M01: Prompting Foundations — Clear, Consistent Outputs

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Duration 13 m 27 s

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M01: Prompting Foundations — Clear, Consistent Outputs

About Course

Stop Guessing. Start Engineering.

Most professionals treat AI like a magic box—they type a vague wish and hope for a good result. That is not engineering; that is gambling. Ambiguity drives variance, and in a professional workflow, variance is risk.

Module 01 changes the operating model. We move from "Creative Writing" to "Architectural Specification." You will learn to build prompts that deliver predictable, checkable, and safe results every single time.

What We Will Build:

  • The RCC Framework: Master the four building blocks (Role, Context, Constraints, Guardrails) to eliminate hallucination risks.
  • Schema-First Inputs: Learn how to force the AI into "Data Entry Mode" to get checklists and tables instead of vague prose.
  • The "Chloe Method" Auto-Grader: Stop grading your own work. Build an automated "Quality Gate" that scores your prompts before you run them.

The Protocol:

This is not a theoretical lecture. It is a hands-on construction guide. By the end of this module, you will have a reusable Prompt Architecture Checklist and the ability to pass the "Intern Test" for any delegation task.

Prerequisites: None.
Est. Duration: 45 Minutes.

Course content

videoREAD ME FIRST: Configure Split Screen Browsers for LLM and NuSkool.AI Workflow0 s
videoVideo Walkthrough for Split Screen Browsers Setup2 m 30 s
videoLab 01 (Vague vs. RCC+G)0 s
videoLesson 1: Stop Guessing, Start Engineering57 s
videoLesson 2: The Formula: RCC + Guardrails2 m 29 s
videoLesson 3: The Schema Technique – Requesting Structure with RCC+G2 m 54 s
videoLesson 4: Psychology of the Model3 m 34 s
videoLab 02 (The Schema Technique)0 s
videoThe RCC+G Auto-Grader Prompt0 s
video[PRACTICE DATASET] The "NexusFlow" Project Sync0 s
video[ANSWER KEY] NexusFlow Lab0 s
videoM01 Knowledge Check: The Sanity Gate0 s
videoLesson 8: The Architecture Path1 m 3 s
Edgar Oblitey

Edgar Oblitey

Course Instructor

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