Debugging LLM-Based Features

Program Overview

What This Program Covers

Debugging AI features is fundamentally different from debugging traditional software — the failures are probabilistic, the outputs are variable, and the root causes are often buried in prompt design, context management, or model behavior. This program teaches engineers systematic approaches to debugging LLM-based features in production environments.

What You'll Learn

1. 1Apply systematic debugging approaches to non-deterministic AI systems
2. 2Diagnose prompt-related issues including hallucination and instruction following failures
3. 3Debug context management problems in production LLM applications
4. 4Implement logging and observability for LLM features
5. 5Use evaluation frameworks to catch regressions in AI feature quality
6. 6Debug tool use and function calling failures
7. 7Build reproducible test cases for intermittent AI failures