On this episode of Crazy Wisdom, Stewart Alsop sits down with Guillermo Schulte to explore how AI is reshaping up-skilling, re-skilling, and the future of education through play, from learning games and gamification to emotional intelligence, mental health, and the coming wave of abundance and chaos that technology is accelerating; they also get into synchronous vs. asynchronous learning, human–AI collaboration, and how organizations can use data-driven game experiences for cybersecurity, onboarding, and ongoing training. To learn more about Guillermo’s work, check out TGAcompany.com, as well as TGA Entertainment on Instagram and LinkedIn.

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Timestamps

00:00 Stewart Alsop opens with Guillermo Schulte on up-skilling, re-skilling, and AI’s accelerating impact on work.
05:00 They explore play-based learning, video games as education, and early childhood engagement through game mechanics.
10:00 Conversation shifts to the overload in modern schooling, why play disappeared, and the challenge of scalable game-based learning.
15:00 Guillermo contrasts synchronous vs asynchronous learning and how mobile access democratizes education.
20:00 They reflect on boredom, creativity, novelty addiction, and how AI reshapes attention and learning.
25:00 Discussion moves to AGI speculation, human discernment, taste, and embodied decision-making.
30:00 They explore unpredictable technological leaps, exponential improvement, and the future of knowledge.
35:00 Abundance, poverty decline, and chaos—both from scarcity and prosperity—and how societies adapt.
40:00 Mental health, emotional well-being, and organizational responsibility become central themes.
45:00 Technical training through games emerges: cybersecurity, Excel, and onboarding with rich data insights.
50:00 Guillermo explains the upcoming platform enabling anyone to create AI-powered learning games and personalized experiences.

Key Insights

1. AI is accelerating the urgency of up-skilling and re-skilling. Guillermo highlights how rapid technological change is transforming every profession, making continuous learning essential for remaining employable and adding value in a world where machines increasingly handle routine tasks.
2. Play is humanity’s native learning tool—and video games unlock it for adults. He explains that humans are wired to learn through play, yet traditional education suppresses this instinct. Learning games reintroduce engagement, emotion, and curiosity, making education more intuitive and scalable.
3. Gamified, asynchronous learning can democratize access. While synchronous interaction is powerful, Guillermo emphasizes that mobile-first, game-based learning allows millions—including those without resources—to gain skills anytime, closing gaps in opportunity and meritocracy.
4. Emotional intelligence will matter more as AI takes over technical tasks. As AI becomes increasingly capable in logic-heavy fields, human strengths like empathy, leadership, creativity, and relationship-building become central to meaningful work and personal fulfillment.
5. Novelty and boredom shape how we learn and think. They discuss how constant novelty can stunt creativity, while boredom creates the mental space for insight. Future learning systems will need to balance stimulation with reflection to avoid cognitive overload.
6. Abundance will bring psychological challenges alongside material benefits. Stewart and Guillermo point out that while AI and robotics may create unprecedented prosperity, they may also destabilize identity and purpose, amplifying the already-growing mental health crisis.
7. AI-powered game creation could redefine education entirely. Guillermo describes TGA’s upcoming platform that lets anyone transform documents into personalized learning games, using player data to adapt difficulty and style—potentially making learning more effective, accessible, and enjoyable than traditional instruction.

On this episode of Crazy Wisdom, Stewart Alsop sits down with Terrence Yang to explore the US economy through the lens of federal net outlays, inflation, and growth, moving into China–US economic and military dynamics, the role of the dollar as a reserve currency, and how China’s industrial and open-source AI strategies intersect with US innovation; they also get into Bitcoin’s governance, Bitcoin Core maintainers, and what long-term digital scarcity means for money, security, and decentralization. To learn more about Terrence’s work, you can find him on LinkedIn.

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Timestamps

00:00 Stewart and Terrence open with the US economy, federal net outlays, and why confidence matters more than doom narratives.
05:00 They compare debt-to-GDP, discuss budget surpluses, and how the US once grew out of large debt after WWII.
10:00 Terrence explains recurring revenue vs. one-time income, taxes, tariffs, and why sustainable growth is essential.
15:00 Conversation turns to China’s strategy, industrial buildup, rare earths, and provincial debt vs. national positioning.
20:00 They explore military power, aircraft carriers, nuclear subs, and how hard power supports reserve currency status.
25:00 Discussion of AI competition among Google, OpenAI, Claude, and China’s push for open-source standards.
30:00 Terrence raises concerns about open-source trust, model weights, and parallels with Bitcoin Core governance.
35:00 They examine maintainers, consensus rules, and how decentralization actually works in practice.
40:00 Terrence highlights Bitcoin as digital gold, its limits as money, and why volatility shapes adoption.
45:00 They close on unit of account, long-term holding strategies, and risks of panic selling during cycles.

