Imagine having a world-class fundraising consultant, a master grant writer, or a seasoned marketing strategist on call 24/7, ready to provide instant, expert advice tailored to your needs. This guide will show you how to build exactly that: a custom “AI Coach” that embodies the knowledge, style, and frameworks of a leading expert in any field.
This workflow walks you through choosing an expert, assembling their core wisdom into a powerful knowledge base, and using a simple, low-cost tool to create a persistent AI persona that your whole team can use to brainstorm ideas, review documents, and develop strategies.
There are hundreds of areas where we could apply the AI Coach/Consultant/Expert concept. Basically anything where getting advice from an expert could help us.
But in case you are out of ideas, here are a few examples where an AI coach could be helpful:
Before we build the AI Coach, it’s crucial to understand the 3 key decisions you’ll make.
Ideally we want to choose experts that:
Our “base expert” doesn’t have to be always one individual, we could base our AI Coach on several experts that apply the same or similar methods (e.g. Theory of Change) or a famous company (e.g. McKinsey strategy consultants)
You need a tool that can maintain a consistent persona and access a custom knowledge base. Here are the best options, from simplest to most advanced.
GPTs (in ChatGPT) and Gems (in Google Gemini) are the most direct and user-friendly way to build a reusable “AI Coach”.
The have slightly different pricing models, features and limitations, but the concepts are very similar. You build a custom bot based on some instructions and files, that you can share with other users.
Pros:
Cons:
Platforms like ChatGPT Team and Claude Pro/Team offer shared “Projects” or workspaces. This allows you to start a shared chat session with a large set of pre-uploaded documents as context.
Shared Projects is usually a paid feature, but if you don’t want to share them with your team, you might be able to use this feature for free on certain platforms (private/individual projects) .
Pros:
Cons:
RAG (Retrieval-Augmented Generation) is a technology that allows you to connect a language model to your own external knowledge base. With RAG you create a searchable library of information that the AI can “look up” in real-time to find the most relevant facts before answering.
This should provide more accurate results than the other options, especially if you want to retrieve specific facts and detailed theories, not just replicate the “vibes” and main strategies/frameworks of an expert.
Pros:
Cons:
The effectiveness of your AI coach depends heavily on the knowledge you provide it. There is no single best approach; the ideal strategy depends on your chosen expert, the source material, and the tool you’re using.
The Library Model is the easiest and usually gives good results, but we recommend testing the 3 methods and comparing results (at least for one of the “AI Coaches” that you want to create).
What it is: You provide the AI with a large volume of the expert’s raw, full-text works (e.g., multiple book chapters, 10-15 articles, transcripts of talks…).
What it is: You create a concise (5-10 page) “Master Principles” document that synthesizes the expert’s core frameworks, key principles, and step-by-step processes.
What it is: You provide both your “Master Principles” summary document AND a few long documents (e.g. 2-3 key articles).
This process will guide you from selecting an expert to having a fully functional AI Coach.
First, decide who your AI Coach will emulate. Then, prepare your knowledge files based on the strategy you want to test (Library, Summary, or Hybrid).
We will use a Custom Bot + Hybrid Model for this example.
If you want the easier and faster solution, use the Library Model and skip the step A below (don’t create or upload the “Master Principles” document).
We will be using Gemini Gems (available for free) to create the Bot. The setup is very similar for GPTs (in ChatGPT), but you need a paid account to create those.
Start a new document and synthesize the expert’s core ideas, frameworks, principles, and voice/tone description. Structure it with clear headings.
Tools like ChatGPT or Google’s NotebookLM can help you synthesize large volumes of expert content into distilled knowledge documents. NotebookLM is particularly valuable for this task, as it can process up dozens of documents and create comprehensive summaries that maintain connections between concepts.
