Better Questions, Better Results

What’s the Advantage to Those Who Start Using AI Earlier? Why early adopters are shaping the rules of the AI game As AI reshapes industries and workflows, those who started earlier aren’t just ahead—they’re building the road others will travel. This post explores the compounding advantages of early AI adoption and how the latecomers can still catch up. Expect insights on competitive edges, learning curves, and real-world dynamics. If you’re wondering whether being early to AI matters, the keyword is: momentum. The Compounding Power of Early Adoption Early adopters of AI technologies gain an edge not only in tools, but in mindset. They begin accumulating data, refining workflows, and developing institutional know-how long before AI becomes a norm. Like compound interest in finance, small consistent improvements over time create an exponential gap. Why This Matters: Experience builds efficiency : Teams familiar with AI tools work faster and make fewer mistakes. Data advantage : Early use...

Why Is Artificial General Intelligence a Dangerous Distraction? How to balance ambition with impact in the race for smarter machines. 📦Framing Artificial General Intelligence (AGI)—a system that can think, learn, and reason across any domain like a human—has long been cast as the “endgame” of AI. Billions in investment now flow toward this vision. But here’s the dilemma: while AGI captures headlines, narrow AI is already delivering real-world impact—detecting cancers earlier, accelerating drug discovery, reducing emissions, and strengthening cybersecurity. The challenge isn’t that AGI research is useless. In fact, many foundational advances (like attention mechanisms and transfer learning) came from work framed around general intelligence. The challenge is  emphasis and sequencing . Treating AGI as an imminent engineering goal risks diverting scarce resources from proven, high-impact applications. The smarter path is prioritizing measurable benefits now, while pursuing fundamental...

What Questions Should We Be Asking AI? Rethinking Intelligence: Why the Questions Matter More Than the Code Before we unleash AI into the world, we must first tame how we think about it. What should we ask? What should we avoid? And who gets to decide? The question “What questions should we be asking AI?” isn’t just about prompt engineering—it’s about responsibility, foresight, and power.  The quality of our questions determines how AI evolves, who it serves, and who it ignores. From predictive policing to medical diagnostics, our interactions with AI are shaped not only by the data and code—but by the questions that went unasked. Why Now? We’re living through a  “question crisis.”  AI systems are making real-world decisions based on poorly framed problems. Healthcare AI : IBM’s Watson for Oncology offered flawed recommendations because it was trained on hypothetical cases from a single hospital. Missing question: Is our data globally representative? Criminal Justice : To...

Can AI Help Get You Into a Flow State? From Algorithms to Alpha Waves: How Machines Can Boost Human Focus The idea of “flow”—that hyper-focused state where you lose track of time and perform at your peak—has fascinated athletes, artists, and knowledge workers alike. But can artificial intelligence help us  engineer  this elusive mental state? This post dives into how AI tools and systems are being designed to optimize conditions for flow, blending neuroscience, psychology, and technology. With the rise of smart tools and environments, the path to peak performance might just include a little machine learning. What Is Flow—and Why It Matters Coined by psychologist Mihaly Csikszentmihalyi, flow is that sweet spot where challenge meets skill. You’re deeply immersed, lose sense of self-consciousness, and feel a sense of mastery and purpose. It’s like being “in the zone”—time slows, distractions fade, and productivity soars. Research shows flow leads to: Higher productivity Greater ...