Free Daily Podcast Summary
Crazy Wisdom: Daily Summaries Delivered
by Stewart Alsop
In his series "Crazy Wisdom," Stewart Alsop explores cutting-edge topics, particularly in the realm of technology, such as Urbit and artificial intelligence. Alsop embarks on a quest for meaning, engaging with others to expand his own understanding of reality and that of his audience. The topics covered in "Crazy Wisdom" are diverse, ranging from emerging technologies to spirituality, philosophy, and general life experiences. Alsop's unique approach aims to make connections between seemingly unrelated subjects, tying together ideas in unconventional ways.
Latest Episodes
The most recent episodes — sign up to get AI-powered summaries of each one.
- 4 days ago55 min
Episode #550: From Armies to Algorithms: Why the Biggest Player No Longer Wins
In this episode of the Crazy Wisdom Podcast, host Stewart Alsop sits down with returning guest Ekue Kpodar for their third conversation together, covering a wide range of topics at the intersection of technology, geopolitics, and the evolving information age. They dig into Ekue's unconventional setup of running local AI models across roughly 15 computers, the growing case for open source models over closed ones from companies like OpenAI and Anthropic, and how Chinese open source models may be positioned to outcompete Western alternatives on a global scale. The conversation also touches on vibe coding and the democratization of software development, the strategic use of small models for IoT and enterprise applications, the role of Israel and China as dominant players in the information age, and how smaller nations and even individuals may wield outsized power as AI continues to collapse the cost of knowledge work. You can find Ekue Kpodar on X @ekpodar and LinkedIn.Timestamps00:00 Stewart welcomes Ekue for their third episode, diving into vibe coding and AI-driven development changes.05:00 Ekue explains using Claude on Chrome to auto-reply on Skool, burning tokens through screenshots, and Playwright as a more efficient alternative.10:00 Stewart describes his Claude-dependent planning and coding agent system breaking after a model update, prompting him to build his own chatbot.15:00 Small models discussed as critical for IoT, defense, and privacy-focused enterprises building internal APIs instead of routing traffic to OpenAI.20:00 Open source versus closed source debated, with Chinese models gaining global traction while US foundational labs remain expensive and restrictive.25:00 SaaS apocalypse explored as AI commoditizes knowledge work, with Linux and Terraform cited as proof open source still generates wealth.30:00 OpenAI's sci-fi terminator fears explained as the reason they stayed closed source, ultimately handing China a strategic open source advantage.35:00 China's economic dumping strategy applied to AI, potentially displacing US model dominance globally the same way manufacturing was disrupted.40:00 Israel's signals intelligence dominance discussed alongside asymmetric warfare, drones defeating tanks, and information control replacing military muscle.45:00 Global information age rankings debated, Israel leading, US and China tied, France and Poland emerging as sovereign tech players.50:00 Qatar, NVIDIA, and Iran cited as proof that rare resources and technology matter more than population size in the 21st century power landscape.Key Insights1. Running local AI models on a network of affordable computers can be more cost-effective than relying entirely on third-party APIs. By using compressed or smaller open source models locally, developers can handle repetitive or lower-stakes tasks without burning through expensive tokens from providers like Anthropic or OpenAI.2. Small AI models are becoming increasingly important for IoT, defense applications, and companies that do not want to send sensitive data to external providers. Organizations can download open source models, run them on internal servers, and build proprietary APIs around them, creating something like an intranet of specialized small models.3. The value created by AI tools is being redistributed away from traditional SaaS companies toward foundational model providers and individual builders. People are canceling subscriptions to software they once paid hundreds per month for, because AI now allows a single person to build comparable tools themselves.4. Open source technology does not eliminate the ability to profit. Linux and Terraform are both open source yet made their creators wealthy. People will still pay for installation, setup, troubleshooting, and customization even when the underlying software is free.5. China is applying its longstanding manufacturing dumping strategy to artificial intelligence by releasing cheap open source models globally, which threatens to erode US dominance in AI the same way Chinese manufacturing undercut other countries for decades.6. In the information age, the size of a country or institution matters far less than its access to rare resources or advanced technology. Qatar, Israel, and NVIDIA each demonstrate that small populations or headcounts can wield enormous global negotiating power through concentrated technological or resource advantages.7. Asymmetric warfare is redefining military power, with inexpensive drones defeating tanks that cost millions to build. This shifts the advantage toward nations that excel at signals intelligence and information management rather than those with the largest conventional military
- 1 weeks ago1h 10m
Episode #549: From MS-DOS to Vibe Coding: How Non-Technical Founders Build Complex Software
