Episode #517: How Orbital Robotics Turns Space Junk into Infrastructure

In this episode of the Crazy Wisdom Podcast, host Stewart Alsop speaks with Aaron Borger, founder and CEO of Orbital Robotics, about the emerging world of space robotics and satellite capture technology. The conversation covers a fascinating range of topics including Borger's early experience launching AI-controlled robotic arms to space as a student, his work at Blue Origin developing lunar lander software, and how his company is developing robots that can capture other spacecraft for refueling, repair, and debris removal. They discuss the technical challenges of operating in space - from radiation hardening electronics to dealing with tumbling satellites - as well as the broader implications for the space economy, from preventing the Kessler effect to building space-based recycling facilities and mining lunar ice for rocket fuel. You can find more about Aaron Borger’s work at Orbital Robots and follow him on LinkedIn for updates on upcoming missions and demos. Check out this GPT we trained on the conversationTimestamps00:00 Introduction to orbital robotics, satellite capture, and why sensing and perception matter in space 05:00 The Kessler Effect, cascading collisions, and why space debris is an economic problem before it is an existential one 10:00 From debris removal to orbital recycling and the idea of turning junk into infrastructure 15:00 Long-term vision of space factories, lunar ice, and refueling satellites to bootstrap a lunar economy 20:00 Satellite upgrading, servicing live spacecraft, and expanding today’s narrow space economy 25:00 Costs of collision avoidance, ISS maneuvers, and making debris capture economically viable 30:00 Early experiments with AI-controlled robotic arms, suborbital launches, and reinforcement learning in microgravity 35:00 Why deterministic AI and provable safety matter more than LLM hype for spacecraft control 40:00 Radiation, single event upsets, and designing space-safe AI systems with bounded behavior 45:00 AI, physics-based world models, and autonomy as the key to scaling space operations 50:00 Manufacturing constraints, space supply chains, and lessons from rocket engine software 55:00 The future of space startups, geopolitics, deterrence, and keeping space usable for humanityKey Insights1. Space Debris Removal as a Growing Economic Opportunity: Aaron Borger explains that orbital debris is becoming a critical problem with approximately 3,000-4,000 defunct satellites among the 15,000 total satellites in orbit. The company is developing robotic arms and AI-controlled spacecraft to capture other satellites for refueling, repair, debris removal, and even space station assembly. The economic case is compelling - it costs about $1 million for the ISS to maneuver around debris, so if their spacecraft can capture and remove multiple pieces of debris for less than that cost per piece, it becomes financially viable while addressing the growing space junk problem.2. Revolutionary AI Safety Methods Enable Space Robotics: Traditional NASA engineers have been reluctant to use AI for spacecraft control due to safety concerns, but Orbital Robotics has developed breakthrough methods combining reinforcement learning with traditional control systems that can mathematically prove the AI will behave safely. Their approach uses physics-based world models rather than pure data-driven learning, ensuring deterministic behavior and bounded operations. This represents a significant advancement over previous AI approaches that couldn't guarantee safe operation in the high-stakes environment of space.3. Vision for Space-Based Manufacturing and Resource Utilization: The long-term vision extends beyond debris removal to creating orbital recycling facilities that can break down captured satellites and rebuild them into new spacecraft using existing materials in orbit. Additionally, the company plans to harvest propellant from lunar ice, splitting it into hydrogen and oxygen for rocket fuel, which could kickstart a lunar economy by providing economic incentives for moon-based operations while supporting the growing satellite constellation infrastructure.4. Unique Space Technology Development Through Student Programs: Borger and his co-founder gained unprecedented experience by launching six AI-controlled robotic arms to space through NASA's student rocket programs while still undergraduates. These missions involved throwing and catching objects in microgravity using deep reinforcement learning trained in simulation and tested on Earth. This hands-on space experience is extremely rare and gave them practical knowledge that informed their current commercial venture.5. Hardware Challenges Require Innovative Engineering Solutions: Space presents unique technical challenges including radiation-induced single event upsets that can reset processors for up to 10 seconds, requiring "passive safe" trajectories that won't cause collisions even during system resets. Unlike traditional space companies that spend $100,000 on radiation-hardened processors, Orbital Robotics uses automotive-grade components made radiation-tolerant through smart software and electrical design, enabling cost-effective operations while maintaining safety.6. Space Manufacturing Supply Chain Constraints: The space industry faces significant manufacturing bottlenecks with 24-week lead times for space-grade components and limited suppliers serving multiple companies simultaneously. This creates challenges for scaling production - Orbital Robotics needs to manufacture 30 robotic arms per year within a few years. They've partnered with manufacturers who previously worked on Blue Origin's rocket engines to address these supply chain limitations and achieve the scale necessary for their ambitious deployment timeline.7. Emerging Space Economy Beyond Communications: While current commercial space activities focus primarily on communications satellites (with SpaceX Starlink holding 60% market share) and Earth observation, new sectors are emerging including AI data centers in space and orbital manufacturing. The convergence of AI, robotics, and space technology is enabling more sophisticated autonomous operations, from predictive maintenance of rocket engines using sensor data to complex orbital maneuvering and satellite servicing that was previously impossible with traditional control methods.

