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In integrating AI into my courses, I’ve had experience using Custom GPTs. They can be very beneficial over broad AI use as they focus specifically on a single task or project to help the user – whether student, professor, or professional. For example, I have used JobsGPT in a previous blog post as a way to help predict how AI will impact the skills marketers need in the future so that I can adjust my course material.

I was also recently inspired by an article in Chronicle of Higher Ed. In “Teaching: Can AI actually help students write authentically?” Beth McMurtrie shares how Jeanne Beatrix Law, director of composition at Kennesaw State created a custom GPT Writing Guide Assistant. She found a way to engage students with AI to teach critical thinking and the writing process through prompting versus having AI write for students.

I also realize my students need to gain experience working with AI such as custom GPTs and agents to prepare for today’s marketing jobs. The latest CMO survey reports use of generative AI in marketing increased by 116% since 2024 – now 15% of marketing activities. As a hopeful sign, the same survey reports companies are still growing their marketing teams – 5.3% last year and predicted 5.0% in 2025.

The Primary Goal of My GPT

My goal in creating the Social Media Audit GPT was to provide students with a learning assignment to teach step-by-step an important course concept. Social media audits are an amazing strategic tool but students often struggle to understand them completely – even with new examples in the 4th edition of my Social Media Strategy book.

The custom GPT takes them through the process of completing a main assignment through prompting, and they can ask questions at any time along the way. It also has the benefit of focusing on source materials to ensure accuracy.

To create the Social Media Audit GPT I gave it an article I wrote on this blog last year detailing the process for conducting a social media audit with a social media audit template. I see the custom GPT as a great support to in-person instruction giving each student access to how I would tutor them in this key concept 24/7. For those using my Social Media Strategy text in classes, this is a great supplement to support your instruction.

Social Media Audit Template To Improve Social Media Marketing Strategy. — I trained the GPT on the Social Media Audit template from my Social Media Strategy book.

Secondary Goals of My GPT

A secondary goal was to show students how to use AI responsibly to empower their learning, not harm it. Creating a custom GPT is a key demonstration of AI integration and teaching AI literacy versus AI bans labeling all AI use as cheating. This helps teach responsible AI use for students tempted to use AI to complete assignments.

Another secondary goal is to teach students how to work with AI as a partner in developing marketing strategies. The GPT is not a replacement for those creating a social media strategy for an employer or client. The AI agent doesn’t complete the audit.

I instructed the GPT to not collect data for the user it to prompt them to formulate their own insights. The real value of a social media audit is getting into each social media platform and seeing what’s happening with your own eyes. I built the AI as a strategy development assistant demonstrating how students or professionals can use custom GPTs and AI agents in their future or current marketing careers.

How I Created The Custom GPT

I had a working model of this Social Media Audit GPT several weeks ago as a Microsoft Copilot Agent (AI-powered assistant), but it was stuck inside my institution – you can only share with individuals or groups in your organization/company. Google Gemini Gems (custom AI experts), and Anthropic Claude Projects (curated sets of knowledge) have similar limitations in that your custom AI agent, gem, or project can only be shared internally within your organization.

Only OpenAI’s custom GPTs can be published on the open web and mobile app to be shared publicly. Anyone can use Custom GPTs with a free ChatGPT account, but to create a custom GPT you need at least ChatGPT Pro (at $20 a month). Before this, all my AI use was limited to only models and tools that I could access for free (so my students wouldn’t have to pay).

Yet with custom GPTs, I was in the opposite situation. As Marc Watkins explained recently, while OpenAI and Google are giving away premium subscriptions to students, they have not extended that offer to professors. I finally secured some funding to purchase a ChatGPT Pro account.

One thing I like about my blog is I own it and control what is published there. With this GPT I’m relying on OpenAI to host for me. If I downgrade to a free account, I can’t access it. Thus, I’m locked into paying $20 a month to manage and update. OpenAI, if you’re reading, please extend the free Pro account to educators, not just students.

GPTs Are Essentially Good Prompts

What is a custom GPT? OpenAI says “a version of ChatGPT for a specific purpose.” MIT Sloan explains, “Custom GPTs are helpful AI tools tailored for specific domains or contexts. GPTs differ from standard chats through ChatGPT due to custom instructions and the ability to keep a knowledge base in addition to what ChatGPT has been trained on. This allows users to create a custom GPT to address a specific need that might be hard for ChatGPT to achieve on its own. The process … requires no code, and involves using specific prompts and your own data to provide insights into a particular field.”

AI Prompt Framework Template with 1. Task/Goal 2. AI Persona 3. AI Audience 4. AI Task 5. AI Data 6. Evaluate Results. — AI Prompt Framework Template for writing good prompts – what you need to create a GPT.