Stewart Alsop sat down with Michael Shackelford to discuss their experiences building applications through vibe coding—the practice of using AI to create software without traditional programming expertise. Stewart, who runs the AI Whispers community in Buenos Aires and hosts the Crazy Wisdom podcast (with over 660 interviews), shared how he went from teaching people prompt engineering to building his own video conferencing software as a Riverside.fm replacement, while Michael opened up about his year-long journey creating Genrupt Inc, an AI-powered content generation tool for e-commerce sellers. The conversation covered everything from the decline in quality of Claude's reasoning capabilities and how Chinese companies used distillation attacks to copy Anthropic's models, to the importance of spaced repetition systems for managing knowledge in the age of LLMs, with both sharing battle-tested prompting strategies like asking AI to "explain it to me in genius terms" and using deep research queries to reverse engineer how competitors build their products.Show Notes:- Dan Martell's book "Buy Back Your Time" was mentioned as one of the best business books for thinking about life and business- Check out John Vervaeke's "Awakening from the Meaning Crisis" for understanding relevance realization and why AI fundamentally cannot determine what's relevant to humans without being toldTimestamps00:00 Michael discusses being exhausted from getting his app ready for launch, working nonstop with AI to prepare landing page for podcast traffic driving beta signups05:00 Stewart explains starting AI Whispers in Buenos Aires after leaving OpenAI vendor company, meeting early adopters like Torin who was building mind-reading EEG technology10:00 Discussion of how corporations resist AI adoption due to political games and job security fears while some companies use AI as excuse for pandemic-era layoffs15:00 Stewart describes teaching workshops on using LLMs as linguistic tools rather than coding tools, noting technical people often lack humanities background needed for prompting20:00 Explaining chatbot wrappers, API calls, and how Anthropic's reasoning quality declined after Chinese distillation attacks copied their secret sauce developed with philosophers25:00 Technical discussion of model training, fine-tuning versus RAG for new information, and different approaches to updating AI knowledge beyond initial training30:00 Stewart describes building podcast recording software to replace expensive Riverside, struggling with syncing audio and video files across different computer clocks35:00 Discussion of critical factors in vibe coding, discovering unknown technical requirements, and how AIs don't automatically reveal missing information40:00 Stewart's reverse engineering process using deep research function to study competitors' hiring and technology stacks, separating planning agents from coding agents45:00 Prompting techniques including "explain like I know everything" and using spaced repetition systems to capture valuable prompts and technical knowledge50:00 Michael explains his Generux app for generating ecommerce content using Amazon review data analysis to inform high-converting listing images and videos55:00 Discussion of founder mentality involving self-delusion about project timelines, Michael working nine-plus hours daily for nine months on app development60:00 Comparing Amazon's expert software to prosumer software approach, discussing distribution challenges and future robotics applications for customized products65:00 Stewart demonstrates spaced repetition app for memory improvement and knowledge retention, explaining relevance realization problem that AI agents cannot solve without embodimentKey Insights1. Stewart Alsop started AI Whisperers in Buenos Aires after leaving his role at Invisible Technologies, which was OpenAI's largest vendor for RLHF work. He noticed that machine learning engineers at tech companies lacked the humanities background needed to properly interact with large language models, which are fundamentally linguistic tools. This led him to create weekly workshops teaching non-technical people how to use AI effectively, running events every Thursday for two years straight. The group attracted intense geeks from the start and eventually led to Stewart speaking right after Vitalik Buterin at DevConnect, marking a significant milestone for the community.2. Large corporations are resistant to AI adoption due to multiple factors including political dynamics within organizations and employees fearing job loss. Many companies that grew during the pandemic are now using AI as an excuse to downsize when the real issue is inefficiency from rapid expansion. Stewart observed that even technical people in machine learning often don't understand how to properly use AI tools
- 1 weeks ago56 min
Episode #548: The Pixel Path: From Perception to Action, and the Future of Intelligent Robots with Nizar