Key Insights

1. Federal net outlays reveal the real fiscal picture. Terrence Yang emphasizes that looking only at debt-to-GDP misses the deeper issue: the U.S. has run negative net outlays—more cash going out than coming in—for decades. He argues that sustainable recurring revenue, not one-time windfalls or asset sales, is what ultimately stabilizes a nation’s finances.
2. Confidence is an economic force of its own. Terrence warns that cultural pessimism can damage the U.S. more than high debt. Drawing parallels to Japan’s post-1990 stagnation, he notes that when people stop taking risks, innovation slows and economies ossify. The U.S. thrives on risk-taking, immigration, and entrepreneurial experimentation—and needs to preserve that spirit.
3. Inflation and growth are locked in a difficult balance. The conversation explores how current inflation remains above target while growth feels sluggish, creating a quasi-stagflation environment. Terrence questions whether the Federal Reserve should remain tied to a 2% target or adapt to new conditions, particularly when jobs and productivity remain uneven.
4. China’s economic strategy is broad, deliberate, and deeply practical. From inviting Western VCs in the 1990s to absorbing semiconductor know-how and refining rare earth materials, China built an industrial base that now rivals or surpasses U.S. manufacturing in many domains. Yet its provincial and real-estate debt highlight structural weaknesses beneath the surface.
5. The U.S. dollar’s dominance rests on military and institutional power. Terrence argues that reserve-currency status persists because the U.S. guarantees open trade routes and global security. Even countries with weak currencies prefer the dollar in black markets. Competitors like BRICS may want an alternative system, but replacing the dollar requires decades, not years.
6. Open-source AI is becoming a geopolitical tool. China’s strategy of flooding the world with strong, free, open-source models mirrors Linux’s global influence. Terrence notes that trust and transparency matter, since open-source code still requires knowledgeable maintainers who can verify safety, intentions, and alignment. This dynamic is now a competitive front in the AI race.
7. Bitcoin governance is both decentralized and fragile. Terrence explains that Bitcoin Core has very few maintainers and relies on a culture of trust, review, and distributed accountability. While Bitcoin works well as long-term “digital gold,” improvements are incremental, and the small number of developers poses systemic risks. He stresses that understanding governance—not just price—is crucial for anyone serious about Bitcoin’s future.

In this episode of Crazy Wisdom, host Stewart Alsop talks with Kevin Smith, co-founder of Snipd, about how AI is reshaping the way we listen, learn, and interact with podcasts. They explore Snipd’s vision of transforming podcasts into living knowledge systems, the evolution of machine learning from finance to large language models, and the broader connection between AI, robotics, and energy as the foundation for the next technological era. Kevin also touches on ideas like the bitter lesson, reinforcement learning, and the growing energy demands of AI. Listeners can try Snipd’s premium version free for a month using this promo link.

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Timestamps

00:00 – Stewart Alsop welcomes Kevin Smith, co-founder of Snipd, to discuss AI, podcasting, and curiosity-driven learning.
05:00 – Kevin explains Snipd’s snipping feature, chatting with episodes, and future plans for voice interaction with podcasts.
10:00 – They discuss vector search, embeddings, and context windows, comparing full-episode context to chunked transcripts.
15:00 – Kevin shares his background in mathematics and economics, his shift from finance to machine learning, and early startup work in AI.
20:00 – They explore early quant models versus modern machine learning, statistical modeling, and data limitations in finance.
25:00 – Conversation turns to transformer models, pretraining, and the bitter lesson—how compute-based methods outperform human-crafted systems.
30:00 – Stewart connects this to RLHF, Scale AI, and data scarcity; Kevin reflects on reinforcement learning’s future.
35:00 – They pivot to Snipd’s podcast ecosystem, hidden gems like Founders Podcast, and how stories shape entrepreneurial insight.
40:00 – ETH Zurich, robotics, and startup culture come up, linking academia to real-world innovation.
45:00 – They close on AI, robotics, and energy as the pillars of the future, debating nuclear and solar power’s role in sustaining progress.

