
Most people get caught up with ChatGPT. It’s fast, sometimes helpful… and the outputs are often way off. There’s so much AI slop floating around the internet, and hustle-culture bros hyping how much more they can do with AI now. Yes, we can do more with AI. But if you’re not using it well, people can tell. Which is probably why you landed here wondering how to build a custom GPT.
The amount of times I hear something like: “I want to use AI because I know it could help me do more, but I waste time with it and feel like I could have done things faster myself.”
That frustration is valid—and it’s usually not because AI “doesn’t work.” It’s because generic tools require constant prompting and decision-making, which defeats the point for most founders. Without the judgement, discernment, taste, and overall understanding of what you’re trying to create, you won’t be able to lead your AI. And that’s the whole point.
AI doesn’t replace humans. It helps you do more, better. But you need the context to prompt it well and get outputs that aren’t slop.
Enter: custom GPTs trained on a specific workflow, so you don’t have to prompt it every time. The strategy is built in.

Custom GPTs are AI assistants built within ChatGPT that combine tailored instructions, knowledge files, and capabilities to perform specific tasks reliably without repeating prompts. Custom GPTs can be private, shared with select people, or public.
I build custom GPTs for internal use, client use, and mass use through my digital product shop, The Biz Bar.
In the video that inspired this post, I break down what custom GPTs can do that regular ChatGPT can’t, and why I treat mine like team members in development, not static tools. Because they’re just not.
In this blog post, we’ll go through:
If you’d prefer to watch, check out the YouTube video here.
If you’re thinking about building a custom GPT, there’s a good chance you’re either:
Custom GPTs don’t need to be hard. But they do need to be intentional. The setup is actually technically simple. You could build one in under 5 minutes. But is it built well? Will it work within your business systems? That’s another story. That’s where the intentionality, approach, and the knowledge base you train it with really make a difference.
I use customGPTs in multiple internal and client-facing workflows, and have built GPT ecosystems for clients as well. A lot of my tools available in The Biz Bar are custom GPTs trained for mass use, so anyone can get the support they need to grow their business.
Examples of tasks that custom GPTs can do for you include…
Most people jump straight into prompts and instructions, then wonder why their GPT feels inconsistent, off-brand, or unusable in real workflows. But building a custom GPT is less about clever role-style prompting and more about designing a system that supports how you already think and work… or how you want to.
I’m Jill Wise. 👋 I help my clients become better marketers and business owners, acting as a thinking partner for those who don’t need more tactics. You need clarity, reflection, accountability, and systems to help you work smarter, not harder. AI (and custom GPTs) are part of that ecosystem of solutions we can create for you.
This post walks through how to build a custom GPT, but more importantly, how to think about building one so it actually supports your business—not just adds another thing to manage.
Before you build a custom GPT, you need to know what job it’s being hired to do.
AI should support a system you already have, or one you need. There’s so much a GPT could do, but that doesn’t mean it should do all of it. When people try to build “do-everything” GPTs, they usually end up with tools that feel vague, unpredictable, or hard to trust.
From a coaching and consulting lens, this is where I always start with clients:
What decisions are you making on repeat? And which ones are draining you, distracting you, or not worth your time?
What tasks are you or your team doing more than 2x? ← Many of these can be automated with custom GPTs.
These answers reveal where a GPT can:
Before building GPTs for content or messaging, I audited my own workflows first. As a systems-thinking person, I already had SOPs and workflows for every aspect of my business and client work. This made it easy to look at which parts I could remove from my plate, so I can now focus on better things.
For example, with my YouTube channel, I looked at:
Then I built a GPT that helps me turn my video transcripts into keyword-optimized descriptions, email teasers to send to my list, then repurpose that content elsewhere for my blog and social media. The GPT wasn’t built to “come up with ideas.” And it doesn’t create anything from scratch because I want to preserve my voice.
This blog post sounds like me because it’s my words. But now I don’t need to sit at my desk typing for 4 hours to turn a video into an SEO and LLM optimized blog post. The GPT helps with the weight of that work. It was built to support an existing system, so I can focus on better outputs.
I get to spend more time making better videos now because the time dedicated to busywork of repurposing has collapsed significantly.
What should I automate first when building a custom GPT?
Start with repeated decisions and bottlenecks, not creative ideation.
Do I need an existing system before building a custom GPT?
You don’t need perfection, but you do need a workflow to anchor the tool.
The quality of your system prompt and knowledge base directly impacts the quality of your results.
Custom GPTs can be simple or complex, but they must be specific. When people say their GPT “isn’t listening or working,” it’s usually because the inputs are vague, conflicting, or incomplete.