Stewart Alsop interviews Nizar, CEO of Pixel Robotics, on the Crazy Wisdom Podcast to explore the intersection of AI, robotics, and perception. The conversation covers a wide range of technical topics including how transformers enable multimodal representation across text, images, and voice, the role of world models in predicting physical interactions, the advantages of diffusion models over traditional LLMs for certain applications, and the challenges of achieving real-time processing for robotics applications. Nizar explains Pixel Robotics' work on creating accurate 3D meshes from smartphone cameras for companies like L'Oréal, moving away from specialized sensors to make the technology more accessible through sophisticated algorithms, and discusses the future of robotics as closing the perception-action loop to enable robots to perform real tasks beyond simple demonstrations. To find out more visit Pixel Robotics' website.Timestamps00:00 Stewart welcomes Nizar, CEO of Pixel Robotics, discussing what a pixel is as the smallest visual unit on screens composed of red green and blue colors05:00 Discussion of perception systems and how logarithmic laws help compress signals in both human and artificial systems, exploring normalization layers and sigmoid functions in deep learning10:00 Exploring how transformers unified different data modalities including text voice and images, creating common representations through methods like contrastive learning15:00 Nizar explains transformers as brute force learning systems with room for improvement through focused attention mechanisms and knowledge graphs rather than processing everything20:00 Conversation about loss functions local minima versus global minima and how mixture of experts uses specialized small models instead of one massive generalist network25:00 Discussion of deterministic versus probabilistic systems and how explicitly defined task graphs often outperform orchestrator-based approaches in AI systems30:00 Exploring world models as predictive physics-based systems that learn environmental flows and transformations, complementing rather than replacing language models35:00 Nizar discusses real-time processing challenges for robotics requiring millisecond responses with small memory footprints using vision transformers for faster experimentation40:00 Pixel's work creating three d meshes from smartphone cameras for companies like L'Oreal, moving away from specialized sensors toward accessible software-based solutions45:00 Explanation of different three d representations including voxels point clouds and meshes, with meshes being optimal for manipulation and rendering in applications50:00 Future direction involves closing perception-action loops in robotics, moving beyond dancing toy robots toward practical multimodal systems that perform real tasks55:00 Pixel's goal is democratizing high-quality three d scanning through smartphones, making mesh creation accessible to unlock applications in gaming cinema and virtual showroomsKey Insights1. Pixel Robotics derives its name from combining perception and action in robotics, where the pixel represents the digital perception component and robotics represents the physical action component. The pixel serves as a metaphor for how robots must quantize and digitize continuous analog information from the real world into discrete units that computer systems can process, similar to how pixels are the fundamental building blocks of images on a screen. This quantization process is essential because numerical systems cannot work with truly continuous data and must convert reality into tractable digital representations that algorithms can manipulate.2. The transformer architecture has created a fundamental unification in how different types of data can be represented and processed across multiple modalities. Before transformers, researchers working on natural language processing, computer vision, and audio analysis used completely different approaches and methodologies. The breakthrough of transformers was establishing a common representational framework that could handle text, images, voice, and other data types using similar underlying mechanisms. This unification is what enabled the development of truly multimodal AI systems and represents one of the most significant advances beyond just the language modeling capabilities that initially gained public attention.3. Current transformer-based systems represent a brute force approach to learning that will likely be superseded or enhanced by more efficient algorithms. Despite claims that we have exhausted internet text data for training, significant improvements continue to emerge every few months through algorithmic innovations rather than simply adding more data. Future developments will likely involve more specialize
- 2 weeks ago58 min
Episode #547: Dead Forests and Living Networks: Why the Future of Knowledge Looks Like Fungi, Not Filing Cabinets
In this episode of the Crazy Wisdom Podcast, host Stewart Alsop sits down with Joshua Bate, founder of Bonfires.ai and DeciWorld, for a wide-ranging conversation covering knowledge management, graph technology, ontologies, decentralized science, and the future of how humans organize and share information. They break down the differences between personal and enterprise knowledge management, explore why flat ontological graphs may be the key to making diverse knowledge bases interoperable, and get into why traditional RAG systems break down at scale and how graph RAG offers a more principled solution. The conversation expands into the philosophy of categorization, the slow death of basic "gentleman science" under institutional pressures, and how decentralized protocols might restore a kind of mycelial knowledge network connecting small groups of researchers, enthusiasts, and communities — much like the original spirit of the encyclopedia before it was co-opted by institutions. You can learn more about Joshua's work at bonfires.ai and deci.world or follow him on X at @Bonfiresai and @DeSciWorld.Timestamps00:00 - Stewart introduces Joshua Bate, founder of Bonfires.ai, discussing personal versus enterprise knowledge management and their fundamental differences at scale.05:00 - Joshua explains ontologies as classifiers for knowledge structures, describing their two-year search for a perfect ontology and ultimately building a flat, ontology-less graph protocol.10:00 - Stewart connects