Building a CustomGPT? Don’t skip confidentiality & security

Imagine this: You’ve spent weeks building a CustomGPT based on your original content, processes, and insights. You're proud of it—it reflects your voice, your work, and your value.

Now imagine someone tells you they were able to access your GPT’s instructions or infer your training data.

What’s your first reaction?
Anger? Concern? Paranoia?
Or gratitude that they told you?

For me, the possibility alone was enough to change how I approached the build process.

One of the very first things I focused on was learning about Confidentiality and Security Rules for CustomGPTs—and it shaped everything I did next.

Why It Matters More Than You Think
If you’re a content creator, marketer, coach, or consultant building with AI, your CustomGPT likely includes:

• Custom prompts tied to your unique voice or workflow

• Proprietary systems or step-by-step processes

• Data or ideas you’ve developed over time

• Embedded instructions that influence how the GPT responds

In short: your IP.

And once your GPT is public, it’s interacting with others—some curious, some helpful, and yes, potentially some probing.

That’s why I took the time to study OpenAI’s Confidentiality and Security Rules before making anything public. Not because I had to. Because I wanted to protect what I’d built.

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Here’s What I Learned That Every Builder Should Know

1. Your instructions aren’t visible—but they can still be guessed

Even if users can’t see your system instructions, they can interact with your GPT and infer a lot based on how it responds. That means your logic, structure, and even specific language patterns could be exposed.

2. Uploaded files can create more risk

If you include PDFs, slides, or links to your internal resources, be selective. Assume anything you upload could become part of the GPT’s outputs, even if indirectly.

3. Test it like someone who wants to break it

Before publishing, I spent time stress-testing my GPTs—asking strange questions, trying to get behind the scenes, and seeing how it handled edge cases. If it ever hinted at internal logic I didn’t want shared, I tweaked it.

4. Keep it private while you build

CustomGPTs allow for “Only Me” visibility, and I used that extensively while building. It gave me time to test, revise, and refine without exposing anything prematurely.

5. Don’t assume you’re too small to be targeted

Even if you’re not working at a big company or publishing enterprise-level tools, your ideas still matter. Your framework, your way of working—it’s valuable. Treat it that way.

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So—what does this mean for you?
If you’re building or planning to build a CustomGPT, here’s what I’d recommend based on my experience:

• ✅ Read and understand the Confidentiality & Security rules

• ✅ Avoid uploading sensitive files or full strategy docs

• ✅ Use “Only Me” mode while testing

• ✅ Prompt it as a curious stranger would—look for leaks

• ✅ Decide how much you’re willing to share before going public

• ✅ Protect the parts that make your work unique

Want to see a real example of how to apply these rules?

I’ve created a list of sample rules and instructions I use when setting up my CustomGPTs to protect IP, guide behavior, and ensure clarity.