Creating a custom GPT is essentially writing a good, detailed prompt that users of the GPT will begin a chat from that background and knowledge. In creating my Social Media Audit GPT I wrote a long prompt explaining what I wanted it to do following my AI Prompt Framework of Task/Goal, Persona, Audience, Task, Data, and Results.

In the image below I marked up my GPT prompt to sections of the AI Prompt Framework. The text on the top was my original building the Copilot Agent and adjustments. The text in the bottom right is the adjustments I made in custom GPT.

Custom GPT and Copilot Agent prompts to create Social Media Audit GPT.

Test Your GPT To Make Changes

An important part of this process is to test your GPT as a typical user to see how well it performs. If you find something wrong simply tell the GPT what you like and what needs to change. You can test it in a Preview column next to where you instruct the GPT.

One of the first adjustments I made was to clarify that I wanted the GPT to have the user visit each social platform and report results. An earlier version searched the web and reported back its analysis. I tested the social audit GPT with a running brand (see below).

I like to run so I chose to test Social Media Audit GPT with Saucony running shoes and apparel

Once you’ve tested the GPT you’re ready to publish! Click the “Create” button in the top right. Then click “Share” at the top right. In that pop-up screen select “Only me,” “Anyone with the link.” or “GPT Store access.” After choosing GPT Store your GPT will be available at https://chatgpt.com/gpts for anyone with a ChatGPT account to access. Search by name or click “My GPTs.”

The custom GPT you make is only limited by your discipline knowledge, the data you provide, and the strength of your prompt.

Have you explored creating a Copilot Agent, Gemini Gem, or Open AI Customer GPT? How might you use this in your teaching for professional practice?

Please try the Social Media Audit GPT and share any feedback you have. A great feature of custom GPTs is you can revise and update.

This Was Human Created Content!

Years ago, a boss called me into his office and said, “You’re doing the best work in the agency. Your campaigns are exceeding results, winning creative awards and you deliver on every challenging project, but … you suck at presentations.” Ouch!

Who wouldn’t love to hear the first part, but the second? While it hurt, I was grateful because with the critique came an invitation to improve. I was curious enough to want to learn and found a Dale Carnegie High Impact Presentations course. I spent three days learning, being videotaped, and watching back in a hotel conference room full of strangers critiquing me.

From there, presenting was a strength. I would lead high-stakes presentations for clients and new business pitches. Today, I rely on those skills every week in the classroom as a professor. In my career, most advancements came from critique and curiosity. I needed colleagues and mentors as thinking partners, not people pleasers. What does this have to do with AI?

Last week ChatGPT-4o was updated to improve its personality, but the result was a people pleasing sycophant that loved everyone’s ideas including validating flat earth theory and recommending investing $30K in a “poop on a stick” product idea. -Image generated via prompt from Gemini Flash 2.0 Image Generator in Google AI Studio.

Flattery Will Get You Nowhere.

AI expert Ethan Mollick’s latest Substack “Personality and Persuasion” discussed how a small tweak in ChatGPT-4o drew attention because the LLM became eager to please users with agreement and flattery. Mollick and others said AI became a sycophant and everyone’s biggest fan.

AI with a pleasing personality isn’t a bad idea, but it is when responses skew overly supportive and disingenuous. Beebom reports that the ChatGPT update agreed to almost anything. One user received validation for the flat Earth theory. A Redditor shared a screengrab of how ChatGPT told him “poop on a stick” was a brilliant new product idea and he should invest $30K on it!

What’s wrong with fake flattery? AI or human sycophants insincerely praise to get reward. Thus, their feedback is distorted. Only hearing praise, not honest input, leads to poor decisions, mistakes, and maintaining the status quo when change is needed. It discourages fresh ideas, critical thinking, and stifles innovation.

A reason big companies become less innovative is that people become afraid to question current standards, the way things are done, and the boss. That’s fine if the environment the business was created in never changed, but markets change constantly. Businesses that don’t adapt fail to upstarts not afraid to ask, “Why?” and “Why not?” Remember Blockbuster before Netflix?

Lack of innovation can also come from focus on short-term customer, client, boss satisfaction. Customers and clients often don’t know what’s best. In aiming to please them you end up delivering worse results, not better. Aren’t you the expert? OpenAI arose from challenging convention, but in a twist, they created a sycophant focused on conventional customer satisfaction surveys. Appeasement can be a form of fake flattery.

The Problem With User Satisfaction.

The GPT-4o update was to “improve intelligence and personality” based on user feedback. But OpenAI said, “… in this update, we focused too much on short-term feedback … as a result, GPT-4o skewed towards responses that were overly supportive but disingenuous.“ ChatGPT’s default personality became too sycophantic.