In this episode, Stewart Alsop sits down with Joe Wilkinson of Artisan Growth Strategies to talk through how vibe coding is changing who gets to build software, why functional programming and immutability may be better suited for AI-written code, and how tools like LLMs are reshaping learning, work, and curiosity itself. The conversation ranges from Joe’s experience living in China and his perspective on Chinese AI labs like DeepSeek, Kimi, Minimax, and GLM, to mesh networks, Raspberry Pi–powered infrastructure, decentralization, and what sovereignty might mean in a world where intelligence is increasingly distributed. They also explore hallucinations, AlphaGo’s Move 37, and why creative “wrongness” may be essential for real breakthroughs, along with the tension between centralized power and open access to advanced technology. You can find more about Joe’s work at https://artisangrowthstrategies.com and follow him on X at https://x.com/artisangrowth.Check out this GPT we trained on the conversationTimestamps00:00 – Vibe coding as a new learning unlock, China experience, information overload, and AI-powered ingestion systems05:00 – Learning to code late, Exercism, syntax friction, AI as a real-time coding partner10:00 – Functional programming, Elixir, immutability, and why AI struggles with mutable state15:00 – Coding metaphors, “spooky action at a distance,” and making software AI-readable20:00 – Raspberry Pi, personal servers, mesh networks, and peer-to-peer infrastructure25:00 – Curiosity as activation energy, tech literacy gaps, and AI-enabled problem solving30:00 – Knowledge work superpowers, decentralization, and small groups reshaping systems35:00 – Open source vs open weights, Chinese AI labs, data ingestion, and competitive dynamics40:00 – Power, safety, and why broad access to AI beats centralized control45:00 – Hallucinations, AlphaGo’s Move 37, creativity, and logical consistency in AI50:00 – Provenance, epistemology, ontologies, and risks of closed-loop science55:00 – Centralization vs decentralization, sovereign countries, and post-global-order shifts01:00:00 – U.S.–China dynamics, war skepticism, pragmatism, and cautious optimism about the futureKey InsightsVibe coding fundamentally lowers the barrier to entry for technical creation by shifting the focus from syntax mastery to intent, structure, and iteration. Instead of learning code the traditional way and hitting constant friction, AI lets people learn by doing, correcting mistakes in real time, and gradually building mental models of how systems work, which changes who gets to participate in software creation.Functional programming and immutability may be better aligned with AI-written code than object-oriented paradigms because they reduce hidden state and unintended side effects. By making data flows explicit and preventing “spooky action at a distance,” immutable systems are easier for both humans and AI to reason about, debug, and extend, especially as code becomes increasingly machine-authored.AI is compressing the entire learning stack, from software to physical reality, enabling people to move fluidly between abstract knowledge and hands-on problem solving. Whether fixing hardware, setting up servers, or understanding networks, the combination of curiosity and AI assistance turns complex systems into navigable terrain rather than expert-only domains.Decentralized infrastructure like mesh networks and personal servers becomes viable when cognitive overhead drops. What once required extreme dedication or specialist knowledge can now be done by small groups, meaning that relatively few motivated individuals can meaningfully change communication, resilience, and local autonomy without waiting for institutions to act.Chinese AI labs are likely underestimated because they operate with different constraints, incentives, and cultural inputs. Their openness to alternative training methods, massive data ingestion, and open-weight strategies creates competitive pressure that limits monopolistic control by Western labs and gives users real leverage through choice.Hallucinations and “mistakes” are not purely failures but potential sources of creative breakthroughs, similar to AlphaGo’s Move 37. If AI systems are overly constrained to consensus truth or authority-approved outputs, they risk losing the capacity for novel insight, suggesting that future progress depends on balancing correctness with exploratory freedom.The next phase of decentralization may begin with sovereign countries before sovereign individuals, as AI enables smaller nations to reason from first principles in areas like medicine, regulation, and science. Rather than a collapse into chaos, this points toward a more pluralistic world where power, knowledge, and decision-making are distributed across many competing systems instead of centralized authorities.