Key Insights

1. Podcasts as dynamic knowledge systems: Kevin Smith presents Snipd as an AI-powered tool that transforms podcasts into interactive learning environments. By allowing listeners to “snip” and summarize meaningful moments, Snipd turns passive listening into active knowledge management—bridging curiosity, memory, and technology in a way that reframes podcasts as living knowledge capsules rather than static media.
2. AI transforming how we engage with information: The discussion highlights how AI enables entirely new modes of interaction—chatting directly with podcast episodes, asking follow-up questions, and contextualizing information across an author’s full body of work. This evolution points toward a future where knowledge consumption becomes conversational and personalized rather than linear and one-size-fits-all.
3. Vectorization and context windows matter: Kevin explains that Snipd currently avoids heavy use of vector databases, opting instead to feed entire episodes into large models. This choice enhances coherence and comprehension, reflecting how advances in context windows have reshaped how AI understands complex audio content.
4. Machine learning’s roots in finance shaped early AI thinking: Kevin’s journey from quantitative finance to AI reveals how statistical modeling laid the groundwork for modern learning systems. While finance once relied on rigid, theory-based models, the machine learning paradigm replaced those priors with flexible, data-driven discovery—an essential philosophical shift in how intelligence is approached.
5. The Bitter Lesson and the rise of compute: Together they unpack Richard Sutton’s “bitter lesson”—the idea that methods leveraging computation and data inevitably surpass those built from human intuition. This insight serves as a compass for understanding why transformers, pretraining, and scaling have driven recent AI breakthroughs.
6. Reinforcement learning and data scarcity define AI’s next phase: Stewart links RLHF and the work of companies like Scale AI and Surge AI to the broader question of data limits. Kevin agrees that the next wave of AI will depend on reinforcement learning and simulated environments that generate new, high-quality data beyond what humans can label.
7. The future hinges on AI, robotics, and energy: Kevin closes with a framework for the next decade: AI provides intelligence, robotics applies it to the physical world, and energy sustains it all. He warns that society must shift from fearing energy use to innovating in production—especially through nuclear and solar power—to meet the demands of an increasingly intelligent, interconnected world.

In this episode of Crazy Wisdom, host Stewart Alsop talks with Jessica Talisman, founder of Contextually and creator of the Ontology Pipeline, about the deep connections between knowledge management, library science, and the emerging world of AI systems. Together they explore how controlled vocabularies, ontologies, and metadata shape meaning for both humans and machines, why librarianship has lessons for modern tech, and how cultural context influences what we call “knowledge.” Jessica also discusses the rise of AI librarians, the problem of “AI slop,” and the need for collaborative, human-centered knowledge ecosystems. You can learn more about her work at Ontology Pipeline

 and find her writing and talks on LinkedIn.

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Timestamps

00:00 Stewart Alsop welcomes Jessica Talisman to discuss Contextually, ontologies, and how controlled vocabularies ground scalable systems.
05:00 They compare philosophy’s ontology with information science, linking meaning, categorization, and sense-making for humans and machines.
10:00 Jessica explains why SQL and Postgres can’t capture knowledge complexity and how neuro-symbolic systems add context and interoperability.
15:00 The talk turns to library science’s split from big data in the 1990s, metadata schemas, and the FAIR principles of findability and reuse.
20:00 They discuss neutrality, bias in corporate vocabularies, and why “touching grass” matters for reconciling internal and external meanings.
25:00 Conversation shifts to interpretability, cultural context, and how Western categorical thinking differs from China’s contextual knowledge.
30:00 Jessica introduces process knowledge, documentation habits, and the danger of outsourcing how-to understanding.
35:00 They explore knowledge as habit, the tension between break-things culture and library design thinking, and early AI experiments.
40:00 Libraries’ strategic use of AI, metadata precision, and the emerging role of AI librarians take focus.
45:00 Stewart connects data labeling, Surge AI, and the economics of good data with Jessica’s call for better knowledge architectures.
50:00 They unpack content lifecycle, provenance, and user context as the backbone of knowledge ecosystems.
55:00 The talk closes on automation limits, human-in-the-loop design, and Jessica’s vision for collaborative consulting through Contextually.

Key Insights

1. Ontology is about meaning, not just data structure. Jessica Talisman reframes ontology from a philosophical abstraction into a practical tool for knowledge management—defining how things relate and what they mean within systems. She explains that without clear categories and shared definitions, organizations can’t scale or communicate effectively, either with people or with machines.
2. Controlled vocabularies are the foundation of AI literacy. Jessica emphasizes that building a controlled vocabulary is the simplest and most powerful way to disambiguate meaning for AI. Machines, like people, need context to interpret language, and consistent terminology prevents the “hallucinations” that occur when systems lack semantic grounding.
3. Library science predicted today’s knowledge crisis. Stewart and Jessica trace how, in the 1990s, tech went down the path of “big data” while librarians quietly built systems of metadata, ontologies, and standards like schema.org. Today’s AI challenges—interoperability, reliability, and information overload—mirror problems library science has been solving for decades.
4. Knowledge is culturally shaped. Drawing from Patrick Lambe’s work, Jessica notes that Western knowledge systems are category-driven, while Chinese systems emphasize context. This cultural distinction explains why global AI models often miss nuance or moral voice when trained on limited datasets.
5. Process knowledge is disappearing. The West has outsourced its “how-to” knowledge—what Jessica calls process knowledge—to other countries. Without documentation habits, we risk losing the embodied know-how that underpins manufacturing, engineering, and even creative work.
6. Automation cannot replace critical thinking. Jessica warns against treating AI as “room service.” Automation can support, but not substitute, human judgment. Her own experience with a contract error generated by an AI tool underscores the importance of review, reflection, and accountability in human–machine collaboration.
7. Collaborative consulting builds knowledge resilience. Through her consultancy, Contextually, Jessica advocates for “teaching through doing”—helping teams build their own ontologies and vocabularies rather than outsourcing them. Sustainable knowledge systems, she argues, depend on shared understanding, not just good technology.