categorization to shamanic practice and intercategorical theory, noting how major companies like Netflix and Yahoo built graph-based ontologies while the discipline remains underappreciated philosophically.15:00 - Joshua traces Bonfires origins through decentralized science, explaining how NFT community excitement inspired redirecting capital toward funding unconventional researchers locked out of institutional systems.20:00 - Joshua describes building federated knowledge networks through hackathons and conferences, comparing the vision to what Wikipedia could have been with decentralized incentive structures.25:00 - Discussion shifts toward inevitable collapse of rigid scientific institutions, debating patchwork age theory, nation-state fragmentation, and rhizomatic versus arboreal knowledge structures.30:00 - Joshua articulates the mycelial network vision, enabling direct cross-cultural information access where individuals control their own narrative lens, warning against collective we thinking and authoritarianism.Key Insights1. Knowledge management exists on a spectrum from personal to enterprise, but the founder of Bonfires argues this split is artificial. He believes knowledge itself does not respect those boundaries, and that small groups, researchers, hobbyists, and large institutions all possess knowledge that can and should interoperate with each other.2. After two and a half years of searching for the perfect ontology to structure their knowledge graph, the team concluded that no perfect ontology exists. Their solution was to build the flattest possible graph structure with only events, entities, and edges, creating a base layer others can build specialized ontologies on top of.3. Graph-based knowledge systems are more efficient than traditional databases for AI traversal because once a graph is computed, it is relatively free to query. Graph RAG combines the discovery power of vector search with the structured precision of graph traversal, solving many hallucination problems associated with standard retrieval augmented generation.4. Basic scientific research, the soil from which applied discoveries grow, is deteriorating because institutional funding structures only reward commercially viable outcomes. The founder built his platform partly to redirect community-driven capital toward researchers who are doing important work without institutional support.5. The institutionalization of science has historically blocked the open exchange of ideas that drove the original scientific revolution. The human spirit for open inquiry has not changed, but people cannot pursue it without financial support, and building decentralized infrastructure could restore that possibility.6. A federated knowledge network would allow individuals to access information from any contributor and filter it through their own preferred lens, rather than receiving information pre-filtered by centralized platforms. This represents a form of information symmetry similar to how mycelial networks distribute nutrients across a forest.7. The concern is not whether current scientific and governmental institutions will change but in what direction the rebuilding goes. Those capitalizing on the transitio
- 3 weeks ago56 min
Episode #546: Beyond Postgres and Node.js: What Happens When Your Database Runs Your Code
In this episode of the Crazy Wisdom Podcast, host Stewart Alsop sits down with Tyler Cloutier, founder of Clockwork Labs and creator of SpaceTimeDB. They explore how SpaceTimeDB functions as more than just a database—it's essentially a distributed operating system that merges server logic with data storage, enabling real-time applications and time-travel capabilities. The conversation ranges from the technical architecture of databases and operating systems to the philosophy of distributed systems, touching on everything from Unix and Linux to how SpaceTimeDB could revolutionize AI-generated software deployment. Tyler explains how their system reduces the complexity of building real-time applications, makes deployment simpler for both humans and AI agents, and why games like their MMORPG BitCraft Online drove them to create this new infrastructure. They also discuss the future of the internet, the role of bots in gaming, and how SpaceTimeDB fits into the broader landscape of cloud computing alongside tools like Cloudflare, Vercel, and Docker. For more information, visit spacetimedb.com or check out Clockwork Labs on GitHub and Twitter.Timestamps00:00 Stewart introduces Tyler Cloutier, founder of Clockwork Labs, discussing the origin of SpaceTimeDB's name inspired by Einstein's theory and its time travel capabilities that store all operations indefinitely05:00 Tyler explains SpaceTimeDB as more of an operating system than a database, using tables instead of file systems while running code in a sandboxed environment with full atomic properties10:00 Discussion of how SpaceTimeDB replaces both Node.js and Postgres by merging web server and database functionality, eliminating separate deployment concerns15:00 Tyler explains JavaScript execution through Chrome's V8 engine and JIT compiling, leading to Node.js creation for server-side JavaScript development20:00 Explanation of stateless web servers versus stateful game servers, and why games require in-memory state management for real-time performance25:00 Tyler introduces reducers and real-time subscriptions, questioning why more applications aren't real-time when state changes should update immediately30:00 Discussion of Facebook as essentially a text-based MMO, comparing social media architecture to game server requirements and the need for unified systems35:00 Tyler explains ACID