A system prompt isn’t just tone instructions. It’s the operating parameters that keep your custom GPT aligned with its core goal.
I design system prompts like I design roles for human collaborators:
I write job descriptions for all of my GPTs because that’s how I’d onboard a team member. When you approach building your custom GPTs from this perspective, it’s easier to wrap your head around what the GPT needs in order to succeed.
Would you take 5 minutes to train a team member? Probably not. Give longer to think through your custom GPTs too.
Depending on the use case, this often includes:
Garbage in, garbage out still applies, especially with custom GPTs.
What should I include in a custom GPT knowledge base?
Anything you’d give a team member: SOPs, examples, frameworks, style guides, decision rules.
Why is my custom GPT ignoring my knowledge files?
Usually the files aren’t structured, are redundant/contradictory, or the instructions don’t tell the GPT how to use them.
Who is actually using this GPT? This question shapes everything: prompt style, output length, structure, and guardrails.
From a thinking-partner perspective, this matters because tools shape behavior.
That’s why one-size-fits-all GPTs rarely work well.
For example, I have a website copywriter GPT that’s trained on my brand voice. This is different from my website copywriter GPT that you can get access to via The Biz Bar. That GPT is designed around a workflow for people who may not know the typical process to write website copy. I’ve also built similar but different GPTs for clients who need a jr website copywriter. These are designed to fit their workflows, not mine. But they have different context and checkpoints compared to the mass use variations.
Can one custom GPT work for everyone?
Usually no. Different users need different guardrails.
Should client-facing GPTs be more restricted?
Yes. Constraints improve outcomes for non-expert users.
I’ve been going deep into AI land recently. Not just YouTube rabbit holes and spending time using these tools, but actually taking courses facilitated by industry leaders too so I can better support clients. We’re living through a huge shift in what “working smarter” really means. And since that’s a core pillar of everything I do, obviously I need to dig into this stuff.
It’s all about finding better ways to systemize marketing and ops so business is easier for you. So you can live your life.
A cool perspective I’ve gained is that training AI is a lot like training human team members.
Skills that transfer between training AI vs human teams:
The excitement when it clicked… The things that help me train a human team are the key components that are helping me use AI tools better.
Thankfully, I already have the resources to train, lead, and manage a team. All the technical details: SOPs, workflows, KPIs, style guides, examples, training resources, job descriptions. Libraries of it are living in my business backend.
You can use the same things to get AI to really work for you too.
For example, a 1–2 sentence prompt is a start if you’re new. Everyone’s pushing prompts these days. But if you’re unhappy with the results that ChatGPT is giving you, it’s not the computer. It’s the lack of strategy—and honestly, leadership—that you’re giving it.
Imagine if you gave a new human contractor instructions for a project that were just as brief. Maybe she’s eager to show her independence or too scared to ask followup questions, so she acts in the best way she thinks possible.
Then you’re not happy with the results. Queue: I should have just done it myself… and No one can do X job like I can.
We already know those are false, limiting beliefs.
💡 Better input = better output.
It’s kind of like how the best leaders are also people who have done the small jobs first. Maybe you’re not able to do everything at A+ level, but you understand enough about each role within the business to guide your team with empathy and specificity, and help them improve. You have context and awareness and the language to communicate the results you expect.
The same applies here.
It means that the skills of your trade, whether that’s copywriting or design or something else, still apply. You need to know what language to use to prompt your AI assistants to get the best results.
Because better input = better output… just like humans.
On the flip side, this means that if you don’t know the strategy or words or have the specific tools to train your AI assistants (so you can feed each one that strategy), you’ll struggle with output.
This was a 💡 moment for me, so I thought you might benefit from that perspective too. Since realizing this, I’ve been feeding my AI tools from my team processes and the results are 👌👌👌 much better.
I mentioned I have multiple GPTs for internal use, client use, and ones that anyone can use! Some of those are available in The Biz Bar.
Billie the Messaging Maven builds your messaging playbook that plugs into your ChatGPT, team resources, and keeps everyone on the same page.
The Website Copywriter GPT uses my library of frameworks and your playbook to put together not boring copy that acts as a step in your pipeline. Not just a digital business card.
The Email Copywriter GPT helps you get and warm your first 1000 subscribers by turning your ideas into legitimately valuable sequences and marketing emails that feel like you.
Check out the tools currently available in The Biz Bar here.
I also have a GPT I named Sage, who is trained as my personal website copywriter. This one is specific to my brand messaging and output. It’s only meant for use within my business for my website copy. That’s how detailed you can get with custom GPTs.
