A Custom GPT is a personalized version of ChatGPT that you configure for a specific purpose. Think of it as hiring a specialized assistant who already knows your organization, follows your guidelines, and performs specific tasks exactly the way you need them done.
Unlike the standard ChatGPT that starts fresh with every conversation, a Custom GPT can come pre-loaded with:
Google calls “Gems” to their version of Custom GPTs. Gems are free to create and share, while Custom GPTs are a paid feature, so in general they are a better option.
We will talk mostly about Custom GPTs in this guide, but unless we say otherwise, everything is the same for Gemini Gems.
The setup is very similar, but GPTs let you configure also “Capabilities” and “Welcome messages” if you want. If you are not sure, we recommend adding all capabilities (so the AI decides which tools to use) and no welcome messages (they can be confusing, better to include a brief usage guide in the “Description” field).
Custom GPTs can be used basically for anything that ChatGPT can do. But they make more sense for tasks that are repetitive and require a lot of context or a consistent voice.
Here are some examples for nonprofits:
But these are just some general ideas. The most effective GPTs for your organization may come from your specific frustrations: tasks that take too long, produce inconsistent results, or create a bottleneck for your team.
Advantages:
Limitations:
Before building a custom GPT or Gem, consider whether these alternatives might better suit your needs:
When to build a Custom GPT:
The difference between a mediocre Custom GPT and an excellent one comes down to planning. Spending a few minutes thinking through these questions will save you hours of frustration.
Ask yourself: What is the ONE specific task this GPT will do?
The most common mistake is trying to make a GPT do everything. A GPT designed to “help with all nonprofit communications” will perform worse than several specific GPTs focused on very specific tasks.
Write your purpose statement: “This GPT will help [specific team members] to [specific task] by [how it will help].”
Example: “This GPT will help our development team draft personalized major donor proposals by incorporating our program outcomes, budget information, and matching our organizational voice.”
Who will use this GPT?
What do they need to accomplish?
List the specific outputs you need.
If they are very similar, you might integrate all those outputs into one GPT. Otherwise, you should probably create a different GPT for each key output (with different instructions, examples, etc.).
For example, you could create only one “donor communications GPT” or divide it into different GPTs for:
Your GPT will only be as good as the information you give it. It may be relevant to provide (either as files or text instructions):
Organizational background:
Style and voice guidelines:
Constraints and rules:
Reference materials:
What should users input?
Think about what information users should provide each time they use the GPT. It could be text, files, URLs, or a combination. This should be explained clearly in the GPT’s description.
What should the output look like?
What should your GPT refuse to do?
How should it handle uncertainty and insufficient context?
When the GPT doesn’t have enough information, should it:
Now that you’ve planned your Custom GPT, let’s build it.
You can check the official guides to check all the setup options available for Custom GPTs and Gemini Gems. Here we will focus more on specific tips and strategies for nonprofits.
For ChatGPT:
For Google Gemini:
The title of your Custom GPT. It’s important if you use a lot of different GPTs or are going to share it with other people.
Best practices:
A brief explanation that appears when people browse or use GPTs. A good description is very important if you are going to share the GPT with people that don’t know what the GPT does and how to use it.
Best practices:
Example: “Helps the development team create personalized thank-you letters. Provide info about one specific donor (using text and/or files) and it will generate the final text for the letter.”
This is the most important section. These are the detailed directions that control how your GPT behaves.
Structure your instructions in clear sections. For example:
# Role and Purpose
You are an expert donor communications specialist for [Your Organization Name]. Your primary job is to help our development team create heartfelt, personalized thank-you letters and donor communications.
# About Our Organization
[2-3 paragraphs about your mission, programs, and approach]
# Voice and Tone
- Warm and personal, as if written by our Executive Director
- Grateful without being obsequious
- Inspiring and hopeful about our impact
- Conversational but professional
- Avoid: corporate jargon, overly formal language, generic phrases
# How to Interact with Users
1. Always greet users warmly
2. Ask for the following information if not provided:
- Donor name
- Gift amount
- Designation or program supported
- Any personal connection to note
3. Generate a draft letter
4. Offer to revise based on feedback
# Letter Structure
Every thank-you letter should include:
- Personal greeting using donor's name
- Specific acknowledgment of gift amount
- Genuine gratitude expressed authentically
- Connection between their gift and specific program impact
- A concrete example of how their support makes a difference
- Future vision or next steps
- Warm closing with Executive Director's name
# What You Should Never Do
- Fabricate donation amounts or impact statistics
- Make commitments about how funds will be used without verification
- Include information about other donors
- Generate receipts or tax documentation
- Share confidential organizational information
# Example Letter
[Paste one excellent example here as a reference]
Key principles for instructions:
They are pre-written prompts that appear as buttons users can click. They are not available in Gemini Gems.
We don’t recommend using them, they can be more confusing than helpful.
You want users to provide all the relevant context (e.g. a long text or a few files) to provide a valuable personalized response, not just click on a generic conversation starter that doesn’t provide any context.
