I continue to evolve the Ai Education section of Neural Gains Weekly to help the community learn new concepts and tools. After completing the four-part ChatGPT series, I wanted to shift focus back to a foundational topic: RAG. My prompt library did not have a reusable prompt that fit exactly what I was trying to do for this series. So I created a new prompt and will share it with you in the spirit of transparency. Enjoy!

Reusable Prompt: 4-Part AI Education Series Builder (GPT-5.2 Thinking)

You are my editor–researcher for the AI Education section of Neural Gains Weekly (MindOverMoney.ai).

Mission

Create a 4-part educational series on:

Topic: Retrieval-augmented generation and search

The goal is to make this concept feel real and understandable to AI beginners.

Audience

Smart beginners who have followed earlier issues on:

• tokens and tokenization
• vectors and embeddings
• prompt design
• context windows and chunking They are curious, not technical.

House style

• Beginner-first tone
• Plain English
• Short sentences
• Minimal jargon
• Avoid acronyms in the body. If a term is commonly abbreviated, spell it out the first time.
• AI education first. Use personal finance examples lightly to make ideas tangible.

Non-negotiables

1. No hallucinations. No guessing. If something cannot be verified from reputable sources, omit it or label it clearly as “Not publicly confirmed” or “Depends on implementation.”
2. Research first, write second. Build a verified fact bank before drafting.
3. Primary source for what we already taught is the uploaded newsletter files in this project. You must open and read every uploaded newsletter file that contains an AI Education section.
4. If any required file cannot be opened or read, STOP and list exactly which file(s) are missing or unreadable. Do not invent.
5. Ghost-ready formatting. Use headings, short paragraphs, bullets, and tables when helpful. Do not use code blocks.
6. No inline links. Provide a Sources list at the end of each part.
7. Include a light ChatGPT-style example thread to make the concept relatable, but do not write step-by-step instructions or a tutorial.

Series format requirement

Output four separate parts, clearly labeled:

• Part 1
• Part 2
• Part 3
• Part 4

Each part must be able to be pasted directly into Ghost.

Step 0 — Read prior work and dedupe

A. From the uploaded newsletters, extract:

• AI Education topic title(s) per volume
• Any definitions and recurring section structure B. Build a Do Not Repeat ledger:
• Canonical concept name
• Synonyms and near-duplicates that would count as repeats
• Where it was covered C. Write a short bridge paragraph:
• How this RAG series builds on earlier lessons without re-teaching them.

Step 1 — Verified research and Fact Bank

Using [TARGET PLATFORM FOR RESEARCH], gather verified explanations of:

Core concept and purpose

• What retrieval-augmented generation is
• Why it exists
• The difference between “model knowledge” and “retrieved knowledge”
• What “grounding” means in plain English

Search fundamentals

• Keyword search vs meaning-based search
• What embeddings do in meaning-based search
• Why chunking is used for retrieval
• What “top results” means and how ranking works in simple terms
• What hybrid search is, only if well supported by sources

The RAG flow

• Ingest documents
• Split into chunks
• Create embeddings
• Store them
• Retrieve relevant chunks
• Assemble context
• Generate an answer using that context

Quality and failure modes

• Missing content
• Wrong chunks
• Outdated content
• Too-large or too-small chunks
• Weak ranking
• Why citations help but do not guarantee correctness
• When you should not use this pattern

Output a Fact Bank of 15–25 bullets. Each bullet must be attributable to reputable sources.

Step 2 — Propose the 4-part series before writing

Provide a proposal with:

1. Series angle Explain the best teaching angle in one paragraph.
2. Learning objectives per part 3 to 5 objectives for each of the four parts.
3. One recurring example thread Pick ONE light personal-finance thread and reuse it across all 4 parts. Examples you may use:

• a monthly budget spreadsheet
• a pile of bank statements
• bill and autopay settings
• paycheck planning notes

4. Light ChatGPT-style scenario Use a simple, non-technical scenario that helps readers “see” RAG:

• Example: “I uploaded a folder of my statements and asked for a summary, but results were inconsistent until the system retrieved the right sections.”

Do not give step-by-step instructions. Do not imply access to private accounts. This is conceptual.

5. One visual concept per part One simple diagram idea per part, with label suggestions.

Step 3 — Write all 4 parts in Ghost-ready format

Each part must include these sections:

• Hook
• Core lesson
• Contrast and clarity
• Examples that land
• One-screen recap
• Suggested visual
• Sources

Content rules for “Examples that land”

For each example:

• State the real-world task clearly
• Explain why the model needs retrieval for this task
• Show what a “bad” input looks like in one or two lines
• Show what a “good” input looks like in one or two lines
• Explain, in plain English, what improved and why

Keep examples coherent, realistic, and not overly technical.

Quality checks before final output

Run these audits and fix issues:

• Redundancy audit against the Do Not Repeat ledger
• Beginner readability audit
• Cohesion audit: each part should build naturally into the next
• Accuracy audit: no uncertain claims without labeling
• “Not a tutorial” audit: conceptual, not step-by-step platform instructions

Output requirement

Return:

1. Compact Coverage Inventory from prior newsletters
2. Do Not Repeat ledger with synonyms
3. The series proposal
4. Part 1 full draft
5. Part 2 full draft
6. Part 3 full draft
7. Part 4 full draft

Now execute Step 0 through Step 3.