Module 01 · Introduction

What is Prompt Engineering?

The practice of designing inputs for AI language models to get reliable, useful outputs — in production, not just in a playground.

Beginner Friendly
~12 minutes
No coding required
Why It Matters

It's not just "talking to ChatGPT."

In production systems, prompts run thousands of times a day. A 5% failure rate means hundreds of broken outputs. Prompt engineering is the difference between a demo and a product.

🎯

Reliability at Scale

A prompt that works 95% of the time is broken at scale. Production prompts need to handle thousands of unpredictable inputs consistently.

🛠️

Prompts are Software

They need schemas, validation, failure handling, and retry logic — the same rigour you'd apply to any critical code path.

💰

Cost & Latency

Every token costs money and time. A poorly engineered prompt is expensive, slow, and still unreliable.

The Spectrum

Three levels of prompting.

Not all prompting is the same. There's a clear progression from casual chat to engineered production systems.

Level 1

Casual Prompting

Natural-language questions typed into ChatGPT. One input, one human reviewer. The bar is "interesting".

Level 2

Structured Prompting

Deliberate prompts with examples, roles, and format instructions. Repeatable across a small number of inputs.

Level 3

Production Engineering

Schemas, validation, retries, evaluation, monitoring. Prompts run thousands of times a day with no human in the loop.

This course takes you from Level 1 to Level 3 — the patterns, the failure modes, and the engineering mindset required to ship AI into real systems.

Course Overview

12 modules, three phases.

This course is structured to take you from first principles to production deployment.

📚

Foundations (1–3)

What prompt engineering is. How LLMs process prompts. Zero-shot and few-shot techniques — the building blocks.

🧠

Core Techniques (4–8)

Chain-of-thought, structured outputs, system prompts, retrieval-augmented prompting, and decomposition.

🏭

Production Skills (9–12)

Defensive prompting, evaluation, production patterns, and a cheat sheet for quick reference.

By the end of this course

You'll be able to design prompts that survive contact with real data, combine patterns to build robust AI features, and ship AI systems with confidence.

Recap

Prompt engineering is software engineering for LLMs.

It's how you make AI features reliable, predictable, and production-ready.

 Prompts are software, not conversation

 Production requires reliability at scale

 Three levels: casual, structured, production

 This course takes you to Level 3