In this episode of Crazy Wisdom, host Stewart Alsop sits down with Harry McKay Roper, founder of Imaginary Space, for a wide-ranging conversation on space mining, AI-driven software, crypto’s incorruptible potential, and the raw entrepreneurial energy coming out of Argentina. They explore how technologies like Anthropic’s Claude 4.5, programmable crypto protocols, and autonomous agents are reshaping economics, coding, and even law. Harry also shares his experiences building in Buenos Aires and why hunger and resilience define the city’s creative spirit. You can find Harry online at YouTube, Twitter, or Instagram under @HarryMcKayRoper.

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Timestamps

00:00 – Stewart Alsop welcomes Harry McKay Roper from Imaginary Space and they jump straight into space mining, Helium-3, and asteroid gold.
05:00 – They explore how Bitcoin could hold value when space mining floods markets and discuss China, America, and global geopolitics.
10:00 – Conversation shifts to Argentina, its economic scars, cultural resilience, and overrepresentation in startups and crypto.
15:00 – Harry reflects on living in Buenos Aires, poverty, and the city’s constant hustle and creative movement.
20:00 – The focus turns to AI, Claude 4.5, and the rise of autonomous droids and software-building agents.
25:00 – They discuss the collapse of SaaS, internal tools, and Harry’s experiments with AI-generated code and new workflows.
30:00 – Stewart compares China’s industry to America’s software economy, and Harry points to AI, crypto, and space as frontier markets.
35:00 – Talk moves to crypto regulation, uncorruptible judges, and blockchain systems like Kleros.
40:00 – They debate AI consciousness, embodiment, and whether a robot could meditate.
45:00 – The episode closes with thoughts on free will, universal verifiers, and a playful prediction market bet on autonomous software.

Key Insights

1. Space and Economics Are Colliding – Harry McKay Roper opens with the idea that space mining will fundamentally reshape Earth’s economy. The discovery of asteroids rich in gold and other minerals highlights how our notions of scarcity could collapse once space resources become accessible, potentially destroying the terrestrial gold economy and forcing humanity to redefine value itself.
2. Bitcoin as the New Standard of Value – The conversation naturally ties this to Bitcoin’s finite nature. Stewart Alsop and Harry discuss how the flood of extraterrestrial gold could render traditional stores of value meaningless, while Bitcoin’s coded scarcity could make it the only incorruptible measure of worth in a future of infinite resources.
3. China and the U.S. in Industrial Tug-of-War – They unpack the geopolitical tension between China’s industrial dominance and America’s financial hegemony. Harry argues the U.S. is waking up from decades of outsourcing, driven by China’s speed in robotics and infrastructure. This dynamic competition, he says, is good—it forces America to build again.
4. Argentina’s Culture of Hunger and Resilience – Living in Buenos Aires reshaped Harry’s understanding of ambition. He contrasts Argentina’s hunger to survive and create with the complacency of wealthier nations, calling the Argentine spirit one of “movement.” Despite poverty, the city’s creative drive and humor make it a living example of resilience in scarcity.
5. AI Is Making Custom Software Instant – Harry describes how Claude 4.5 and new AI coding tools like Lovable, Cursor, and GPT Engineer make building internal tools trivial. Instead of using SaaS products, companies can now generate bespoke software in minutes with natural language, signaling the end of traditional software development cycles.
6. Crypto and AI Will Merge Into Incorruptible Systems – Harry envisions AI agents on-chain acting as unbiased judges or administrators, removing human corruption from law and governance. Real-world tools like Kleros, founded by an Argentine, already hint at this coming era of algorithmic justice and decentralized decision-making.
7. Consciousness and the Limits of AI – The episode closes on a philosophical note: can a robot meditate or clear its mind? Stewart and Harry question whether AI could ever experience consciousness or free will, suggesting that while AI may mimic thought, the uniquely subjective and embodied nature of human awareness remains beyond automation—for now.

In this episode of Crazy Wisdom, host Stewart Alsop sits down with Cryptogaucho to explore the intersection of artificial intelligence, crypto, and Argentina’s emerging role as a new frontier for innovation and governance. The conversation ranges from OpenAI’s partnership with Sur Energy and the Stargate project to Argentina’s RIGI investment framework, Milei’s libertarian reforms, and the potential of space-based data centers and new jurisdictions beyond Earth. Cryptogaucho also reflects on Argentina’s tech renaissance, its culture of resilience born from hyperinflation, and the rise of experimental communities like Prospera and Noma Collective. Follow him on X at @CryptoGaucho.