properties in databases: atomic, consistent, isolated, and durable, using game item trading examples40:00 Comparing SpaceTimeDB to smart contract systems without cryptocurrency or global consensus, positioning it as a smart database with centralized trust45:00 Tyler reveals SpaceTimeDB uses 43% fewer tokens than Postgres for AI-generated applications, making it valuable for vibe coding platforms50:00 Conversation shifts to bots in games and proof-of-human concepts, with Tyler proposing biometric systems and discussing potential in-person gaming applications55:00 Closing discussion about tracking AI-driven traffic through UTM parameters and finding SpaceTimeDB at spacetimedb.comKey Insights1. SpaceTimeDB is fundamentally a database that runs application code directly inside it, combining what traditionally required separate systems like Postgres and Node.js. Users compile their application logic into WebAssembly or JavaScript and upload it to run within the database itself. This architecture provides high performance because the entire server backend operates inside the database environment. The system also features time travel capabilities, storing every operation and change to data persistently and indefinitely, allowing users to set application state back to any earlier point in time. This makes SpaceTimeDB more accurately described as an operating system rather than just a database, where the abstraction is that everything is a table rather than a file.2. The inspiration for SpaceTimeDB came from building BitCraft Online, an MMORPG where all players exist in a single persistent world and rebuild civilization together. Traditional MMO backends required complex custom solutions to handle real-time state, with game servers storing state in memory and periodically writing to databases. This complexity existed because games cannot afford the latency of constantly delegating to distant databases like traditional web applications can. SpaceTimeDB solved this by making the database fast enough to handle real-time requirements directly, eliminating the need for separate game servers. This same performance advantage that benefits games also applies to web applications, which is why SpaceTimeDB evolved from a game-specific tool to a general-purpose platform.3. SpaceTimeDB functions as a distributed operating system where each database acts like
- May 4, 20261h 5m
Episode #545: Measuring the Unmeasurable: Agency, IQ, and the Men Who Change History
In this episode of Crazy Wisdom, Stewart Alsop sits down with Kieran Zimmer — a software developer and independent researcher in psychology and psychometrics — to explore the science behind intelligence and personality. They trace the origins of psychometrics from Wilhelm Wundt's early experimental psychology through Charles Spearman's discovery of the g factor, breaking down what IQ actually measures, how verbal, mathematical, and spatial intelligence relate to one another, and why training specific cognitive tasks doesn't translate into a broader boost in general intelligence. The conversation moves into the Big Five personality traits reframed through a cybernetic lens — looking at extraversion as reward sensitivity, agreeableness as social affiliation, and conscientiousness as long-term goal prioritization — before landing on Kieran's original research into the psychology of agency: what personality profile best predicts agentic behavior, and why the environment shapes whether agency is even adaptive in the first place.Show notes:Substack: Liminal RevolutionsTwitter/X: @LiminalRevYouTube: @TheKieranZimmer (to listen to Kieran's conference talk on the agency paper)Timestamps00:00 — Stewart and Kieran trace the origins of psychometrics back to Spearman, Binet, and Wilhelm Wundt's early experimental psychology.05:00 — The conversation unpacks the g factor, fluid vs. crystallized intelligence, and why IQ is fundamentally a physical trait tied to nerve conduction velocity.10:00 — A tangent into AI and LLMs: why they lack vision, taste, judgment, and accountability — the human moat that remains for now.15:00 — Stewart's Claude Code failure sparks a discussion on AI accountability, surveillance, and the rise of dystopian technocracy.20:00 — Parallel structures as a form of exit from failing institutions, and the high-agency people required to build them.25:00 — Agency, risk-taking, and accountability through Napoleon, the Inuit, and why modern Western leaders are managers, not leaders.30:00 — Elites vs. peasants, cost externalization, and Kirk Doolittle's natural law as the physics of cooperation.35:00 — Ressentiment, Nietzsche's under-utilization in psychology, and how secularism replaced the church.40:00 — Kieran's quantitative conspiracy theory study: factor analysis of 85 questions across 273 respondents.45:00 — Two branches of conspiracy belief: the aliens-and-Satanism cluster vs. the fakery factor pathway to Flat Earth.50:00 — AI psychosis, Gnosticism, and the collapse of sense-making institutions in an age of information overload.55:00 — Michael Levin's embodied cognition and cybernetic agency: thermostats, humans, and homeostatic set points.1:00:00 — The Cybernetic Big Five broken down: extraversion as reward sensitivity, agreeableness, neuroticism, and the optimal personality profile for agency.Key InsightsIQ is a physical trait, not just an abstract score. It's rooted in nerve conduction velocity, brain connectivity, and processing speed — and while you can improve crystallized intelligence through learning, the underlying g factor doesn't budge no matter how many brain training apps you use.The human moat against AI comes down to four things: vision, taste, judgment, and