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Loop Engineering with Claude

This course teaches you to design and implement robust feedback loops for Claude, using techniques like Chain-of-Thought and tool use. You will learn to build a self-correcting agent that refines its outputs based on predefined criteria, significantly improving Claude's reliability and performance in complex tasks.

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Lessons
8
Price
Free
Course Curriculum

What you'll learn

4 Modules
8 Lessons
~40m total
01
01
Module 01
Foundations of Feedback Loops
This module introduces the core concepts of feedback loops in AI agents, explaining why they are crucial for robust Claude applications. We will cover the basic architecture of self-correcting systems and how Chain-of-Thought prompting facilitates internal reflection.
2 lessons10 min
0%
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02
02
Module 02
Implementing Advanced Loop Engineering
This module delves into advanced techniques for building sophisticated feedback loops with Claude, including integrating external tools and establishing robust evaluation criteria. You will learn to build a complete self-correcting agent that interacts with its environment.
2 lessons10 min🔒 Locked
0%
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03
03
Module 03
Foundations of Loop Engineering
This module introduces the core concepts of loop engineering for AI agents, explaining why iterative processes are crucial for complex task completion. We will cover the fundamental components of an AI loop and how Claude fits into this architecture, focusing on prompt chaining and basic feedback mechanisms.
2 lessons10 min🔒 Locked
0%
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04
04
Module 04
Advanced Self-Correction
This module delves into sophisticated techniques for building self-correcting AI loops with Claude. We will explore external tool integration, robust error handling, and dynamic adaptation strategies to create highly resilient and intelligent agents. Learners will apply these methods to build agents that can autonomously improve their performance.
2 lessons10 min🔒 Locked
0%
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Loop Engineering with Claude
23/06/2026
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