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Timestamps

00:00 – Stewart Alsop opens with Cryptogaucho from Mendoza, talking about Argentina, AI, crypto, and the energy around new projects like Sur Energy and Satellogic.
05:00 – They dive into Argentina’s growing space ambitions, spaceport plans, and how jurisdiction could extend “upward” through satellites and data sovereignty.
10:00 – The talk shifts to global regulation, bureaucracy, and why Argentina’s uncertainty may become its strength amid red tape in the US and China.
15:00 – Discussion of OpenAI’s Stargate project, AI infrastructure in Patagonia, and the geopolitical tension between state and private innovation.
20:00 – Cryptogaucho explains the “cepo” currency controls, the black market for dollars, and crypto’s role in preserving economic freedom.
25:00 – They unpack RIGI investment incentives, Argentina’s new economic rules, and efforts to attract major projects like data centers and nuclear reactors.
30:00 – Stewart connects hyperinflation to resilience and abundance in the AI era, while Cryptogaucho reflects on chaos, adaptability, and optimism.
35:00 – The conversation turns philosophical: nation-states, community networks, Prospera, and the rise of new governance models.
40:00 – They explore Argentina’s global position, soft power, and its role as a frontier of Western ideals.
45:00 – Final reflections on AI in space, data centers beyond Earth, and freedom of information as humanity’s next jurisdiction.

Key Insights

1. Argentina as a new technological frontier: The episode positions Argentina as a nation uniquely situated between chaos and opportunity—a place where political uncertainty and flexible regulation create fertile ground for experimentation. Stewart Alsop and Cryptogaucho argue that this openness, combined with a culture forged in crisis, allows Argentina to become a testing ground for new models of governance, technology, and sovereignty.
2. The convergence of AI, energy, and geography: OpenAI’s deal with Sur Energy and plans for a data center in Patagonia signal how Argentina’s geography and resources are becoming integral to the global AI infrastructure. Cryptogaucho highlights the symbolic and strategic power of Argentina serving as a “southern node” for the intelligence economy.
3. Economic reinvention through RIGI: The RIGI framework offers tax and regulatory advantages to major investors, marking a turning point in Argentina’s attempt to attract stable, high-value industries such as server farms, mining, and biotech. It represents a pragmatic balance between libertarian reform and national development.
4. Crypto and currency freedom: Cryptogaucho recounts how Argentina’s crypto community arose from necessity during hyperinflation and currency controls. Bitcoin and stablecoins became lifelines for developers and entrepreneurs locked out of traditional banking systems, teaching the world about decentralized resilience.
5. AI abundance and human adaptation: The discussion draws parallels between hyperinflation’s unpredictability and the overwhelming speed of AI progress. Stewart suggests that Argentina’s social adaptability, born from scarcity and instability, may prepare its citizens for a future defined by abundance and rapid technological flux.
6. Network states and new governance: The conversation explores Prospera, Noma Collective, and the idea of city-scale governance networks. These experiments, blending blockchain, law, and community, are seen as prototypes for post-nation-state organization—where trust and culture matter more than geography.
7. Space as the next jurisdiction: The episode ends with an exploration of space as a new legal and economic domain. Satellites, data centers, and orbital communication networks could redefine sovereignty, creating “data islands” beyond Earth where information flows freely under new kinds of governance—a vision of humanity’s next frontier.

In this episode of Crazy Wisdom, host Stewart Alsop speaks with Eli Lopian, author of AICracy and founder of aicracy.ai, about how artificial intelligence could transform the way societies govern themselves. They explore the limitations of modern democracy, the idea of AI-guided lawmaking based on fairness and abundance, and how technology might bring us closer to a more participatory, transparent form of governance. The conversation touches on prediction markets, social media’s influence on truth, the future of work in an abundance economy, and why human creativity, imperfection, and connection will remain central in an AI-driven world.

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Timestamps

00:00 Eli Lopian introduces his book AICracy and shares why democracy needs a new paradigm for governance in the age of AI.
05:00 They explore AI-driven decision-making, fairness in lawmaking, and the abundance measure as a new way to evaluate social well-being.
10:00 Discussion turns to accountability, trust, and Eli’s idea of three AIs—government, opposition, and NGO—balancing each other to prevent corruption.
15:00 Stewart connects these ideas to non-linearity and organic governance, while Eli describes systems evolving like cities rather than rigid institutions.
20:00 They discuss decade goals, city-state models, and the role of social media in shaping public perception and truth.
25:00 The focus shifts to truth detection, prediction markets, and feedback systems ensuring “did it actually happen?” accountability.
30:00 They talk about abundance economies, AI mentorship, and redefining human purpose beyond traditional work.
35:00 Eli emphasizes creativity, connection, and human error as valuable, contrasting social media’s dopamine loops with genuine human experience.
40:00 The episode closes with reflections on social currency, self-healing governance, and optimism about AI as a mirror of humanity.