In this episode of the Crazy Wisdom podcast, host Stewart Alsop talks with Umair Siddiqui about a wide range of interconnected topics spanning plasma physics, aerospace engineering, fusion research, and the philosophy of building complex systems, drawing on Umair’s path from hands-on plasma experiments and nonlinear physics to founding and scaling RF plasma thrusters for small satellites at Phase Four; along the way they discuss how plasmas behave at material boundaries, why theory often breaks in real-world systems, how autonomous spacecraft propulsion actually works, what space radiation does to electronics and biology, the practical limits and promise of AI in scientific discovery, and why starting with simple, analog approaches before adding automation is critical in both research and manufacturing, grounding big ideas in concrete engineering experience. You can find Umair on Linkedin.Check out this GPT we trained on the conversationTimestamps00:00 Opening context and plasma rockets, early interests in space, cars, airplanes 05:00 Academic path into space plasmas, mechanical engineering, and hands-on experiments 10:00 Grad school focus on plasma physics, RF helicon sources, and nonlinear theory limits 15:00 Bridging fusion research and space propulsion, Department of Energy funding context 20:00 Spin-out to Phase Four, building CubeSat RF plasma thrusters and real hardware 25:00 Autonomous propulsion systems, embedded controllers, and spacecraft fault handling 30:00 Radiation in space, single-event upsets, redundancy vs rad-hard electronics 35:00 Analog-first philosophy, mechanical thinking, and resisting premature automation 40:00 AI in science, low vs high hanging fruit, automation of experiments and insight 45:00 Manufacturing philosophy, incremental scaling, lessons from Elon Musk and production 50:00 Science vs engineering, concentration of effort, power, and progress in discoveryKey InsightsOne of the central insights of the episode is that plasma physics sits at the intersection of many domains—fusion energy, space environments, and spacecraft propulsion—and progress often comes from working directly at those boundaries. Umair Siddiqui emphasizes that studying how plasmas interact with materials and magnetic fields revealed where theory breaks down, not because the math is sloppy, but because plasmas are deeply nonlinear systems where small changes can produce outsized effects.The conversation highlights how hands-on experimentation is essential to real understanding. Building RF plasma sources, diagnostics, and thrusters forced constant confrontation with reality, showing that models are only approximations. This experimental grounding allowed insights from fusion research to transfer unexpectedly into practical aerospace applications like CubeSat propulsion, bridging fields that rarely talk to each other.A key takeaway is the difference between science and engineering as intent, not method. Science aims to understand, while engineering aims to make something work, but in practice they blur. Developing space hardware required scientific discovery along the way, demonstrating that companies can and often must do real science to achieve ambitious engineering goals.Umair articulates a strong philosophy of analog-first thinking, arguing that keeping systems simple and mechanical for as long as possible preserves clarity. Premature digitization or automation can obscure understanding, consume mental bandwidth, and even lock in errors before the system is well understood.The episode offers a grounded view of automation and AI in science, framing it in terms of low- versus high-hanging fruit. AI excels at exploring large parameter spaces and finding optima, but humans are still needed to judge physical plausibility, interpret results, and set meaningful directions.Space engineering reveals harsh realities about radiation, cosmic rays, and electronics, where a single particle can flip a bit or destroy a transistor. This drives design trade-offs between radiation-hardened components and redundant systems, reinforcing how environment fundamentally shapes engineering decisions.Finally, the discussion suggests that scientific and technological progress accelerates with concentrated focus and resources. Whether through governments, institutions, or individuals, periods of rapid advancement tend to follow moments where attention, capital, and intent are sharply aligned rather than diffusely spread.

