The Simple RAG Trick That Stops AI From Making Up Facts About Your Company
Your AI Is Forgetting Everything You Tell It (Here's The Fix That Takes 30 Minutes)
From generic chatbot to specialized assistant in 30 minutes: How RAG turns AI into your most knowledgeable team member.
Hey there!
Your AI keeps forgetting what you told it three prompts ago. Or worse, it’s making up facts about your business, your processes, your industry data. You feed it information, and two minutes later, it’s citing sources that don’t exist.
Here’s what most people don’t know: there’s a simple way to give AI a permanent memory of everything that matters to you. No coding required. No technical setup. Just a systematic approach that takes 30 minutes to build and makes your AI 10x more useful.
I’m talking about Retrieval Augmented Generation (RAG), and today you’re getting 12 prompts that turn any AI into your personal knowledge assistant. One that actually remembers your stuff, cites real sources, and never hallucinates about your business.
Why This Changes Everything Right Now
RAG sounds technical, but it’s just organized AI memory. Instead of dumping everything into a single prompt and hoping for the best, you create a searchable knowledge base that AI pulls from automatically. Think of it as giving ChatGPT or Claude a filing cabinet of your actual documents, then teaching it how to find exactly what it needs.
The difference is that your AI goes from a generic advice machine to a specialized expert on YOUR business. And you’re building this system today.
The difference between basic AI use and RAG-powered AI is the difference between asking a stranger for advice and consulting your own expert who’s read everything you’ve ever written. Same AI, completely different results.
Building Your Foundation
Prompt #1: Knowledge Base Structure Blueprint
What it does: Creates the folder structure and organization system for your AI knowledge base
When to use it: Starting your RAG setup from scratch, before adding any documents
The Prompt:
I need to build a personal knowledge base for AI retrieval. My focus areas are [YOUR 3-5 MAIN TOPICS/WORK AREAS].
Create a structured organization system with:
- Top-level categories for my knowledge base
- Sub-categories under each
- Naming conventions that make files easy to find
- Recommended file types for each category
- A simple tagging system that doesn’t require technical knowledge
Format this as a clear directory structure I can implement today.How to use it:
List your 3-5 main work areas or topics you want AI to know
Copy the output and create these folders in Google Drive or Dropbox
Use the naming conventions exactly as specified
Example input: “My focus areas are: content marketing strategy, client case studies, AI implementation guides, competitive research, and sales messaging frameworks”
What you’ll get: A clean folder structure with 15-20 categories ready to fill with your documents
Pro tip: Add a “Quick Reference” category for one-page summaries - these become your highest-value RAG sources
Prompt #2: Document Summary Generator
What it does: Converts any document into a retrieval-optimized summary that AI can search effectively
When to use it: Processing each document before adding it to your knowledge base
The Prompt:
Summarize this document for AI retrieval purposes:
[PASTE YOUR DOCUMENT TEXT]
Using these naming conventions from my knowledge base structure:
[PASTE RELEVANT NAMING CONVENTIONS FROM PROMPT 1 OUTPUT]
Create a summary that includes:
1. Recommended filename using my naming conventions
2. Core topic and purpose (one sentence)
3. Key facts, figures, or data points (bullet list)
4. Main conclusions or recommendations
5. Searchable keywords (10-15 terms someone might use to find this)
6. Related topics or categories
Keep the summary under 300 words but capture everything essential for future reference.How to use it:
Copy your full document text
Copy the naming conventions from your Prompt #1 output
Paste both into the prompt
Save the summary with the recommended filename in your knowledge base
Example input: A 10-page competitive analysis report on social media management tools. Naming convention: “YYYY-MM-DD_Category_Description.pdf”
What you’ll get: A dense, searchable summary with a properly formatted filename like “2024-11-09_Competitive-Analysis_Social-Media-Tools.pdf”
Pro tip: Add the document creation date and author to your summary - this context matters for time-sensitive information
Prompt #3: Master Index Builder
What it does: Creates a searchable index of all your knowledge base documents with descriptions
When to use it: After organizing your first 10-20 documents, then update monthly
The Prompt:
I’m building a master index for my knowledge base.
