Module 2
Prompt Engineering Mastery
The single highest-leverage skill in the AI age
Lessons
PremiumStart the 7-day trial to open this module.
You can still review the module outcomes, capstone, examples, and resources before upgrading.
2.1
Anatomy of a Perfect Prompt
Locked30 min
2.2
Chain-of-Thought Prompting
Locked35 min
2.3
Few-Shot & Zero-Shot Mastery
Locked40 min
2.4
System Prompts & Personas
Locked45 min
2.5
Prompt Chaining & Pipelines
Locked50 min
2.6
Structured Output Engineering
Locked35 min
2.7
Meta-Prompting
Locked40 min
2.8
Prompt Security
Locked30 min
Expert Lens
Founder
Think like a founder: what user pain, distribution channel, pricing, and retention loop does this AI capability unlock?
Systems
Think like a first-principles systems builder: separate demos from durable products, and measure the bottleneck the model actually removes.
Infrastructure
Think like an AI infrastructure leader: account for data, latency, cost, reliability, evaluation, and deployment constraints before scaling.
Objectives
- Master all 8 major prompting frameworks
- Build a professional reusable prompt library
- Engineer prompts for consistent, production-quality output
- Design system prompts and AI personas for any application
Capstone
Professional Prompt Library
Build a library of 60 production-ready prompts across 12 business categories with documented variables, use cases, and quality benchmarks.
A living Notion/Airtable prompt library you'll use and expand throughout your career.
Real Examples
- A solo operator replaces repetitive research, drafting, and QA loops with an AI-assisted workflow while preserving human review.
- A startup validates an AI feature by measuring time saved, accuracy, user retention, and willingness to pay before building a platform.
- An enterprise team moves from chatbot demo to governed internal assistant with retrieval, permissions, observability, and escalation.
Mastery Checks
- Write prompts that specify role, context, task, constraints, output format, and evaluation criteria.
- Run the same prompt across at least two model families and document behavior differences.
- Turn a successful prompt into a reusable template with variables and test cases.