Prompt Engineering Basics
Supporting Notes for This Lesson
This video introduces the core foundations of prompt engineering—the skill of designing clear, structured instructions that guide AI to deliver business-ready results.
Key Takeaways:
Stop treating AI like Google. Asking vague questions leads to vague answers.
Think like a director, not just a user. Your job is to instruct, not just ask.
The PTCF Framework
Persona – Assign a role to the AI (e.g., “You are a senior marketing manager…”).
Task – Use clear action verbs (e.g., create, summarize, rewrite, analyze).
Context – Add the background info the AI needs (most prompts fail here).
Format – Tell the AI exactly how you want the response (e.g., bullet points, table).
Prompting Techniques Covered
Zero-Shot Prompting: No examples needed—just a clear, structured prompt.
Few-Shot Prompting: Include one or more examples to “show” the AI what good looks like.
Step-Back Prompting: Start broad to help the AI gather relevant knowledge before narrowing in.
Chain of Thought (CoT): Add phrases like “Let’s think step by step” to improve logic and reasoning.
Choosing the Right AI for the Job
Standard Models – Fast, great for simple tasks like summaries or rewrites.
Reasoning Models – Better for multi-step problems and strategic tasks.
Deep Research Models – Use for high-stakes, in-depth analysis (trade speed for depth).
Best Practices
Keep prompts clear and simple—if it’s confusing to you, it’s confusing to the AI.
Be specific about the output (length, style, format).
Use instructions over constraints—tell the AI what to do, not just what to avoid.
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