Loop Engineering is a practical, hands-on course that teaches the engineering principles behind modern autonomous AI systems. Instead of stopping at prompt engineering, you’ll learn the complete four-layer AI engineering stack—Prompt, Context, Harness, and Loop and understand how these layers work together to build reliable AI agents. Throughout the course, you’ll build a real AI agent using Python and Claude Code while learning the ReAct reasoning pattern, context management, verification, guardrails, stopping conditions, and essential AI safety practices required for production-ready AI systems.
This course focuses on practical engineering rather than theory. You’ll watch a complete end-to-end live build, understand why autonomous agents fail, and learn how to design AI systems that can reason, act, verify, and improve without requiring constant human intervention.
What you’ll learn:
- Build autonomous AI agents using Claude Code
- Understand Prompt Engineering, Context Engineering, Harness Engineering, and Loop Engineering
- Learn the ReAct (Reason, Act, Observe, Repeat) agent pattern
- Build reliable AI workflows with verification and stopping conditions
- Manage context efficiently and prevent context rot
- Implement guardrails, budget controls, sandboxing, and prompt injection protection