The “Master Principles” document could be something like this:
# Expert Profile: **Expert Name**
## Background & Expertise
**Brief bio and credentials**
## Core Philosophy
**Their fundamental beliefs and approach**
## Communication Style
- Tone: **e.g., encouraging, direct, analytical**
- Approach: **e.g., framework-driven, story-based**
- Key phrases they use: **distinctive language**
## Key Frameworks & Methodologies
1. **Framework name and brief description**
2. **Framework name and brief description**
## Typical Advice Patterns
When asked about **X**, they typically suggest **...**
When someone struggles with **Y**, they recommend **...**
## What Makes Them Unique
**What distinguishes this expert from others in the field**Choose 2-3 of their most representative works and save them in a AI-friendly format (structured text).
Possible sources include:
You can transcribe videos and audios very quickly using AI tools like NotebookLM, Elevenlabs and many others.
Markdown files are the best (most efficient format for delivering formatted text to AI chatbots), but you can also use PDF, TXT, DOCX or other file formats if your AI tool allows them for uploads.
All the files that you use should comply with some basic requirements:
Creating Gems is free in Google Gemini, while creating custom GPTs in ChatGPT is a paid feature. So we will focus here on Gemini, but they are very similar.
1) Log in to Google Gemini and click on “Explore Gems” in the sidebar.
2) Click on the “New Gem” button
3) Fill out the fields and save it:
4) Click on the “Share” button if you want to give access to certain users or anyone with the link. In most cases, you will want to do some testing before sharing it. You can share gems anytime you want by clicking on the share icon in the “Gem manager” page.
Copy and paste this into the “Instructions” field of your Custom GPT.
# PERSONA
You are an AI Coach embodying the expertise, style and strategic frameworks of the following Expert (or company):
**Expert's Name & Bio/Description**
# CORE MISSION
Your primary mission is to help nonprofit professionals improve their work by applying the principles of the Expert. You must provide actionable guidance and advice, all through the lens of this Expert's unique methodology and expertise.
# KNOWLEDGE BASE
We have uploaded documents that contain the work and principles of the Expert.
When a user asks a question, you must ground your answer entirely in those documents.
Do not introduce outside concepts unless specifically asked.
# MASTER PRINCIPLES (OPTIONAL)
If a "Master Principles" document exists, you must treat it as the foundational text. Prioritize the contents of this document to the other documents.
Use the other documents to find specific examples, quotes, and to capture the expert's voice.
# RULES OF INTERACTION
1.Stay in character: Never break character or say you are an AI. If asked about something outside the Expert's domain, acknowledge the limitation and suggest they consult a specialist.
2.Be specific & strategic, never generic: Avoid generic advice. Whenever possible, connect your recommendations back to a specific framework or principle from your knowledge base. For example, say "Applying the 'Clarity First' principle, let's simplify this sentence..."
3.Ask clarifying questions if necessary: If a user's request is vague or you need additional information to give a great response, ask questions to better understand their context, just as a real coach or consultant would.
4.Prioritize action: End your responses with clear, actionable next steps.
Your coach is built, but it needs to be tested. Interact with it in the “Preview” pane.
Ask it to explain a framework, give advice on a scenario, and review a document for tone. Maybe ask other colleagues to test it and give feedback (make sure they know it’s just a beta or “first draft”, not the final version).
If the results are weak, experiment with a different knowledge base strategy (e.g., switch from Hybrid to Summary-only) and refine your instructions.
The real value is unlocked when your whole team uses the coach. Share the link and include a short guide with example prompts to help them get started. This creates consistency and builds skills across the organization.
The guide can be something like this:
# How to Use **Expert Name** AI Coach
## What It Can Do
- **List the best use cases**
## What It Can't Do
- Replace human expertise for final decisions
- Provide real-time data (unless using web browsing)
- **Other limitations**
## Best Practices
1. Provide context: Share relevant details about your situation
2. Ask follow-up questions: Dig deeper into recommendations
3. Request examples: Ask "Can you show me an example?"
4. Verify critical information: Double-check facts and figures
5. Combine with human judgment: Use as a tool, not replacement
## Sample Questions
- **5-10 questions/prompts that usually give great results**
## Getting the Best Results
- Be specific about your constraints (timeline, budget, etc.)
- Share what you've already tried
- Ask for the reasoning behind recommendations
- Request alternative approaches