This unexpected result is a good reminder that generative AI is still an experiment, and we’re the participants. LLM developers often don’t know why generative AI models do what they do. Unlike traditional coding, they guide results with reward mechanisms.

This reminds me of an attempt to improve healthcare that led to a focus on making people happy, rather than making them well. Alexandra Robbins reported that when Department of Health administrators based 30% of Medicare reimbursement on patient satisfaction scores, the most satisfied patients were significantly more likely to be hospitalized than less satisfied patients. And the most satisfied were more likely to die in the next four years!

In my marketing advertising career, giving clients what they wanted, ads that talked about the product, not the customer, and looked like competitors’ ads didn’t lead to the best results. The best ideas stood out as different and were the hardest to get approved – why I needed presentation skills! They didn’t do things the way they’ve always been done, asking “Why?” and “Why not?”

AI As Co-Thinker, Not People Pleaser.

In my last two posts on AI Agents and Vibe Marketing, I’ve been using AI more in my process. In working on this post, I did research on my own but also relied on discussions with ChatGPT as a thinking partner as I asked questions, clarified definitions, and researched more deeply.

I found AI co-thinking is very good at helping me see patterns between seemingly diverse subjects and disciplines. As Paul Roetzer said in The Artificial Intelligence Show, LLMs can’t create something new. AI can connect dots but can’t invent. Yet in working with a human like me, I can prompt it into new directions. My conversations with ChatGPT did just that inventing a new AI framework.

Here was my prompt thought process:

What is a sycophant?
Are sycophants good for organizations and society?
What are good ways to use AI to buffer against sycophantic thinking?
How can this stifle or encourage curiosity?
ChatGPT asked me, “Would you like a framework or checklist for using AI in ways that protect curiosity and intellectual integrity?” I said, “Yes.”
It gave me a rough framework. I asked, “Where did you get this AI & Curiosity framework?
It said, “I created the AI & Curiosity Framework specifically for your question–it’s an original synthesis drawing on best practices from critical thinking pedagogy, AI-human collaboration principles, group dynamics research, and practical patterns from how AI tools are being used in education, leadership, and decision-making.”
I took that rough framework, tweaked it and created the template you see below.

This is an example of “vibe thinking,” where AI enabled me to research, learn, and iterate my thoughts quickly, leading to this AI Curiosity & Critique Framework.

AI Curiosity & Critique Framework

This AI framework will help you go beyond avoiding sycophant AI that stifles innovation to using AI to augment thinking to increase and speed up innovation. Don’t take a passive role in AI use. Follow the ACTIVE framework to expand creative exploration, challenge assumptions, and make strategic decisions free of marketing echo chambers.

Ask divergent questions, brainstorming unexpected campaign angles, and prompt for contra views or audience reactions, such as “What would Gen Z hate about this campaign?” Challenge assumptions, having AI critique messaging and target persona, or uncover untested assumptions, such as “Is our messaging convincing to a skeptical Millennial parent?” Track diverse inputs by testing perspectives and how different demographics may interpret messages, such as “How would this headline sound to a retired Baby Boomer in the South?”

Invite dissenting viewpoints, consider alternative views before implementation, and consider potential backlash, such as “Generate critical responses to this campaign from activists.” Validate Don’t Venerate taking AI at face value. Test with real people, verify facts and recommendations, such as “Where did you get this information? Provide a source.” Embed inquiry into the process using AI for ideation, postmortems, and customer empathy checks, such as “Simulate skeptical customer reaction to our ad.”

AI For Safe Explorations In Learning

Using AI for curiosity and critique, not to provide answers, can improve learning. It creates a safe place for exploration and a low-stakes environment to test ideas. It’s an easy place to ask questions students might not be comfortable asking in public.

I’ve had great success with this in my Digital Marketing class using NotebookLM as an AI tutor. Students ask as many questions as they want of my text and online resources – things they may not feel comfortable asking in class or me. They can test their wildest out-of-the-box ideas. Improved understanding of concepts and performance on assignments has been notable.

Whether you’re a marketing professional or professor, this AI framework will help you get somewhere flattery alone will not. Instead of AI first, it’s an example of an AI forward mindset where AI is used to improve human work, not replace it. If there’s something you suck at AI can help – even presenting.

This Post Was 90% Human Written. I used ChatGPT to research and explore topics while iterating and testing my thoughts to quickly pull together the diverse topics that helped me create this AI Framework. I tweaked the suggested framework, and the main writing was my own. I used ChatGPT to optimize my headline for SEO and engagement.