In this episode of Crazy Wisdom, Stewart Alsop sits down with Javier Villar for a wide-ranging conversation on Argentina, Spain’s political drift, fiat money, the psychology of crowds, Dr. Hawkins’ levels of consciousness, the role of elites and intelligence agencies, spiritual warfare, and whether modern technology accelerates human freedom or deepens control. Javier speaks candidly about symbolism, the erosion of sovereignty, the pandemic as a global turning point, and how spiritual frameworks help make sense of political theater.Check out this GPT we trained on the conversationTimestamps00:00 Stewart and Javier compare Argentina and Spain, touching on cultural similarity, Argentinization, socialism, and the slow collapse of fiat systems.05:00 They explore Brave New World conditioning, narrative control, traditional Catholics, and the psychology of obedience in the pandemic.10:00 Discussion shifts to Milei, political theater, BlackRock, Vanguard, mega-corporations, and the illusion of national sovereignty under a single world system.15:00 Stewart and Javier examine China, communism, spiritual structures, karmic cycles, Kali Yuga, and the idea of governments at war with their own people.20:00 They move into Revelations, Hawkins, calibrations, conspiracy labels, satanic vs luciferic energy, and elites using prophecy as a script.25:00 Conversation deepens into ego vs Satan, entrapment networks, Epstein Island, Crowley, Masonic symbolism, and spiritual corruption.30:00 They question secularism, the state as religion, technology, AI, surveillance, freedom of currency, and the creative potential suppressed by government.35:00 Ending with Bitcoin, stablecoins, network-state ideas, U.S. power, Argentina’s contradictions, and whether optimism is still warranted.Key InsightsArgentina and Spain mirror each other’s decline. Javier argues that despite surface differences, both countries share cultural instincts that make them vulnerable to the same political traps—particularly the expansion of the welfare state, the erosion of sovereignty, and what he calls the “Argentinization” of Spain. This framing turns the episode into a study of how nations repeat each other’s mistakes.Fiat systems create a controlled collapse rather than a dramatic one. Instead of Weimar-style hyperinflation, Javier claims modern monetary structures are engineered to “boil the frog,” preserving the illusion of stability while deepening dependency on the state. This slow-motion decline is portrayed as intentional rather than accidental.Political leaders are actors within a single global architecture of power. Whether discussing Milei, Trump, or European politics, Javier maintains that governments answer to mega-corporations and intelligence networks, not citizens. National politics, in this view, is theater masking a unified global managerial order.Pandemic behavior revealed mass submission to narrative control. Stewart and Javier revisit 2020 as a psychological milestone, arguing that obedience to lockdowns and mandates exposed a widespread inability to question authority. For Javier, this moment clarified who can perceive truth and who collapses under social pressure.Hawkins’ map of consciousness shapes their interpretation of good and evil. They use the 200 threshold to distinguish animal from angelic behavior, exploring whether ego itself is the “Satanic” force. Javier suggests Hawkins avoided explicit talk of Satan because most people cannot face metaphysical truth without defensiveness.Elites rely on symbolic power, secrecy, and coercion. References to Epstein Island, Masonic symbolism, and intelligence-agency entrapment support Javier’s view that modern control systems operate through sexual blackmail, ritual imagery, and hidden hierarchies rather than democratic mechanisms.Technology’s promise is strangled by state power. While Stewart sees potential in AI, crypto, and network-state ideas, Javier insists innovation is meaningless without freedom of currency, association, and exchange. Technology is neutral, he argues, but becomes a tool of surveillance and control when monopolized by governments.

In this episode of Crazy Wisdom, I—Stewart Alsop—sit down with Garrett Dailey to explore a wide-ranging conversation that moves from the mechanics of persuasion and why the best pitches work by attraction rather than pressure, to the nature of AI as a pattern tool rather than a mind, to power cycles, meaning-making, and the fracturing of modern culture. Garrett draws on philosophy, psychology, strategy, and his own background in storytelling to unpack ideas around narrative collapse, the chaos–order split in human cognition, the risk of “AI one-shotting,” and how political and technological incentives shape the world we're living through. You can find the tweet Stewart mentions in this episode here. Also, follow Garrett Dailey on Twitter at @GarrettCDailey, or find more of his pitch-related work on LinkedIn.Check out this GPT we trained on the conversationTimestamps00:00 Garrett opens with persuasion by attraction, storytelling, and why pitches fail with force. 05:00 We explore gravity as metaphor, the opposite of force, and the “ring effect” of a compelling idea. 10:00 AI as tool not mind; creativity, pattern prediction, hype cycles, and valuation delusions. 15:00 Limits of LLMs, slopification, recursive language drift, and cultural mimicry. 20:00 One-shotting, psychosis risk, validation-seeking, consciousness vs prediction. 