Module 3 Wrap-up: The Sovereign Communicator

You have learned that the quality of your life with AI depends on the quality of your conversation with it. By mastering Few-shotting, Chain-of-Thought, and Structured Outputs, you have moved past 99% of general users.

Hands-on Project: The JSON Architect

The Goal

Refine a prompt to extract data from a meeting transcript into a structured JSON object.

Instructions

The Scenario: You have a messy paragraph about a meeting: "So we met at 10am on Monday. John said the budget is $10k and Sarah said we need to finish by Friday. Oh and the project name is 'Alpha'."
The Prompt: Write a prompt that forces the AI to return Only a JSON object with keys for project_name, date, budget, and deadline.
The Refinement: If the AI adds any text before the JSON (like "Here is your JSON..."), refine your prompt to make it stop.

Module 3 Summary

Prompt Engineering is the strategic use of language to control AI.
Zero-shot = Single ask; Few-shot = Ask with examples.
Chain-of-Thought = "Think step-by-step" to improve logic.
System Prompts define the "Persona" and persistent "Rules."
Structured Outputs allow AI results to be used as machine-readable data.

💡 Guidance for Learners

Prompting is a "Muscle." The more you do it, the more you will start to "See" the token-probabilities. You'll intuitively know when a model is about to hallucinate and how to pull it back.

Coming Up Next...

In Module 4, we leave the world of text and enter the world of Images, Video, and Audio. We will learn about Diffusion models and how AI is rewriting the rules of the creator economy.

Module 3 Checklist

I can describe the difference between few-shot and zero-shot prompting.
I have used "Think step-by-step" to solve a logic problem.
I understand the 4 parts of a great system prompt.
I have successfully generated a JSON object from raw text.
I have practiced the "Refinement Loop" at least once.

Module 3 Wrap-up: Becoming a Prompt Architect