Prompt Engineering

Prompt engineering is the practice of writing the input that makes an LLM do what you need — reliably, not just once. For an engineer it is not “talking nicely to the AI.” It’s interface design for a probabilistic system: precise specs, explicit constraints, and structured I/O.

The production mindset

A prompt that works in the playground is a prototype. A production prompt is versioned, tested against an evaluation set, and built to fail safely. The techniques here are about getting from the first to the second.

In this section

Core Techniques Prompt anatomy, system prompts, zero- and few-shot prompting, and chain-of-thought reasoning.

Structured & Reliable Prompts Structured output, JSON schemas, delimiters, and making prompts behave consistently.

Advanced Patterns Decomposition, self-consistency, prompt chaining, injection defense, and prompt management.

What you’ll be able to do

Write prompts that produce consistent, machine-parseable output; choose the right technique for a task; and manage prompts as tested, versioned engineering artifacts.

Prerequisites

LLM Engineering. This section pairs closely with RAG and AI Agents.