25:00 Order mind vs chaos mind, solipsism, autism–schizophrenia mapping, epistemology. 30:00 Meaning, presence, Zen, cultural fragmentation, shared models breaking down. 35:00 U.S. regional culture, impossibility of national unity, incentives shaping politics. 40:00 Fragmentation vs reconciliation, markets, narratives, multipolarity, Dune archetypes. 45:00 Patchwork age, decentralization myths, political fracturing, libertarian limits. 50:00 Power as zero-sum, tech-right emergence, incentives, Vance, Yarvin, empire vs republic. 55:00 Cycles of power, kyklos, democracy’s decay, design-by-committee, institutional failure.Key InsightsPersuasion works best through attraction, not pressure. Garrett explains that effective pitching isn’t about forcing someone to believe you—it’s about creating a narrative gravity so strong that people move toward the idea on their own. This reframes persuasion from objection-handling into desire-shaping, a shift that echoes through sales, storytelling, and leadership.AI is powerful precisely because it’s not a mind. Garrett rejects the “machine consciousness” framing and instead treats AI as a pattern amplifier—extraordinarily capable when used as a tool, but fundamentally limited in generating novel knowledge. The danger arises when humans project consciousness onto it and let it validate their insecurities.Recursive language drift is reshaping human communication. As people unconsciously mimic LLM-style phrasing, AI-generated patterns feed back into training data, accelerating a cultural “slopification.” This becomes a self-reinforcing loop where originality erodes, and the machine’s voice slowly colonizes the human one.The human psyche operates as a tension between order mind and chaos mind. Garrett’s framework maps autism and schizophrenia as pathological extremes of this duality, showing how prediction and perception interact inside consciousness—and why AI, which only simulates chaos-mind prediction, can never fully replicate human knowing.Meaning arises from presence, not abstraction. Instead of obsessing over politics, geopolitics, or distant hypotheticals, Garrett argues for a Zen-like orientation: do what you're doing, avoid what you're not doing. Meaning doesn’t live in narratives about the future—it lives in the task at hand.Power follows predictable cycles—and America is deep in one. Borrowing from the Greek kyklos, Garrett frames the U.S. as moving from aristocracy toward democracy’s late-stage dysfunction: populism, fragmentation, and institutional decay. The question ahead is whether we’re heading toward empire or collapse.Decentralization is entropy, not salvation. Crypto dreams of DAOs and patchwork societies ignore the gravitational pull of power. Systems fragment as they weaken, but eventually a new center of order emerges. The real contest isn’t decentralization vs. centralization—it’s who will have the coherence and narrative strength to recentralize the pieces.

In this episode of Crazy Wisdom, Stewart Alsop talks with Aaron Lowry about the shifting landscape of attention, technology, and meaning—moving through themes like treasure-hunt metaphors for human cognition, relevance realization, the evolution of observational tools, decentralization, blockchain architectures such as Cardano, sovereignty in computation, the tension between scarcity and abundance, bioelectric patterning inspired by Michael Levin’s research, and the broader cultural and theological currents shaping how we interpret reality. You can follow Aaron’s work and ongoing reflections on X at aaron_lowry.Check out this GPT we trained on the conversationTimestamps00:00:00 Stewart and Aaron open with the treasure-hunt metaphor, salience landscapes, and how curiosity shapes perception. 00:05:00 They explore shifting observational tools, Hubble vs James Webb, and how data reframes what we think is real. 00:10:00 The conversation moves to relevance realization, missing “Easter eggs,” and the posture of openness. 00:15:00 Stewart reflects on AI, productivity, and feeling pulled deeper into computers instead of freed from them. 00:20:00 Aaron connects this to monetary policy, scarcity, and technological pressure. 00:25:00 They examine voice interfaces, edge computing, and trust vs convenience. 00:30:00 Stewart shares experiments with Raspberry Pi, self-hosting, and escaping SaaS dependence. 00:35:00 They discuss open-source, China’s strategy, and the economics of free models. 00:40:00 Aaron describes building hardware–software systems and sensor-driven projects. 00:45:00 They turn to blockchain, UTXO vs account-based, node sovereignty, and Cardano. 00:50:00 Discussion of decentralized governance, incentives, and transparency. 00:55:00 Geopolitics enters: BRICS, dollar reserve, private credit, and institutional fragility. 01:00:00 They reflect on the meaning crisis, gnosticism, reductionism, and shattered cohesion. 01:05:00 Michael Levin, bioelectric patterning, and vertical causation open new biological and theological frames. 01:10:00 They explore consciousness as fundamental, Stephen Wolfram, and the limits of engineered solutions. 