Learning Through Examples

Few-shot learning is one of the most powerful techniques in prompt engineering. Instead of just telling the model what to do, you show it examples of the desired behavior. This dramatically improves output quality and consistency.

Few-Shot Learning Basics

The concept is simple: provide the model with …

Understanding Prompt Structure

When working with LangChain, understanding how to structure prompts is fundamental to getting consistent, high-quality outputs from language models. A well-structured prompt is the difference between vague responses and precise, actionable results.

Anatomy of a Prompt

Every effective prompt has three core components that work together:

1 …

Why Prompt Hygiene Matters

Writing prompts is easy. Writing good prompts that consistently produce reliable results is hard. Prompt hygiene refers to the practices and patterns that make your prompts maintainable, debuggable, and effective over time.

Poor prompt hygiene leads to: - Inconsistent outputs - Difficult debugging - Hard-to-maintain code - Wasted tokens and …