So generic “Conversation starters” in GPTs are usually the worse way to actually start conversations. Instead, you should use the “Description” field to give instructions to the users and explain the different options or possible uses.
You can upload documents that your GPT will reference when generating responses
A few examples of files that might be relevant for GPTs:
Best practices:
Capabilties are special tools you can enable or disable for the GPT (web browsing, image generation, etc.). If you are not sure of which capabilities are necessary for your GPT, just activate all capabilities and test results. In theory, the GPT is intelligent enough to know when to use (or not use) a certain capability.
This option is different on Gemini. All tools are available on every Gem, but you can select a “Default tool” for a certain Gem. When you start a new conversation with the Gem, the default tool will be selected. Users can still remove it or select another one. You can choose between Deep Research, Create videos, Create images, etc. Or don’t select a default tool, so it will be a normal chat by default.
Before refining further, test your GPT:
Make note of:
Then refine the setup if necessary and test again.
Your GPT is probably ready when:
Remember: You can always update and improve later. Better to launch a good GPT that your team actually uses than to endlessly perfect one that never leaves testing.
| Symptom | Likely Cause | Quick Fix |
|---|---|---|
| Ignores instructions | Instructions too buried or vague | Move critical rules to top, use bold/caps, be more specific |
| Too generic | Lacks specific examples and context | Add more uploaded documents, include specific phrases/examples |
| Inconsistent quality | Instructions have contradictions or gaps | Review instructions for conflicts, add explicit requirements |
| Won’t refuse bad requests | No clear boundaries set | Add “Never do X” section with specific prohibitions |
| Asks too many questions | Too many undefined variables | Provide defaults, consolidate questions |
| Doesn’t use uploaded files | Not instructed to reference them | Explicitly tell it to check specific files for information |
| Wrong tone | Tone description too vague | Use comparative examples, specify words to use/avoid |
| Wrong length | No length specified | Add exact word/character counts and structure |
.
You’ve built and refined your Custom GPT. Now it’s time to get it into the hands of your team and manage it effectively over time.
When you’re ready to share, click “Save” and you’ll see three options:
For most nonprofit use cases, choose “Anyone with a Link.” This gives you decent control over who can access it while making it easy to share with your team.
For very sensitive GPTs, you might want to use the private option. Your colleagues can create their own “copy” of the same private GPT. Or forget about GPTs for sensitive use cases and just share the prompt (“Instructions” field) with your team.
Gems are a bit different, but they also offer 3 options:
Step 1: Prepare your team
Don’t just drop a link and expect adoption. Create a brief introduction:
Subject: New Tool: Donor Thank-You Letter Assistant
Team,
I've created a custom AI assistant to help us write more personalized donor thank-you letters faster. It already knows our mission, programs, and voice—you just provide donor details.
What it does:
- Generates personalized thank-you letters in our style
- Incorporates specific program information
- Maintains consistent tone across all team members
How to use it:
1. Click this link: [GPT link]
2. Click one of the suggested prompts or describe what you need
3. Answer any follow-up questions
4. Review and edit the draft it provides
Important: Always review outputs for accuracy, especially donor names and gift amounts.
Try it with your next thank-you letter and let me know what you think!
[Your name]
Step 2: Create quick-start documentation
Even though your GPT should be self-explanatory, it’s a good idea to create a brief guide and add it to your organization’s Knowledge Base.
It could be a short video and/or a one-page doc like this:
[GPT Name]
Quick Start Guide
What it's for: [One sentence purpose]
Who should use it: [Target team members]
Access: [Link]
How to use:
1. [First step]
2. [Second step]
3. [Third step]
Tips for best results:
• [Tip 1]
• [Tip 2]
• [Tip 3]
Common questions:
Q: [Question]
A: [Answer]
Need help? Contact [your name/email]
Step 3: Gather feedback
In the first two weeks:
As you create more Custom GPTs, organization becomes important.
Naming Convention
Develop a consistent system. Make it easy to identify the relevant GPTs for each user.
For example, you could start the name of every GPT with the department or roles that will use it:
Keep an inventory:
Create a simple spreadsheet and share it with your team:
| GPT Name | Purpose | Primary Users | Last Updated | Link | Status |
|---|---|---|---|---|---|
| Donor Thank You Writer | Thank-you letters | Development team | Jan 2026 | [link] | Active |
| Grant Proposal Assistant | Foundation proposals | ED + Development Director | Dec 2025 | [link] | Active |
| Social Media Creator | Facebook/Instagram posts | Communications | Jan 2026 | [link] | Testing |
Custom GPTs aren’t set-it-and-forget-it. Plan for ongoing maintenance.
When to Update:
Quarterly reviews (even if no problems):
Immediate updates when:
Version control tip: Before major changes, copy your current instructions to a document. If the update causes problems, you can easily revert.
For any use case, track:
You should always give a link to gather ongoing feedback (via email, form, Slack or whatever tools you use).
Also, you should probably send a survey every 6 months (regarding specific GPTs or all your active GPTs).