01:15:00 Closing thoughts on good-faith orientation, societal transformation, and the pull toward wilderness.Key InsightsCuriosity restructures perception. Aaron frames reality as something we navigate more like a treasure hunt than a fixed map. Our “salience landscape” determines what we notice, and curiosity—not rigid frameworks—keeps us open to signals we would otherwise miss. This openness becomes a kind of existential skill, especially in a world where data rarely aligns cleanly with our expectations.Our tools reshape our worldview. Each technological leap—from Hubble to James Webb—doesn’t just increase resolution; it changes what we believe is possible. Old models fail to integrate new observations, revealing how deeply our understanding depends on the precision and scope of our instruments.Technology increases pressure rather than reducing it. Even as AI boosts productivity, Stewart notices it pulling him deeper into computers. Aaron argues this is systemic: productivity gains don’t free us; they raise expectations, driven by monetary policy and a scarcity-based economic frame.Digital sovereignty is becoming essential. The conversation highlights the tension between convenience and vulnerability. Cloud-based AI creates exposure vectors into personal life, while running local hardware—Raspberry Pis, custom Linux systems—restores autonomy but requires effort and skill.Blockchain architecture determines decentralization. Aaron emphasizes the distinction between UTXO and account-based systems, arguing that UTXO architectures (Bitcoin, Cardano) support verifiable edge participation, while account-based chains accumulate unwieldy state and centralize validation over time.Institutional trust is eroding globally. From BRICS currency moves to private credit schemes, both note how geopolitical maneuvers signal institutional fragility. The “few men in a room” dynamic persists, but now under greater stress, driving more people toward decentralization and self-reliance.Biology may operate on deeper principles than genes. Michael Levin’s work on bioelectric patterning opens the door to “vertical causation”—higher-level goals shaping lower-level processes. This challenges reductionism and hints at a worldview where consciousness, meaning, and biological organization may be intertwined in ways neither materialism nor traditional theology fully capture.

In this conversation, Stewart Alsop sits down with Ken Lowry to explore a wide sweep of themes running through Christianity, Protestant vs. Catholic vs. Orthodox traditions, the nature of spirits and telos, theosis and enlightenment, information technology, identity, privacy, sexuality, the New Age “Rainbow Bridge,” paganism, Buddhism, Vedanta, and the unfolding meaning crisis; listeners who want to follow more of Ken’s work can find him on his YouTube channel Climbing Mount Sophia and on Twitter under KenLowry8.Check out this GPT we trained on the conversationTimestamps00:00 Christianity’s tangled history surfaces as Stewart Alsop and Ken Lowry unpack Luther, indulgences, mediation, and the printing-press information shift.05:00 Luther’s encounters with the devil lead into talk of perception, hallucination, and spiritual influence on “main-character” lives.10:00 Protestant vs. Catholic vs. Orthodox worship styles highlight telos, Eucharist, liturgy, embodiment, and teaching as information.15:00 The Church as a living spirit emerges, tied to hierarchy, purpose, and Michael Levin’s bioelectric patterns shaping form.20:00 Spirits, goals, Dodgers-as-spirit, and Christ as the highest ordering spirit frame meaning and participation.25:00 Identity, self, soul, privacy, intimacy, and the internet’s collapse of boundaries reshape inner life.30:00 New Age, Rainbow Bridge, Hawkins’ calibration, truth-testing, and spiritual discernment enter the story.35:00 Stewart’s path back to Christianity opens discussion of enlightenment, Protestant legalism, Orthodox theosis, and healing.40:00 Emptiness, relationality, Trinity, and personhood bridge Buddhism and mystical Christianity.45:00 Suffering, desire, higher spirits, and orientation toward the real sharpen the contrast between simulation and reality.50:00 Technology, bodies, AI, and simulated worlds raise questions of telos, meaning, and modern escape.55:00 Neo-paganism, Hindu hierarchy of gods, Vedanta, and the need for a personal God lead toward Jesus as historical revelation.01:00:00 Buddha, enlightenment, theosis, the post-1945 world, Hitler as negative pole, and goodness as purpose close the inquiry.Key InsightsMediation and information shape the Church. Ken Lowry highlights how the printing press didn’t just spread ideas—it restructured Christian life by shifting mediation. Once information became accessible, individuals became the “interface” with Christ, fundamentally changing Protestant, Catholic, and Orthodox trajectories and the modern crisis of religious choice.The Protestant–Catholic–Orthodox split hinges on telos. Protestantism orients the service around teaching and information, while Catholic and Orthodox traditions culminate in the Eucharist, embodiment, and liturgy. This difference expresses two visions of what humans are doing in church: receiving ideas or participating in a transformative ritual that shapes the whole person.Spirits, telos, and hierarchy offer a map of reality. Ken frames spirits as real intelligible goals that pull people into coordinated action—seen as clearly in a baseball team as in a nation. Christ is the highest spirit because aiming toward Him properly orders all lower goals, giving a coherent vertical structure to meaning.Identity, privacy, and intimacy have transformed under the internet. The shift from soul → self → identity tracks changes in