accountability. LLMs are powerful next-token predictors, but they have no stake in the outcome and no capacity to own a mistake — which means a human with those qualities will always be essential.High agency is not just ambition — it's a measurable psychological profile. Kieran's paper frames it through the Cybernetic Big Five: high assertiveness, high intellect, low politeness, low neuroticism, and medium conscientiousness. Getting things done at scale almost always involves upsetting people.All agentic behavior involves risk, and the willingness to absorb that risk is what separates real leaders from managers. Modern Western leadership has decoupled decision-making from consequence, which is why institutions are losing trust and authority at an accelerating rate.Conspiracy belief follows a measurable path dependency. Kieran's factor analysis showed that virtually everyone who believes in Flat Earth also endorses the fakery factor and the Jewish question cluster — bu
- Apr 27, 202650 min
Episode #544: Privacy Is the New Counterculture
In this episode of the Crazy Wisdom Podcast, host Stewart Alsop sits down with Cindy Cohn, Executive Director of the Electronic Frontier Foundation (EFF), for a wide-ranging conversation covering the EFF's origins and mission, the countercultural roots of Silicon Valley, the rise of surveillance-based business models, the challenges facing open source software and open-weight AI models, the legal landscape around intellectual property and privacy law, and the growing tension between government overreach and civil liberties in the digital age. Cindy also discusses her upcoming departure from EFF after 26 years, the transition to new leadership, and her recently published book Privacy's Defender, which chronicles key legal battles she fought to protect digital privacy rights.Links mentioned:- EFF website: eff.org- Privacy's Defender book: eff.org/privacysdefenderTimestamps00:00 - Stewart introduces Cindy Cohn, EFF Executive Director, who explains the organization's mission protecting digital rights since 1990.05:00 - Cindy connects counterculture roots to early internet idealism, describing how digital communication broke down physical barriers for organizing.10:00 - Cindy reveals surveillance becoming the dominant business model surprised her, blaming corporate consolidation over naive techno-optimism.15:00 - Discussion shifts to Silicon Valley's military contractor substrate and how corporate money co-opted hacker ethos.20:00 - Open source community faces existential threat from age verification legislation while open-weight AI models emerge as critical alternative.25:00 - Cindy outlines legal frameworks like compulsory licensing and easements that could democratize access to foundational AI models.30:00 - Privacy principles around secondary data use identified as core surveillance problem, with Anthropic's domestic surveillance red line praised.35:00 - Cloud Act, Five Eyes surveillance networks, and global jurisdictional complexity examined through individual threat modeling lens.40:00 - Constitutional rights and democratic participation framed as irreplaceable bulwarks against authoritarian surveillance tendencies.45:00 - Cindy announces departure from EFF after 26 years, naming successor Nicole Ozer while planning return to courtroom litigation.Key Insights1. The Electronic Frontier Foundation was founded in 1990, before the World Wide Web existed, by Mitch Kapoor, John Perry Barlow, and John Gilmore, with early support from Steve Wozniak. Its core mission is to ensure that civil rights and freedoms follow people into the digital world, using lawyers, technologists, and activists to keep the internet on the side of users.2. The early countercultural movement of the 1960s and 70s heavily influenced the founders of the internet and EFF. Figures like Barlow believed the digital world could reduce physical barriers like race, class, and geography, allowing people to be judged by the quality of their ideas rather than the circumstances of their birth.3. The dominant surveillance business model that emerged was not inevitable. Cohn argues it resulted from deliberate policy failures, particularly the abandonment of competition law, which allowed a handful of companies to consolidate control over the entire internet and adopt 360-degree data collection as their primary revenue strategy.4. Open source communities remain active and vital but are under serious threat from legislation like age verification laws that make it practically impossible to maintain fully open tools. Cohn sees this community as essential to reclaiming public control over computation, especially in the age of AI.5. The open weights question for AI models is fundamentally different from traditional open source software because of the enormous capital required to train foundation models. Cohn suggests legal mechanisms like compulsory licensing, similar to how cover songs work in copyright law, as one possible path toward broader public access.6. A core privacy principle Cohn advocates is that data collected for one purpose must not be used for others. This single rule, if enforced, would begin dismantling the infrastructure that enables mass individual surveillance, including the AI-powered profiling she sees as the next dangerous frontier.7. Cohn is stepping down from EFF after 26 years to allow new leadership and return to litigation, which is where she believes her impact is greatest. She also wrote a book called Privacy's Defender to preserve the history of digital rights fights from the 1990s onward and to help people understand how current threats emerged so they can work to reverse them.
