Custom GPTs Changed How My Clients Work

There is a specific moment I live for in coaching sessions. It is the moment when a client stops asking me how to do something and starts showing me what they already figured out.

It happened during a session with a business consulting team. We were working through some AI image generation capabilities, and one of the team members interrupted to share something she had done on her own.

"Dr. Jeff, I learned so much from you. I literally proposed making a custom GPT for photo lineups, and when I did it, Dr. Jean was amazed, asking how I did it. I told her it was Dr. Jeff who taught me, and she exclaimed, 'This is amazing!'"

That was Kristen, a business consultant who had taken what we covered in our sessions and started building tools without being told to. She did not wait for me to assign homework. She identified a need in her workflow, built a custom GPT to solve it, and impressed her business partner in the process.

This is what AI adoption looks like when it actually works.

What Custom GPTs Actually Are (For Those Who Have Not Built One Yet)

A custom GPT is a specialized version of ChatGPT that you configure for a specific task. You give it instructions, upload reference documents, and define its personality and scope. Instead of starting from scratch every time you open a chat, you open a purpose-built tool that already knows your context.

Think of it like the difference between having a general assistant who knows nothing about your business versus a trained specialist who understands your industry, your clients, and your workflows.

I teach custom GPTs in most of my coaching sessions because they solve one of the biggest friction points I see: people wasting the first five minutes of every AI conversation re-explaining who they are and what they need.

"Custom instructions are the system instructions," I explain in first sessions. "They are instructions that you put inside of your large language model, and it will remember them. It stays there. So anytime you come on, it will know. It is very, very helpful because it makes for efficiencies, so you do not have to keep explaining yourself each time."

But custom GPTs take this a step further. Instead of just custom instructions in a general chat, you get a dedicated tool with its own knowledge base, its own personality, and its own scope.

The Photo Lineup GPT

What Kristen built was elegant in its simplicity. She works with clients who need consistent, professional-looking photo assets. Instead of manually formatting and arranging photos every time, she created a GPT that handles the layout, formatting, and consistency automatically.

Was it the most complex AI project in the world? No. But that is exactly why it matters. She identified a repetitive task in her workflow, built a tool to handle it, and now she saves time on every single project. Multiply that across dozens of clients and the math gets interesting fast.

What made her business partner's reaction so powerful was the gap it revealed. Jean is an experienced business consultant. She has decades of expertise. But she had not yet made the leap from using AI as a chat tool to building AI tools herself. When Kristen showed what she had built, it shifted the entire team's understanding of what was possible.

The Headshot Revolution

Kristen did not stop at photo lineups. During another session, she shared what she had been doing with ChatGPT's image capabilities.

"I have been using ChatGPT in my other company to redo headshots and make them look more uniform. I was amazed at the output because it looked like I paid for that headshot app. I actually find that ChatGPT does a better job of creating those than even the paid app that I have."

Let me put this in business terms. Professional headshot apps charge anywhere from $30 to $100 per session. If you are a consulting firm that needs uniform headshots for a team of 10 or 15 people, that adds up. Kristen replaced that entire cost with a tool she already had access to.

But the time savings matter more than the money. Coordinating professional headshot sessions, especially for distributed teams, is a logistical headache. Getting everyone in front of a photographer, getting consistent lighting and backgrounds, getting the files formatted. Kristen collapsed all of that into something she could do in a few minutes from her laptop.

Claude for Strategy Documents

Kristen also discovered something I see validated constantly across my client base: different AI tools have different strengths.

"I've noticed that with Claude, the output for strategy is very professional looking, and the documents I put together are beautiful. I sent one to the CEO of my other company, and he was amazed that it only took me two minutes. Honestly, for client deliverables and professional documents, ain't nobody touching Claude."

Two minutes for a strategy document that impressed a CEO. That is the kind of result that changes how people think about their own capability. Before AI, producing a polished strategy document required hours of writing, formatting, and revision. With the right AI tool and the right prompts, the mechanical work collapses. The human expertise in knowing what the strategy should say still matters. But the time to produce the deliverable shrinks dramatically.

This is a pattern I teach explicitly: ChatGPT for certain tasks, Claude for others, Gemini for others still. The right tool for the right job.

"When you get done with one tool and you are stuck," I tell clients, "take the full thread and say, 'Hey, ChatGPT did not get anywhere with this. Can you help me, Claude?' And then Claude is like, 'Oh yeah, it is this.' That is how I troubleshoot. You can take the screenshots, put it in there, and then say what is going on."

