Even livestreams need rehearsals. Every Thursday at 1 PM ET, you can catch me, Katie, and John (usually) on our Trust Insights livestream. Tomorrow, for example, we’re looking at the new plugins feature in Claude Cowork. (and they are very cool) What you don’t see is the prep work on Wednesday night. Usually there’s 2-4…
Summary In today's episode, I explore the tension between AI automation and human creativity through the lens of neuroscience. Here's what this means for you. You can maximize your impact by using AI to handle high-probability tasks while focusing your own energy on low-probability, emotional connections. You'll also learn these concepts: the difference between probabilistic…
Sometimes the secret sauce is just a collection of little things. In AI, a lot of folks understandably focus on prompts – they’re the recipes that AI uses to cook with. But anyone who’s spent more than a minute in a kitchen knows that things like ingredients, appliances, chef skills, menu, etc. all matter. When…
Summary In today's episode, I explain why AI models lack long-term memory and how you can solve this problem. Here's what this means for you. You can build more effective workflows by providing the context your AI needs to succeed across multiple sessions. You'll also learn these concepts: the technical reasons behind AI statelessness, the…
_Almost Timely News: 🗞️ The Five Levels of AI Enablement (2026-03-22) :: View in Browser_ The Big Plug 👉 I’ve got a new course! GEO 101 for Marketers. 👉 Just updated! The Unofficial LinkedIn Algorithm Guide, March 2026, now with new information straight from LinkedIn! Content Authenticity Statement 100% of this week’s newsletter content was…
NotebookLM in Gemini is the money. Here’s what I mean. Google’s Gemini 3.1 is a crazy smart model, especially the pro version. But even with a 1 million token context window (short term working memory that can hold about 750,000 words), it can’t remember everything. But not too long ago, Google enabled NotebookLM notebooks as…
Summary In today's episode, I examine the challenges of building AI systems for stock market prediction. Here's what this means for you. You can avoid the pitfalls of chasing market sentiment by using AI to build specialized expertise in stable, fundamental sectors. You'll also learn these concepts: why the stock market functions as a lagging…
Let’s talk about 3 kinds of thinking in AI today: unary, binary, and trinary. Unary: “AI, do this thing for me.” Binary: “AI, which will my customer like better, A or B?” Trinary: “AI, give me 3 different ideas for this thing.” Most folks when using AI are doing unary thinking. Do this thing. Make…
