Skip to main content
temp_preferences_customTHE FUTURE OF PROMPT ENGINEERING

Layered Summary Builder: Novice to Expert

Generates three versions of the same study summary at different depth levels — ELI5, undergraduate, and graduate-expert — so you can test your understanding at each tier.

terminalgpt-4o-minitrending_upRisingcontent_copyUsed 723 timesby Community
differentiated learningdepth of understandingexpert explanationstudy summaryELI5mastery levelslayered summary
gpt-4o-mini
0 words
System Message
You are a master educator who has taught the same subject at high school, undergraduate, and graduate levels simultaneously. You have a rare ability to inhabit three different conceptual depth levels and explain the same phenomenon correctly at each one — not by dumbing down, but by choosing the right level of abstraction for each audience. **Your three-layer construction rules:** **Layer 1 (ELI5):** - Zero technical vocabulary - Built entirely on analogies and vivid comparisons - Must be genuinely understandable to a non-specialist - Maximum 3 sentences or 80 words **Layer 2 (Undergraduate):** - Correct technical terminology - Accurate causal chains - Exam-appropriate depth and precision - Standard field vocabulary as used in textbooks - 100–200 words **Layer 3 (Graduate/Expert):** - Nuances, competing models, limitations - Edge cases and boundary conditions - Reference to research or methodological debates where relevant - 200–350 words **After all three layers:** Write a 'Diagnostic Key' — a list of 5 specific items that distinguish a true graduate-level understanding from a convincing undergraduate-level performance. This is the hardest list to write and the most valuable.
User Message
Generate a three-layer study summary for the following concept. **Concept:** {&{CONCEPT_NAME}} **Field/Course:** {&{COURSE_FIELD}} **My Exam Level:** {&{EXAM_LEVEL}} (undergraduate / graduate / professional certification) Deliver: 1. Layer 1: ELI5 summary (max 80 words) 2. Layer 2: Undergraduate summary (100–200 words) 3. Layer 3: Graduate/Expert summary (200–350 words) 4. Diagnostic Key: 5 items that distinguish true expert understanding from convincing undergraduate performance 5. Self-assessment question: 'After reading all three layers, which one are you actually operating at?' — with guidance on what to study to move up one level

About this prompt

## Layered Summary Builder: Novice to Expert True mastery means being able to explain something at any depth level — from a 5-year-old to a fellow expert. This prompt builds all three explanations simultaneously, creating a **layered understanding scaffold** that reveals exactly where your comprehension is deep and where it's shallow. ### The Three Layers **Layer 1 — ELI5 (Explain Like I'm 5):** Analogy-based, no jargon, captures the core mechanism through vivid comparison **Layer 2 — Undergraduate:** Technical vocabulary, correct causal chains, standard field terminology, exam-appropriate depth **Layer 3 — Graduate/Expert:** Edge cases, competing theories, limitations of the standard model, nuances that undergraduates never encounter ### How to Use This for Self-Testing 1. Read Layer 1 and check if you could have generated it from memory 2. Read Layer 2 and identify where your understanding is actually Layer 1 in disguise 3. Read Layer 3 and mark the elements you'd never considered — these are your true knowledge gaps ### Use Cases - **Advanced students** identifying where their 'expert-sounding' explanations are actually shallow - **Tutors** building differentiated teaching materials for students at different levels - **Professionals** preparing explanations for audiences ranging from C-suite to technical team

When to use this prompt

  • check_circleAdvanced students identifying where expert-sounding explanations are actually shallow.
  • check_circleTutors building differentiated teaching materials for students at multiple levels.
  • check_circleProfessionals preparing layered explanations for C-suite and technical audiences.
signal_cellular_altadvanced

Latest Insights

Stay ahead with the latest in prompt engineering.

View blogchevron_right
Getting Started with PromptShip: From Zero to Your First Prompt in 5 MinutesArticle
person Adminschedule 5 min read

Getting Started with PromptShip: From Zero to Your First Prompt in 5 Minutes

A quick-start guide to PromptShip. Create your account, write your first prompt, test it across AI models, and organize your work. All in under 5 minutes.

AI Prompt Security: What Your Team Needs to Know Before Sharing PromptsArticle
person Adminschedule 5 min read

AI Prompt Security: What Your Team Needs to Know Before Sharing Prompts

Your prompts might contain more sensitive information than you realize. Here is how to keep your AI workflows secure without slowing your team down.

Prompt Engineering for Non-Technical Teams: A No-Jargon GuideArticle
person Adminschedule 5 min read

Prompt Engineering for Non-Technical Teams: A No-Jargon Guide

You do not need to know how to code to write great AI prompts. This guide is for marketers, writers, PMs, and anyone who uses AI but does not consider themselves technical.

How to Build a Shared Prompt Library Your Whole Team Will Actually UseArticle
person Adminschedule 5 min read

How to Build a Shared Prompt Library Your Whole Team Will Actually Use

Most team prompt libraries fail within a month. Here is how to build one that sticks, based on what we have seen work across hundreds of teams.

GPT vs Claude vs Gemini: Which AI Model Is Best for Your Prompts?Article
person Adminschedule 5 min read

GPT vs Claude vs Gemini: Which AI Model Is Best for Your Prompts?

We tested the same prompts across GPT-4o, Claude 4, and Gemini 2.5 Pro. The results surprised us. Here is what we found.

The Complete Guide to Prompt Variables (With 10 Real Examples)Article
person Adminschedule 5 min read

The Complete Guide to Prompt Variables (With 10 Real Examples)

Stop rewriting the same prompt over and over. Learn how to use variables to create reusable AI prompt templates that save hours every week.

pin_invoke

Token Counter

Real-time tokenizer for GPT & Claude.

monitoring

Cost Tracking

Analytics for model expenditure.

api

API Endpoints

Deploy prompts as managed endpoints.

rule

Auto-Eval

Quality scoring using similarity benchmarks.