My knowledge base structure:
[PASTE YOUR FOLDER STRUCTURE FROM PROMPT 1]
Here are my documents:
[LIST YOUR DOCUMENT TITLES AND CATEGORIES]
Create a comprehensive index that includes:
- Document title and category
- One-line description of what’s inside
- Key topics covered (3-5 keywords)
- Best use cases for retrieving this document
- Related documents in my collection
Format this as a table that’s easy to scan and search.How to use it:
Copy your folder structure from Prompt #1 output
List all documents you’ve added to your knowledge base
Generate the index
Save as “MASTER_INDEX.md” in your root folder
Example input: Structure: Marketing/ Sales/ Product/ Operations/ Documents: “Q3_2024_Sales_Report.pdf (Sales Data), Client_Success_Story_Acme.docx (Case Studies), Content_Calendar_Template.xlsx (Marketing Tools)”
What you’ll get: A scannable table showing what’s in your knowledge base, organized by your categories, with clear use cases for each piece
Pro tip: Include this index at the start of every major AI session - it helps the AI know what it can retrieve
Prompt #4: Context-Aware Prompt Builder
What it does: Transforms regular prompts into RAG-optimized prompts that pull from your knowledge base
When to use it: Converting any standard AI prompt to work with your organized documents
The Prompt:
Convert this standard prompt into a RAG-optimized version:
Original prompt: [YOUR CURRENT PROMPT]
My knowledge base categories: [LIST YOUR MAIN CATEGORIES]
Rewrite this prompt to:
1. Explicitly reference which knowledge base documents to search
2. Specify what type of information to retrieve
3. Include instructions for citing sources
4. Request structured output that’s easy to verify
5. Add a relevance check to confirm the retrieved info matches the query
Keep the core intent but make it retrieval-focused.How to use it:
Take any prompt you use regularly
List your knowledge base categories
Use the optimized version going forward
Example input: Original: “Write a case study about successful client implementation.” Categories: “Client case studies, Implementation guides, Success metrics”
What you’ll get: A retrieval-optimized prompt that pulls specific details from your actual client files
Pro tip: Save your top 10 converted prompts in a “RAG_Prompt_Library” folder for quick access
Prompt #5: Retrieval Instruction Template
What it does: Creates the standing instructions you’ll give AI at the start of every session
When to use it: Once at setup, then copy-paste at the beginning of any new conversation
The Prompt:
Create standing RAG instructions for my AI sessions based on:
Knowledge base categories: [YOUR CATEGORIES]
Types of documents: [YOUR DOCUMENT TYPES]
Preferred citation style: [YOUR PREFERENCE]
Output format preference: [YOUR PREFERENCE]
Write instructions that tell AI to:
1. Always check my knowledge base before generating responses
2. Cite specific documents and page numbers when available
3. Flag when it’s using general knowledge vs. my documents
4. Ask clarifying questions if multiple relevant documents exist
5. Indicate confidence level in retrieval accuracy
Make these instructions clear but brief enough to copy-paste at conversation start.How to use it:
Fill in your knowledge base specifics
Generate the instructions once
Save as a text snippet to paste at the start of every session
Example input: “Categories: Marketing, Sales, Product. Documents: PDFs, Google Docs, spreadsheets. Citation: [Source - Document Name]. Format: Bulleted lists with source citations.”
What you’ll get: A 100-150-word instruction block that turns any AI session into a RAG-powered conversation
Pro tip: Test this with 3-4 queries to refine the instructions before saving your final version
Advanced Retrieval Techniques
Prompt #6: Query Optimization Engine
What it does: Rewrites vague questions into precise retrieval queries that find exactly what you need
When to use it: When you know the answer is in your knowledge base, but can’t articulate the exact query