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Building Reliable Systems with Large Language Models

7 chapters · 32 lessons

1. 1. Understanding LLM Failure Modes in Production

   4 lessons

   Learn how and why LLMs fail in professional settings, from hallucination to overconfident formatting.

2. 2. Retrieval-Augmented Generation Architecture

   5 lessons

   Build systems that ground LLM outputs in verified external sources at query time.

3. 3. Tool Use and Function Calling Patterns

   5 lessons

   Enable models to call calculators, databases, APIs, and code interpreters for reliable computation.

4. 4. Human-in-the-Loop Workflow Design

   4 lessons

   Architect systems where expert review, escalation rules, and oversight ensure output quality.

5. 5. Evaluation Frameworks for LLM Systems

   5 lessons

   Test reliability, measure failure rates, and validate outputs across edge cases and real scenarios.

6. 6. Prompt Engineering for Reliability

   4 lessons

   Write prompts that reduce ambiguity, constrain outputs, and improve consistency in production.

7. 7. Production Deployment and Operational Patterns

   5 lessons

   Deploy LLM systems with logging, versioning, cost controls, and incident response protocols.