premium
- 10
Agent System Synthesis, Frameworks, and Tools
5 lessons Premium
Curriculum
Course content
Open a section to preview its lessons.
- 1.1Introduction to AI Agents17 min
- 1.2Agent Architecture: Core Agent Components13 min
- 1.3Agent Architecture: Components Interaction and Agent Memory13 min
- 1.4Structuring Agent Behavior: Agent Orchestration Patterns16 min
- 1.5Building Trustworthy Agents: Guardrails and Human Oversight21 min
- 1.6Key Challenges and Design Strategies in Agentic AI Systems18 min
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