information technology. The internet collapses boundaries, creating unprecedented exposure while weakening the inherent privacy of intimate realities such as genuine lovemaking, which Ken argues can’t be made public without destroying its nature.New Age influences and Hawkins’ calibration reflect a search for truth. Stewart’s encounters with the Rainbow Bridge world, David Hawkins’ muscle-testing epistemology, and the escape from scientistic secularism reveal a cultural hunger for spiritual discernment in the absence of shared metaphysical grounding.Enlightenment and theosis may be the same mountain. Ken suggests that Buddhist enlightenment and Orthodox theosis aim at the same transformative reality: full communion with what is most real. The difference lies in Jesus as the concrete, personal revelation of God, offering a relational path rather than pure negation or emptiness.Secularism is shaped by powerfully negative telos. Ken argues that the modern world orients itself not toward the Good revealed in Christ but away from the Evil revealed in Hitler. Moving away from evil as a primary aim produces confusion, because only a positive vision of the Good can order desires, technology, suffering, and the overwhelming power of modern simulations.

On this episode of Crazy Wisdom, I, Stewart Alsop, sit down with Dax Raad, co-founder of OpenCode, for a wide-ranging conversation about open-source development, command-line interfaces, the rise of coding agents, how LLMs change software workflows, the tension between centralization and decentralization in tech, and even what it’s like to push the limits of the terminal itself. We talk about the future of interfaces, fast-feedback programming, model switching, and why open-source momentum—especially from China—is reshaping the landscape. You can find Dax on Twitter and check an example of what can be done using OpenCode in this tweet.Check out this GPT we trained on the conversationTimestamps00:00 Stewart Alsop and Dax Raad open with the origins of OpenCode, the value of open source, and the long-tail problem in coding agents. 05:00 They explore why command line interfaces keep winning, the universality of the terminal, and early adoption of agentic workflows. 10:00 Dax explains pushing the terminal with TUI frameworks, rich interactions, and constraints that improve UX. 15:00 They contrast CLI vs. chat UIs, discuss voice-driven reviews, and refining prompt-review workflows. 20:00 Dax lays out fast feedback loops, slow vs. fast models, and why autonomy isn’t the goal. 25:00 Conversation turns to model switching, open-source competitiveness, and real developer behavior. 30:00 They examine inference economics, Chinese open-source labs, and emerging U.S. efforts. 35:00 Dax breaks down incumbents like Google and Microsoft and why scale advantages endure. 40:00 They debate centralization vs. decentralization, choice, and the email analogy. 45:00 Stewart reflects on building products; Dax argues for healthy creative destruction. 50:00 Hardware talk emerges—Raspberry Pi, robotics, and LLMs as learning accelerators. 55:00 Dax shares insights on terminal internals, text-as-canvas rendering, and the elegance of the medium.Key InsightsOpen source thrives where the long tail matters. Dax explains that OpenCode exists because coding agents must integrate with countless models, environments, and providers. That complexity naturally favors open source, since a small team can’t cover every edge case—but a community can. This creates a collaborative ecosystem where users meaningfully shape the tool.The command line is winning because it’s universal, not nostalgic. Many misunderstand the surge of CLI-based AI tools, assuming it’s aesthetic or retro. Dax argues it’s simply the easiest, most flexible, least opinionated surface that works everywhere—from enterprise laptops to personal dev setups—making adoption frictionless.Terminal interfaces can be richer than assumed. The team is pushing TUI frameworks far beyond scrolling text, introducing mouse support, dialogs, hover states, and structured interactivity. Despite constraints, the terminal becomes a powerful “text canvas,” capable of UI complexity normally reserved for GUIs.Fast feedback loops beat “autonomous” long-running agents. Dax rejects the trend of hour-long AI tasks, viewing it as optimizing around model slowness rather than user needs. He prefers rapid iteration with faster models, reviewing diffs continuously, and reserving slower models only when necessary.Open-source LLMs are improving quickly—and economics matter. Many open models now approach the quality of top proprietary systems while being far cheaper and faster to serve. Because inference is capital-intensive, competition pushes prices down, creating real incentives for developers and companies to reconsider model choices.Centralization isn’t the enemy—lack of choice is. Dax frames the landscape like email: centralized providers dominate through convenience and scale, but the open protocols underneath protect users’ ability to choose alternatives. The real danger is ecosystems where leaving becomes impossible.LLMs dramatically expand what individuals can learn and build. Both Stewart and Dax highlight that AI enables people to tackle domains previously too opaque or slow to learn—from terminal internals to hardware tinkering. This accelerates creativity and lowers barriers, shifting agency back to small teams and individuals.