- Apr 20, 202653 min
Episode #543: The Year of Agents and the Industries Not Ready for Them
In this episode of the Crazy Wisdom Podcast, host Stewart Alsop sits down with Mauro Schilman, CTO and Co-founder of Tuki, the distribution standard for the AI agent era in travel, for a wide-ranging conversation that moves from the joys of international travel and the beauty of mathematics to the fast-evolving world of AI and large language models. Mauro shares his background as a math Olympiad competitor and later a coach, his time training coding models at the AI company Cohere, and his thoughts on how frontier models are progressing — or plateauing — at the foundational level while innovation accelerates at the application layer. The two also get into the mechanics of agentic AI, MCP and agent-to-agent protocols, hierarchical memory systems, red-green test-driven development as a powerful coding workflow, and the philosophical murkiness of open-source AI. They wrap up discussing Tuki Travel's mission to build AI-ready infrastructure for the travel industry, connecting hotels, suppliers, and online travel agencies to prepare for the coming wave of agentic commerce. You can learn more about Tuki Travel and reach out to the team at tukiclub.com.Timestamps00:00 - Stewart welcomes Mauro Schilman, CTO and Co-founder of Tuki Travel, who shares how traveling since age 15 through high school exchanges opened his mind to cultural similarities and differences.05:00 - Mauro explains Math Olympiad coaching culture and mentorship, noting LLMs now solve competition-level problems while Terence Tao explores AI assisting frontier unsolved mathematics.10:00 - Discussion turns to ChatGPT revealing Mauro's birthdate unprompted, exposing opaque application layers, preference tuning, and system prompts hidden within closed models.15:00 - Mauro argues true open source AI requires full training data, annotation protocols, and alignment processes, not just model weights, while scaling laws appear to be slowing.20:00 - Hierarchical memory models replace flat vector databases, using three-level retrieval systems improving context accuracy as knowledge management becomes AI's core challenge.25:00 - Mauro describes travel's fragmented infrastructure of aggregators, bed banks, and intermediaries, explaining Tuki builds agent-ready unification protocols for AI commerce.30:00 - MCP versus API debate clarifies natural language capability descriptions help agents consume services, while agent-to-agent communication embeds negotiating agents inside supplier systems.35:00 - Hallucinations and consumer trust block agentic payments, industries must build mistake-resilience into bookings before autonomous agent transactions become viable.40:00 - Mauro reveals red-green test-driven development methodology where agents write failing tests first then implementations, creating Oracle verification loops dramatically improving code quality.45:00 - Blockchain's potential for transparent distributed AI training discussed, distinguishing democratization from decentralization while stable coins and regulatory momentum build toward agentic commerce infrastructure.Key Insights1. Travel broadens perspective by revealing both universal human similarities and deep cultural differences. Mauro Schilman began traveling at fifteen through math olympiad competitions and found that people across the world share fundamental traits while also being shaped in profoundly different ways by their cultures. This tension between sameness and difference is what makes travel meaningful.2. Mathematics transitions from structured problem-solving in olympiads to genuine uncertainty in graduate school and research. Olympiad problems are carefully designed with elegant solutions meant to encourage creative thinking, but once a mathematician enters academia, the answers are unknown and the work becomes navigating that uncertainty.3. AI is now assisting mathematicians at the frontier, not just solving olympiad-level problems. Terence Tao, one of the greatest living mathematicians, has written publicly about how AI tools can help tackle unsolved problems, though the role of AI remains assistive rather than independent at the research level.4. Large language models are not truly transparent even when described as open source. Releasing model weights alone does not reveal the training data, annotation protocols, alignment tuning, or system prompts that shape model behavior. Real openness would require access to the entire pipeline.5. Memory and retrieval remain core unsolved challenges in AI systems. Researchers are moving from flat vector database approaches toward hierarchical memory structures with roughly three layers, which improves retrieval accuracy and reduces how much context gets consumed with each search.6. The travel industry is structurally unprepared for AI agents. A hidden web of bed banks, aggregators, and
Get Crazy Wisdom summaries in your inbox
Free AI-powered daily recaps. Key takeaways, quotes, and mentions — in a 5-minute read.
