This episode is all about custom GPTs: What they are, what they can do, and how to “build” one. If you’ve ever wished you could clone yourself, this is basically how you do it. In this episode I share how I created my own ChatGP-TA for the Instagram Intensive, the files and instructions I used to make it sound like me, and the simple steps you can take to “clone yourself” without writing a single line of code. Along the way we talk vectors, transformers, input quality, and how to set capabilities so your Custom GPT does exactly what you want.

This episode takes a look at the hype surrounding AI and asks a simple question: Are we in a bubble? Spoiler alert: ABSOLUTELY. To make sense of it, I dig into the history of the dot-com boom and bust, walk through today’s AI financials, and explore what it might mean for companies, investors, and everyday people like you and me.

In this episode of ChatGPT Curious I share a handful of ChatGPT features that you might not know about, and that I think you might find genuinely useful. These aren’t “hidden gems” or shiny distractions, they’re tools and settings I personally use and that I believe can improve both your user experience and the model’s outputs. From release notes and memory controls to project settings and the surprisingly powerful Study Mode, this is a practical tour of features that can actually make a difference.

In this episode we’re talking about what it really takes to get ChatGPT to do what you want. From clarifying your own thoughts to understanding the basics of prompting, this is a how-to guide without the hoopla. Really though, it’s not that serious. Whether you're asking it to write an email or act as your assistant, specificity and clarity are the name of the game.

This episode is about giving you a clear, simple definition of a word that gets thrown around constantly: AI. You’re hearing it in every commercial, on every app, and in every new feature rollout. But what is it, really? I share a plain-language definition — “software that can guess” — contrast everyday examples of AI with simple automation, and give quick context on where the term came from, how regulating agencies define it, what is meant by “agents” and “AGI”, and how close we realistically are to what Terminator predicted. (Spoiler, not close at all.)

In this episode I give an introduction to using ChatGPT for content creation with a focus on practical strategies for repurposing your own work. You’ll hear about reverse prompting, using Projects to save instructions, and how to keep your taste and voice at the center of what you create.

In this episode, I dig into whether you can trust ChatGPT, and what that question reveals about trust in general. From model changes and user backlash to the three pillars of trust (benevolence, integrity, competency), I share why double-checking is anon-negotiable and how personal responsibility plays into using AI. We talk about media incentives, misinformation, and why “important” is a slippery, subjective word when it comes to verifying the answers that ChatGPT gives you.

So… is ChatGPT actually coming for your job? In this episode, I walk you through the GPT-5 release, what’s new, what’s noise, and why I think most folks won’t even notice a difference. We’ll talk about how AI is being used at work, why the headlines can be misleading, where the tech still falls short, and why job-loss predictions are far from straightforward.

In this episode of ChatGPT Curious, I lay the groundwork for understanding what ChatGPT actually is, without getting too lost in the weeds. I break down key terms like LLM and parameters, explain how the model was trained (hint: lots of math), why it sometimes spits out wrong info, and what all of this means for how you use it. I also touch on the environmental cost, what the free vs. paid versions can actually do, and how to think critically about its outputs. If you've ever felt a little confused, a little curious, or both, this one's for you.

In this episode I dig into the environmental impact of using ChatGPT: energy use, water consumption, and carbon emissions. I walk through the research, acknowledge the risk of whataboutism, and explain why comparisons to other systems matter when we're talking about true impact. Adopting a both/and approach, this episode is absolutely not about letting ChatGPT off the hook, it’s about putting things in perspective so we can take action on what will actually move the needle.