Key Insights

1. Democracy is evolving beyond its limits. Eli Lopian argues that traditional democracy—one person, one vote—no longer fits an age where individuals have vastly different technological capacities. With AI empowering some to act with exponential influence, he suggests governance should evolve toward systems that are more adaptive, participatory, and continuous rather than episodic.
2. AI-guided lawmaking could ensure fairness. Lopian’s concept of AICracy imagines an AI system that drafts laws based on measurable outcomes like equity and happiness. Using what he calls the abundance measure, this system would assess how proposed laws affect societal well-being—balancing freedoms, security, and fairness across all citizens.
3. Trust and accountability must be engineered. To prevent corruption or bias in AI governance, Lopian envisions three independent AIs—a coalition, an opposition, and an NGO—cross-verifying results and exposing inconsistencies. This triad ensures transparency and keeps human oversight meaningful.
4. Governance should be organic, not mechanical. Drawing inspiration from cities, Lopian and Alsop compare governance to an ecosystem that adapts and self-corrects. Like urban growth, effective systems arise from real-world feedback, where successful ideas take root and failing ones fade away naturally.
5. Truth requires new forms of verification. The pair discuss how lies spread faster than truth online and propose an algorithmic “speed of a lie” metric to flag misinformation. They connect this to prediction markets and feedback loops as potential ways to keep governance accountable to real-world outcomes.
6. The abundance economy redefines purpose. As AI reduces the need for traditional jobs, Lopian imagines a society centered on creativity, mentorship, and personal fulfillment. Governments could guarantee access to mentors—human or AI—to help people discover their passions and contribute meaningfully without economic pressure.
7. Human connection is the new currency. In contrast to social media’s exploitation of human weakness, the future Lopian envisions values imperfection, authenticity, and shared experience. As AI automates production, what remains deeply human—emotion, error, and presence—becomes the most precious and sustaining form of wealth.

In this episode of Crazy Wisdom, host Stewart Alsop talks with Richard Easton, co-author of GPS Declassified: From Smart Bombs to Smartphones, about the remarkable history behind the Global Positioning System and its ripple effects on technology, secrecy, and innovation. They trace the story from Roger Easton’s early work on time navigation and atomic clocks to the 1973 approval of the GPS program, the Cold War’s influence on satellite development, and how civilian and military interests shaped its evolution. The conversation also explores selective availability, the Gulf War, and how GPS paved the way for modern mapping tools like Google Maps and Waze, as well as broader questions about information, transparency, and the future of scientific innovation. Learn more about Richard Easton’s work and explore early GPS documents at gpsdeclassified.com, or pick up his book GPS Declassified: From Smart Bombs to Smartphones.

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Timestamps

00:00 – Stewart Alsop introduces Richard Easton, who explains the origins of GPS, its 12-hour satellite orbits, and his father Roger Easton’s early time navigation work.
05:00 – Discussion on atomic clocks, the hydrogen maser, and how technological skepticism drove innovation toward the modern GPS system.
10:00 – Miniaturization of receivers, the rise of smartphones as GPS devices, and early mapping tools like Google Maps and Waze.
15:00 – The Apollo missions’ computer systems and precision landings lead back to GPS development and the 1973 approval of the joint program office.
20:00 – The Gulf War’s use of GPS, selective availability, and how civilian receivers became vital for soldiers and surveyors.
25:00 – Secrecy in satellite programs, from GRAB and POPPY to Eisenhower’s caution after the U-2 incident, and the link between intelligence and innovation.
30:00 – The myth of the Korean airliner sparking civilian GPS, Reagan’s policy, and the importance of declassified documents.
35:00 – Cold War espionage stories like Gordievsky’s defection, the rise of surveillance, and early countermeasures to GPS jamming.
40:00 – Selective availability ends in 2000, sparking geocaching and civilian boom, with GPS enabling agriculture and transport.
45:00 – Conversation shifts to AI, deepfakes, and the reliability of digital history.
50:00 – Reflections on big science, decentralization, and innovation funding from John Foster to SpaceX and Starlink.
55:00 – Universities’ bureaucratic bloat, the future of research education, and Richard’s praise for the University of Chicago’s BASIC program.

