AI Agent Architecture
Build agents that actually work. Not toy demos.
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About This Course
Most AI agent tutorials build demos that break in production. This course teaches production agent patterns — planning loops, tool orchestration, error recovery, human-in-the-loop checkpoints, and the architecture that makes agents reliable. Based on real agent systems running in production.
What You'll Walk Away With
✓Build AI agents that actually work in production — not toy demos
✓Implement planning loops and the ReAct pattern for multi-step reasoning
✓Orchestrate tools across complex workflows with error recovery
✓Design human-in-the-loop checkpoints that prevent costly mistakes
✓Evaluate agent quality with measurable metrics
✓Control costs with token budgets and intelligent caching strategies
What You'll Learn
01Agent vs Chatbot — The Architecture Difference
02Planning Loops & ReAct Pattern
03Tool Orchestration — Multi-Step Workflows
04Error Recovery & Graceful Degradation
05Human-in-the-Loop Checkpoints
06Sub-Agent Delegation Patterns
07Memory — Short-term, Long-term, Episodic
08Evaluation — How to Measure Agent Quality
09Cost Control — Token Budgets & Caching
10Case Study: Production Agent System
What's Included
✓Agent architecture templates
✓Tool orchestration framework
✓Evaluation harness
✓Cost monitoring dashboard