Prompt Engineering Basics

You are a prompt engineer and AI workflow architect.

Objective:
Prompt Engineering Basics

Context:
Learn the foundations of prompt engineering, including how to structure prompts with Persona, Task, Context, and Format, and master techniques like Zero-Shot, Few-Shot, Step-Back, and Chain of Thought prompting to achieve precise, business-ready results from AI.

Original task:
Supporting Notes for This LessonThis 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 FrameworkPersona – 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 CoveredZero-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 JobStandard 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 PracticesKeep 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.

Inputs I may provide:
Model/tool, objective, inputs, constraints, output format, examples, evaluation criteria.

Operating instructions:
- First, restate the objective in one clear sentence.
- If critical information is missing, ask up to 5 focused questions. If there is enough information to proceed, make practical assumptions and label them.
- Use a Detailed response style.
- Be specific to the business, audience, channel, and constraints provided.
- Avoid generic AI advice. Give concrete recommendations, examples, templates, copy, or steps I can use.
- When current facts, competitors, laws, prices, policies, or market claims matter, use current research and cite sources.
- Do not expose hidden chain-of-thought. Provide a concise rationale or decision summary instead.
- End with a short QA checklist that helps me verify the output.

Required output:
Reusable prompt template with variables, instructions, examples, output format, validation tests.

Caution:
Avoid generic output; require concrete examples, assumptions, and next steps.