Key Insights

1. GPS was born from competing visions within the U.S. military. Richard Easton explains that the Navy and Air Force each had different ideas for navigation satellites in the 1960s. The Navy wanted mid-Earth orbits with autonomous atomic clocks, while the Air Force preferred ground-controlled repeaters in geostationary orbit. The eventual compromise in 1973 created the modern GPS structure—24 satellites in six constellations—which balanced accuracy, independence, and resilience.
2. Atomic clocks made global navigation possible. Roger Easton’s early insight was that improving atomic clock precision would one day enable real-time positioning. The hydrogen maser, developed in 1960, became the breakthrough technology that made GPS feasible. This innovation turned a theoretical idea into a working global system and also advanced timekeeping for scientific and financial applications.
3. Civilian access to GPS was always intended. Contrary to popular belief, GPS wasn’t a military secret turned public after the Korean airliner tragedy in 1983. Civilian receivers, such as TI’s 4100 model, were already available in 1981. Reagan’s 1983 announcement merely reaffirmed an existing policy that GPS would serve both military and civilian users.
4. The Gulf War proved GPS’s strategic value. During the 1991 conflict, U.S. and coalition forces used mostly civilian receivers after the Pentagon lifted “selective availability,” which intentionally degraded accuracy. GPS allowed troops to coordinate movement and strikes even during sandstorms, changing modern warfare.
5. Secrecy and innovation were deeply intertwined. Easton recounts how classified projects like GRAB and POPPY—satellites disguised as scientific missions—laid technical groundwork for navigation systems. The crossover between secret defense projects and public science fueled breakthroughs but also obscured credit and understanding.
6. Ending selective availability unleashed global applications. When the distortion feature was turned off in May 2000, GPS accuracy improved instantly, leading to new industries—geocaching, precision agriculture, logistics, and smartphone navigation. This marked GPS’s shift from a defense tool to an everyday utility.
7. Innovation’s future may rely on decentralization. Reflecting on his father’s era and today’s landscape, Easton argues that bureaucratic “big science” has grown sluggish. He sees promise in smaller, independent innovators—helped by AI, cheaper satellites, and private space ventures like SpaceX—continuing the cycle of technological transformation that GPS began.

On this episode of Crazy Wisdom, Stewart Alsop sits down with Leo Guinan to talk about the Manhattan Project for Human Potential, his vision of AI as a tool for personal agency, and the Bottega model inspired by the Medici workshops as a way to reimagine networks, mastery, and transformation. The conversation moves through themes of exponential versus linear growth in the economy, the decline of manufacturing in Ohio, China’s rise through complexity and control of supply chains, the dangers of time violence and information asymmetry, and the potential of prediction markets to reshape politics and business. Leo also shares his creative project Hitchhiker’s Guide to the Future, which he’s building as a group art experiment on Substack — you can find it at hitchhikertothefuture.substack.com.

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Timestamps

00:05 Stewart introduces Leo Guinan and they discuss the Manhattan Project for Human Potential, personal agency revolution, and the Bottega model rooted in Medici workshops.
00:10 Leo reflects on networks vs. individuals, the genius–insanity line, and how exponential growth clashes with linear wages in Silicon Valley.
00:15 They explore economic tension, the decline of wages, mastery in Bottegas, and the vision of decentralized innovation hubs.
00:20 Conversation turns to Argentina, decentralization, and Leo’s Ohio roots, tying local manufacturing decline, Anchor Hocking, and drug addiction to global shifts.
00:25 Leo shares his frustration with student debt, the fakeness of the economy, and neuroses encoded into AI models like Gemini.
00:30 They examine China’s manufacturing dominance, mercantilism, complexity inflation, and the concept of time violence.
00:35 Leo explains infinite predictors, cooperation, and consciousness as network awareness, citing Creator HQ as conscious technology.
00:40 Discussion moves to rigorous mysticism, deterministic transformation, probabilistic futures, and the monkey and the pedestal metaphor.
00:45 They analyze 1971 as a break between linear and exponential growth, compute access, surveillance states, and the power of human spite.
00:50 Leo imagines algorithm manipulation, local AI, and prediction markets, referencing futarchy and political false choices.
00:55 They close with Hitchhiker’s Guide to the Future, Leo’s group art project on Substack, and the rediscovery of ancient wisdom.

Key Insights

1. The heart of Leo Guinan’s work is what he calls the Manhattan Project for Human Potential, a recognition that artificial intelligence isn’t just about technology but about a personal agency revolution. He frames AI as a mirror that reveals how networks of people, rather than isolated individuals, drive intelligence and creativity.
2. The Bottega model, inspired by the Medici workshops, is central to Leo’s vision. By gathering diverse minds in tight-knit communities where mastery and exploration thrive, Bottegas become nodes of transformation — miniature Silicon Valleys where reality is fluid and imagination creates exponential value.
3. A recurring theme is the structural flaw of modern economies: wages grow linearly while technology and capital compound exponentially. This creates systemic inequality, leaving most people crushed by rising costs while the top flourishes, a dynamic Leo witnessed firsthand in both Silicon Valley and his Ohio hometown.
4. Leo introduces complexity inflation and time violence as hidden forces of the system. Complexity is rewarded over simplicity, making technology harder for everyday people, while time violence lets some actors leverage others’ time to their own advantage, turning the economy into an arms race of asymmetries.
5. Consciousness, for Leo, is about networks that are aware of themselves. He praises simple, embodied tools like Creator HQ that respect users’ lived reality and contrasts them with AI systems unmoored from the real world. True mastery, he argues, is embodied, consistent, and grounded in human transformation rather than probabilistic shortcuts.
6. Prediction markets emerge as a future-facing tool, offering a way to test decisions, hedge uncertainty, and surface blind spots. Leo envisions organizations running internal prediction markets and even rethinking politics by holding leaders accountable to explicit promises rather than vague partisan change.
7. At the personal level, Leo is experimenting with transformation through his Hitchhiker’s Guide to the Future project on Substack, a group art process that forces him out of his engineering comfort zone. He ties this back to ancient wisdom — from Buddha to Renaissance workshops — showing that the process of transformation has always been a deeply human practice we must continually rediscover.