Why Custom GPTs Unlock a Mindset Shift

The technical capability of custom GPTs matters. But the mindset shift they trigger matters more.

When a business owner builds their first custom GPT, something changes in how they see AI. They stop being a consumer of AI capabilities and start being a builder. They start looking at their business through a different lens: not "what can AI do for me?" but "what tool can I build to solve this specific problem?"

Kristen articulated this shift better than most: "AI is not taking your job. There will always be a human component to it. If you are able to innovate, you can think of creative ways that AI can accelerate and complement your work. Those who are just 'doers' without a flexible mindset are the ones whose jobs will be replaced."

That is a sophisticated understanding. She did not learn it from a course or a keynote. She learned it by building things, breaking things, and iterating until they worked. And then teaching her business partner how to do the same.

Platform-Specific GPTs

One of the more advanced applications we built during the consulting team's sessions was platform-specific content GPTs. The idea is simple in concept but powerful in execution.

"YouTube is top of funnel," I explained during one of our sessions. "You do long-form content, like a podcast. Then it is clipped up. We take the most exciting viral parts of the podcast, three to five clips, and those go on YouTube Shorts, but the Shorts also go on all the other platforms: Instagram, LinkedIn, and TikTok. Each platform has its own GPT. The LinkedIn GPT will take that transcript, put it in, and it will spit out the right platform-specific format."

One piece of content. Multiple platforms. Each platform gets a custom-formatted version that matches its norms and audience expectations. LinkedIn copy reads differently than Instagram captions. TikTok descriptions have different conventions than YouTube descriptions. A single GPT cannot optimize for all of them simultaneously. But a suite of platform-specific GPTs can.

This is where custom GPTs move from convenience to competitive advantage. Instead of a social media manager spending an hour reformatting content for each platform, the GPT handles the adaptation. The human reviews, approves, and posts. The creative strategy is still human. The mechanical formatting is not.

The Bot Economy

Beyond personal productivity GPTs, we also explored something more ambitious: building AI bots that serve clients directly.

Jean described her vision during a session: "I want the bot to be able to do two things. One is I would like for some of my clients calling me and saying, 'Help me on this,' I want them to write to the bot and say, 'Hey, I have this problem with a team member.' And then the bot provides a comprehensive way of looking at it. And then the second thing I want to do is, once we have tested all of it, I would like for us to sell it."

This is the progression I see with clients who fully embrace AI. They start by using it for their own work. Then they build tools for their team. Then they realize they can build tools for their clients. And then they realize those tools can become a revenue stream.

A consulting bot that handles first-pass client questions does not replace the consultant. It extends their reach. It handles the 80% of questions that have well-established answers, freeing the consultant to focus on the 20% that require real expertise. And if you can sell that bot as a subscription, you have created recurring revenue from your intellectual property without adding hours to your calendar.

The Knowledge Base Principle

One critical lesson we worked through was how to build effective knowledge bases for custom GPTs and bots.

"It cannot be too much," I explained, "because then it may not pull what you need at the time. So we want to make sure that what we give it is the most important information. Upload the minimum documents. What is the bare minimum that you feel like it has to at least have? We start with the bare minimum, and then we try to break it."

This is counterintuitive. Most people think more data equals better AI performance. The opposite is usually true for custom GPTs. A focused knowledge base with the right 10 documents will outperform a bloated one with 100. The AI can find what it needs faster, and it is less likely to pull irrelevant context into its responses.

We start small and stress-test. Ask it questions designed to find the gaps. When it gets something wrong, add the specific document that would fix that answer. This iterative approach builds a tight, effective knowledge base that produces reliable results.

What This Means for Your Business

Here is what I tell every business owner who is still on the fence about custom GPTs.

You already have the expertise. You already know your industry. You already have processes, documents, templates, and frameworks that make your business work. Custom GPTs let you encode that expertise into a tool that multiplies your capacity.

Start with one GPT for one task. Do not try to build a comprehensive AI ecosystem on day one. Pick the thing you do most often, the task where you find yourself explaining the same context over and over, and build a GPT for it.

If you are a consultant, build a GPT that drafts your proposals. If you are in financial services, build a GPT that formats your client reports. If you manage a team, build a GPT that generates meeting agendas from your notes. One tool. One task. Master it. Then build the next one.

Kristen went from learning the basics to building tools that impressed experienced executives. She did it in a few sessions. Not because she is a technical person. Because she is a business person who recognized that building with AI is now a core business skill.

The question is not whether your competitors will figure this out. They will. The question is whether you will be the one showing them how it is done, or the one being shown.