Introduction We’ve entered the age of abundance. More data. More models. More automation. And now, more people using AI than ever before. But abundance has a dark side — slop. AI slop is what happens when people use artificial intelligence as a shortcut for thinking rather than a tool for
Introduction Agentic AI isn’t just another generative model—it’s a system that can act, decide, and operate within your workflows. The question is no longer whether you can use AI, but where, how, and why you let it do so. This post maps the real decision environment your
We’re past the AI hype cycle. Most teams know they need to “use AI,” but I have a hot take after working with a few groups now. Some may be starting in the wrong place: with their data. That’s like starting a fire with wet wood. Technically possible.
The future doesn't reward availability. It rewards value. AI is shifting the center of gravity from who can respond the fastest to who can think the deepest. But deep work doesn’t happen in the glow of notifications or during back-to-back status calls. If we want
We’re in a new age. Not the information age. Not the AI age. The pirate age (stay with me, it's funner that way). R. Buckminster Fuller saw it coming. In Operating Manual for Spaceship Earth, he described how the world pushed people into narrow lanes—specialists with
Most people treat their body like a mystery. I treat mine like a system. Artificial intelligence is the coaching assistantthat keeps the whole thing running—alongside the human coaches that still matter most. This blog is for coaches wondering how to deal with the looming threat of replacement via AI.
AI adoption doesn’t happen overnight. It happens in phases, shaped by emotion as much as capability. For most people, the journey from hearing about AI to actually using it confidently isn’t a single “aha” moment—it’s a curve. A human curve. It starts with fear or doubt,
In the era of artificial intelligence, executive decision-making is entering a new phase—one where speed, clarity, and confidence matter more than ever. What once took months now demands action in days. Markets shift quickly. Customer expectations evolve in real time. The burden on leadership has never been greater.
Introduction In Part 1, we covered the foundational steps for creating AI personas—how they serve as structured thought partners, refine ideas before human feedback, and accelerate decision-making. Now, in Part 2, we’ll explore advanced techniques: fine-tuning personas for deeper accuracy, integrating external knowledge, and scaling them
Introduction AI personas offer a unique way to gain structured feedback on ideas, projects, and workflows without waiting for human input. We all have colleagues or friends we turn to for specific perspectives—someone for tough love, another for high-level strategy, and yet another for detailed critique. AI personas
Customer segmentation used to be simple—marketing teams updated audience profiles once a year, maybe quarterly if they were aggressive. Now, that model is obsolete. AI isn’t just analyzing customer behaviors anymore—it’s generating new audience segments before they exist. Traditional segmentation relies on past data, but AI-
AI is everywhere. It’s helping people write emails, diagnose diseases, create marketing copy, and even analyze the weird noise coming from your car. But here’s the uncomfortable truth: AI isn’t making you smarter. If anything, it’s making people lazier thinkers. We already saw it happen with