In this episode of The Crazy Wisdom Podcast, Stewart Alsop talks with Jacob Hall and Kyriakos Skiouris, co-founders of Agingo, about the evolution of blockchain from linear ledgers to volumetric, multi-agent architectures. Together they explore how concepts like sovereignty, auditability, and immutability can redefine trust, governance, and digital agency in both human and artificial systems. The conversation touches on blockchain’s philosophical and technical frontiers—what an “AGI for blockchain” might mean, why immutability will matter in the age of AI, and how decentralization could restore autonomy without chaos. You can learn more about Agingo and their upcoming talks at agingo.com and reach them via [email protected].

Check out this GPT we trained on the conversation

Timestamps

00:00 Stewart Alsop welcomes Jacob Hall and Kyriakos Skiouris of Agingo, setting the stage for a conversation on blockchain as a paradigm shift beyond crypto.
05:00 They explore trust, contracts, and the difference between real-world agreements and smart contracts, questioning how sovereignty depends on auditability.
10:00 The guests reflect on Bitcoin’s origins, Satoshi’s intent, and the ideological fractures that shaped crypto’s culture and early altruism.
15:00 They discuss manipulation, value, and how blockchain technology parallels alchemy—transforming belief into perceived value.
20:00 The idea of social imaginaries emerges, using everyday systems like traffic lanes as metaphors for collective trust and order.
25:00 The talk moves toward digital etiquette, communication decay, and the cultural lag behind technological acceleration.
30:00 Agingo introduces the concept of volumetric blockchain, multi-agent validation, and four-dimensional nanochains replacing linear ledgers.
35:00 They unpack volumetric security, the tesseract metaphor, and blockchain as a living system mirroring consciousness.
40:00 Discussion turns to blockchain as language and history, linking immutability, perception, and meaning.
45:00 Business use cases arise—tokenized films, compliance, and real-world asset representation on decentralized infrastructure.
50:00 They imagine blockchain as infrastructure for AGI, distributed systems modeled after nature’s intelligence.
55:00 Closing reflections on centralization, sovereignty, and the need for open, non-binary conversations about trust and autonomy in the digital age.

Key Insights

1. Blockchain’s next evolution is volumetric, not linear. Jacob Hall and Kyriakos Skiouris argue that traditional blockchains like Bitcoin and Ethereum are “choo-choo trains”—linear systems limited by their own history. Agingo’s model introduces volumetric blockchain, where multiple agents and dimensions of time operate simultaneously, allowing for more secure, adaptive, and physics-like computation.
2. Sovereignty depends on auditability at speed. True digital sovereignty, they suggest, isn’t just owning your data but being able to verify it instantly. If you can’t audit a transaction or vote in real time, you’ve lost control of it. Fast, transparent auditability becomes the foundation of autonomy and trust in digital systems.
3. Language, contracts, and blockchains are all ledgers of meaning. The conversation reframes contracts as linguistic and symbolic structures—records of shared trust. Blockchain, in this light, is not just code but a living language that keeps history intact and immutable, anchoring truth in a world of mutable data.
4. Bitcoin’s promise was idealistic, but its structure is fragile. Hall recalls the early altruism of the Bitcoin community, contrasting it with the dogmatic, profit-driven culture that followed. The failure to evolve past linear design and ideological rigidity mirrors historical schisms in religion and governance.
5. Immutability will become essential in the AI era. As AI systems learn to rewrite their own data, humans will crave immutable records. Blockchain’s permanence provides a safeguard against subtle, undetectable shifts in digital reality—an anchor for truth as models become more autonomous.
6. Volumetric systems mirror consciousness. Their design mimics the distributed, multi-agent nature of the human brain. Just as neurons work in parallel, a volumetric blockchain processes data through overlapping agents that validate one another, creating a kind of digital nervous system with emergent intelligence.
7. Decentralization must include cultural and ethical intelligence. True progress, they conclude, isn’t just technical—it’s cultural. Without new forms of etiquette, communication, and mutual respect, decentralization risks reproducing the same hierarchies it seeks to replace. Blockchain’s next leap must integrate human values with technological sovereignty.