She assumes deep context, fewer guardrails, and higher strategic awareness. Her system prompt and knowledge base are different by design.
All these GPTs work in similar ways, but they were built for different roles and different users.
If you’re the kind of person who wants to understand the why before the how, everything we’ve covered so far matters.
But once the thinking is clear, the actual build process is surprisingly straightforward.
This is the high-level checklist I follow when building any custom GPT whether it’s for myself, a client, or a self-serve tool like Billie.
Before touching the tool, answer this in plain language:
If you can’t describe the role clearly, the GPT won’t perform clearly either. This step prevents scope creep and “do everything” bots that aren’t trustworthy.
Inside the GPT builder, this is where you set the foundation.
Your system prompt should read more like instructions than the viral prompts you see online. It needs to include:
I treat this exactly like onboarding a new team member because that’s effectively what you’re doing. You can see the start of mine here, but my system prompts typically run the full 8000 characters, or close to it.

Conversation starters aren’t fluff. They shape how users interact with the GPT.
Use them to:
Client-facing GPTs usually need more structure here. Internal GPTs can be looser. Here’s one that private clients use, and is available for mass use in The Biz Bar.

This is where most people either overdo it or underdo it. When deciding how to build a custom GPT that fits your business, you need to consider the information your new GPT will need. Give it just enough. Not too little that it can’t do the job required. Not so much that it gets confused.
Your knowledge base should include:
Quality matters more than quantity. Conflicting or outdated documents will confuse the model.
I also keep a simple tracking sheet for:
Here’s an example of how to build a custom GPT with a specific, intentional knowledge base. This is for a content repurposer GPT that I use personally.

Decide what this GPT actually needs access to:
More capabilities ≠ better GPT. Too many steps can weigh down the system prompt and cause more hallucinations. Only enable what supports the role you defined in Step 1.
Testing isn’t about asking, “Is this smart?”
It’s about asking:
Test with real tasks you already do, not idealized examples. I start by giving ChatGPT my system prompt and having it create tests for me to run, but then also test it in real use cases.
A custom GPT is not “set it and forget it” after you build it.
As your business evolves:
Your GPT should evolve too. This is why you need a tracking database for all your GPTs! You should keep these organized so you know which tool does what, just like you’d track a human team.
This is why I treat GPTs as team members in development, not static tools.
Even well-built GPTs can drift or underperform. The key is knowing where to adjust instead of scrapping the whole thing. Here are the most common issues I see, and how to resolve them.
There’s so many viral videos talking about how to build a custom GPT in 5 minutes that most people miss the point. Just because you can build these quickly doesn’t mean those custom GPTs will serve the purpose you need them to within your workflows. Follow the instructions in this blog post, and you’ll get better results.
This is one of the most common frustrations.
Possible causes:
How to fix it:
This is rarely a model problem. It’s usually a clarity problem.
Possible causes:
Remember: Better input = better output. What would a human need to do this job well?
How to fix it:
This is a boundary issue. If a GPT is over-helpful, it’s because you didn’t tell it where to stop. The silly little robot is trying to do a good job and give you the answer it thinks is most likely.
How to fix it:
This is the biggest red flag that something is off for your entire system design. If a GPT increases cognitive load, it’s misaligned with your workflow.
Possible causes:
How to fix it:
A good GPT should feel like relief, not another thing to manage.
You don’t always need to start over.
Refine when:
Rebuild when:
This mirrors human teams too. Sometimes you coach, sometimes you restructure.
Without clarity, GPTs drift. Outputs become inconsistent. Decisions feel random. People assume the tool failed when the real issue is missing context.
That’s why every GPT I build is anchored to a brand foundation. If you don’t have this yet, check out my AI-Ready Brand Brief.
It acts as the source of truth for:
It’s a living system. When the brand evolves, this brief needs to be updated too. If you’re struggling to integrate AI, this is the tool you start with! It’s free—learn more about the AI Ready Brand Brief here.
I’m not here to sell shortcuts or tools in isolation. My literal job is strategy, which requires creative and critical thinking. My AI tools all eliminate the stuff that bogs me and my clients down. The repetitive stuff. The busywork. The things you don’t want to do.
When we work together, my goal is to help you think better, stay accountable to your goals, and execute without burning out because your business model and systems support you as a human being.
GPTs can support that when they’re designed intentionally, inside a larger system of strategy and reflection.
If you want to self-serve and get better at marketing now, my GPTs can help. If you want a thinking partner to help you see what you can’t see and build systems that hold, that’s where coaching and consulting come in. All options help you create space for better.
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