Watch here: https://youtu.be/NQHTdb5_Af8

Craig and Emmanuella tackle the burning question: Is AI just another dotcom-style bubble waiting to burst? The Bubble Debate Emmanuella has been hearing concerns across industries that AI might be overhyped like the dotcom boom. She wonders if people deep in AI dismiss these concerns because admitting it would hurt them. As an outsider, she wanted an objective analysis. Why This Time Is Different The Dotcom Lesson: Jeff Bezos noted that industry movements require experimentation, which costs money. During dotcom, infrastructure (fiber optic cables) survived even when companies failed. Amazon shares dropped from IPO to $6, but one original share is now worth ~$48,000. Bubbles punish speculators but reward those who identify real value. AI's Key Distinctions: Actual usage: Unlike hypothetical dotcom projections, AI infrastructure is used immediately as it's deployed Tangible products: OpenAI went from zero to $500 billion in two years with something people actually use daily Fast prototyping: At the Indigenous Australian Datathon Conference, participants built working health/food systems in 1.5 days (five years ago, they just made PowerPoint slides) The Three-Layer Framework Infrastructure Layer (Bottom): Data centers and compute being used and paid for as deployed. Competitive pressure will drive efficiency. This is real, not hypothetical. Business Layer (Middle): Companies building on infrastructure—lots of experimentation, not all will succeed. This is where the "bubble" risk lives. Consumer Layer (Top): People using AI daily for research, scheduling, advice. Already embedded in life with genuine utility. What Determines Winners The pets.com cautionary tale: They had a great name but terrible user experience. PetSmart crushed them with a better website. Winners marry user experience with new tech. Losers trade on hype. Companies that survived dotcom (Amazon, early Yahoo, later Facebook) had genuine utility that compelled continued use. The Democratisation Opportunity You no longer need coding skills—just understand systems, business, and customers. Barriers to entry have collapsed. Emmanuella has been buying shares for her daughters since birth; what might fund one startup could now fund 10 experiments. The Reality Check No substance = failure. Hypothetical AI companies without humans putting in grunt work won't succeed. Value requires the end-to-end human experience—people identifying problems and experiencing solutions. Don't judge success at one point in time. See what survives market corrections. Takeaway This isn't a bubble—it's a punctuated equilibrium. Infrastructure is solid, consumer utility is real, but not all businesses building on top will succeed. If you identify genuine long-term value and ride out volatility, history suggests patience pays off.

Watch here: https://youtu.be/Je3ynVTQrXs

Craig builds a meditation app in 15 minutes to demonstrate how AI is fundamentally changing our relationship with smartphones—and potentially making traditional apps obsolete. The Meditation App Experiment The Problem: Craig was frustrated with his meditation app constantly asking him to log in, share data, and navigate unnecessary features. He just wanted something simple: a timer that chimes at the start, middle, and end. The Solution: Using Claude AI, he built a custom meditation app in approximately 15 minutes (plus deployment to his phone). The entire process: Created a simple meditation timer with specific requirements Made it "woody zen" in appearance through natural language prompting Deployed as a Progressive Web App (PWA) to his Google Pixel 9 Shared all code publicly on GitHub—written entirely by AI, including instructions The Result: A functional, personalized meditation app that does exactly what he needs, nothing more. The Death of Apps Thesis Craig argues we're witnessing the beginning of the end for traditional smartphone apps. His reasoning: Common Problems Get Solved: Throughout tech history, universal problems eventually become utilities (like cloud computing replacing everyone building their own data centers). Apps are next. Ephemeral Code: What took weeks to build now takes hours. Soon, AI will generate apps on-the-fly to solve immediate problems, then either: Disappear after use, or Join a library for future retrieval when someone needs the same solution The Future Interface: Instead of hunting through app stores, your phone becomes a true personal assistant. You state a problem ("I want to tune my guitar"), and AI generates the solution instantly—no installation, no data sharing, no login screens. The Deloitte Academic Paper Incident Emmanuella raises the recent controversy where Deloitte was hired to analyze problematic code but instead published an academic paper. Her analysis: The wrong command was given. Key insight: Deloitte hired a team and used AI to do something it was told to do, but the initial instruction was incorrect. The tool served the wrong purpose because the human question was wrong. Deep Philosophical Questions On Prompting as a Skill Emmanuella observes that prompting AI effectively requires: Specificity and brevity Iteration and refinement Understanding what outcome you actually want Consideration of whether the purpose is appropriate She predicts schools will need entire subjects dedicated to prompting. On Logic vs. Intelligence A fascinating historical example: When computers were introduced to Black and Hispanic communities in the US, IQ scores increased—not because students became "smarter," but because their thinking adapted to computational logic (which IQ tests measure). Emmanuella's concern: We're optimizing for computational logic at the expense of emotional, human, and spiritual intelligence. This imbalance contributes to rising anxiety and depression. On Productivity vs. Equilibrium Self-identifying as a "human puddle," Emmanuella questions whether productivity gains are worth the cost: "Is our time connecting and being undermined at the expense of productivity?" On Creativity Craig was asked by a senior leader: "Is creativity just remixing old ideas, or is it bigger?" His answer: Creativity pulls inspiration from many sources, sometimes mysterious ones. It's bigger than remix. The human element matters—AI is built on systems like IQ tests that channel curiosity into predictable paths. On Tech Waste Emmanuella wonders if we'll eventually develop consciousness about AI waste the way we have about plastic—recognizing that technology costs the earth something and asking whether uses are frivolous. Cultural Differences Craig shares intriguing research: Anglo-Western countries are the most pessimistic about AI in multiple studies. East Asian and non-English speaking countries tend to be far more bullish on the technology. This raises questions about cultural values, waste creation, and how different societies conceptualize technology's role. Key Takeaway Always ask: Who is the end user, and what is the ultimate goal? Technology must serve a human purpose. Learning to ask the right questions leads to appropriate prompts, which leads to useful outcomes. Without this foundational awareness, we risk building solutions to the wrong problems—or creating productivity that undermines human wellbeing. The future isn't about having better apps. It's about having AI that understands what we need and generates it on demand—making the smartphone finally live up to its promise as a true personal assistant. App code here: https://github.com/cclawton/cctest