Get Free Summaries →Free forever for up to 3 podcasts. No credit card required.
You Might Also Like
Listeners also like.
"The Cognitive Revolution" | AI Builders, Researchers, and Live Player Analysis
Interviews with AI developers and researchers exploring the transformative impact of artificial intelligence on society and technology.
80,000 Hours Podcast
Explores global challenges and practical ways individuals can contribute to solving them through in-depth interviews.
The AI XR Podcast
Experts discuss AI, augmented reality, virtual reality, and spatial computing with industry leaders and innovators.
Inner Cosmos with David Eagleman
Neuroscientist David Eagleman examines how the brain interprets reality through science, stories, and interviews.
Latent Space: The AI Engineer Podcast
Covers advances in AI engineering, including foundation models, code generation, and AI agents, through interviews with researchers and developers.
Possible
Explores optimistic visions of the future shaped by technology, AI, and innovative leaders across industries.
Intelligent Machines (Audio)
Explores the rise of artificial intelligence through conversations with pioneers shaping the future of intelligent machines.
Limitless: An AI Podcast
Explores the frontiers of technology and artificial intelligence.
Google DeepMind: The Podcast
A mathematician explores AI's real-world impact through behind-the-scenes insights from a leading research lab.
Modern Wisdom
Discussions with experts on psychology, philosophy, and self-improvement to help navigate life’s challenges.
AI and I
Interviews with professionals who use AI tools in their work, exploring how AI affects creativity, thinking, and daily life through live demonstrations.
How I AI
A practical guide to using AI tools in work and life, featuring guests who share specific, actionable techniques and workflows.
About Crazy Wisdom
In his series "Crazy Wisdom," Stewart Alsop explores cutting-edge topics, particularly in the realm of technology, such as Urbit and artificial intelligence. Alsop embarks on a quest for meaning, engaging with others to expand his own understanding of reality and that of his audience. The topics covered in "Crazy Wisdom" are diverse, ranging from emerging technologies to spirituality, philosophy, and general life experiences. Alsop's unique approach aims to make connections between seemingly unrelated subjects, tying together ideas in unconventional ways.
Customized Recaps
AI-powered recaps with compact key takeaways, quotes, and insights.
Straight to Your Inbox
Get key takeaways from Crazy Wisdom in a 5-minute read.
Save Hours Every Week
Stay current on your favorite podcasts without falling behind.
Frequently Asked Questions
What is Podzilla's Crazy Wisdom daily summary?
It's a free AI-powered email that summarizes new episodes of Crazy Wisdom as soon as they're published. You get the key takeaways, notable quotes, and links & mentions — all in a quick read.
How does the Crazy Wisdom podcast summary work?
When a new episode drops, our AI transcribes and analyzes it, then generates a personalized summary tailored to your interests and profession. It's delivered to your inbox every morning.
Is this an official Crazy Wisdom product?
No. Podzilla is an independent service that summarizes publicly available podcast content. We're not affiliated with or endorsed by Stewart Alsop.
Can I get summaries of other podcasts too?
Absolutely! The free plan covers up to 3 podcasts. Upgrade to Pro for 15, or Premium for 50. Browse our full catalog at /podcasts.
How often does Crazy Wisdom release new episodes?
Crazy Wisdom publishes weekly. Our AI generates a summary within hours of each new episode.
What topics does Crazy Wisdom cover?
Crazy Wisdom covers topics including Philosophy, Culture, Society & Culture. Our AI identifies the specific themes in each episode and highlights what matters most to you.
Start getting Crazy Wisdom summaries tomorrow morning.
Free forever for up to 3 podcasts. No credit card required.
Free forever for up to 3 podcasts. No credit card required.