In this episode of Crazy Wisdom, I, Stewart Alsop, sit down with Argentine artist Mathilda Martin to explore the intimate connection between creativity, flow, and authenticity—from how swimming mirrors painting, to why art can heal, and what makes human-made art irreplaceable in the age of AI. We also touch on Argentina’s vibrant art scene, the shift in the art world after COVID, and the fine line between commercial and soulful creation. You can find Mathilda’s work on Instagram at @arte_mathilda.Check out this GPT we trained on the conversationTimestamps00:00 – Mathilda Martin joins Stewart Alsop to talk about art, creativity, and her upcoming exhibitions in Miami and Uruguay.05:00 – She shares how swimming connects to painting, describing water as calm, presence, and a source of flow and meditation.10:00 – They discuss art as therapy, childhood creativity, and overcoming fear by simply starting to create.15:00 – Mathilda reflects on her love for Van Gogh and feeling as the essence of authentic art, contrasting it with the coldness of AI.20:00 – The conversation turns to the value of human-made art and whether galleries can tell the difference between AI and real artists.25:00 – They explore Argentine authenticity, “chantas,” and what makes Argentina both chaotic and deeply real.30:00 – Mathilda talks about solidarity, community, and daily life in Buenos Aires amid political and economic instability.35:00 – She highlights Argentine muralists and how collaboration and scale transform artistic expression.40:00 – The pair discuss the commercialization of art, the “factory artist,” and staying true to feeling over fame.45:00 – Mathilda explains how COVID reshaped the art world, empowering independent artists to exhibit without galleries.50:00 – They end with art markets in Argentina vs. the U.S., her gallery in New York, and upcoming shows at Spectrum Miami and Punta del Este.Key InsightsArt and Water Share the Same Flow: Mathilda Martin reveals how swimming and painting both bring her into a meditative state she calls “the pause.” In the water, she feels the same stillness she experiences while painting — a total immersion in the present moment where the outside world disappears.Art Is a Form of Healing: Mathilda emphasizes that art is not just expression but medicine. She references the World Health Organization’s recognition that creativity benefits mental and physical health, describing painting as a space of emotional regulation and clarity.Human-Made Art Has Soul, AI Doesn’t: One of the episode’s most thought-provoking moments comes when Mathilda contrasts the warmth of human-made art with the cold precision of AI. She believes that while AI can replicate technique, it can’t replicate feeling — and that collectors will always value art infused with human emotion.Authenticity Defines Argentine Culture: Mathilda paints a vivid picture of Argentina as a land of contradictions — full of chaos, charm, and honesty. Argentines, she says, are “authentic, sometimes too direct,” a quality that shapes both their relationships and their art.COVID-19 Changed the Art World Forever: The pandemic disrupted the old gallery system and gave artists freedom to organize their own exhibitions. For Mathilda, this shift created independence, even if it also demanded new entrepreneurial skills.Commercial Success vs. Soulful Creation: Mathilda critiques “factory artists” who mass-produce work for fame or profit, contrasting them with artists who create from genuine emotion. The real challenge, she says, is maintaining authenticity in a system that rewards volume over vulnerability.Art as Connection and Presence: Beyond skill or aesthetics, Mathilda believes true art is about human connection — between artist, viewer, and the moment of creation itself. Whether painting, swimming, or teaching workshops, she views art as an ongoing conversation with life’s deeper flow.

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.Check out this GPT we trained on the conversationTimestamps00:00 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 InsightsAI 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.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.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.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.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.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.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.