Squid Game is back—and this time, the knives are out. In the thrilling Season 3 premiere, Player 456 is spiraling and a brutal round of hide-and-seek forces players to kill or be killed. Hosts Phil Yu and Kiera Please break down Gi-hun’s descent into vengeance, Guard 011’s daring betrayal of the Game, and the shocking moment players are forced to choose between murdering their friends… or dying. Then, Carlos Juico and Gavin Ruta from the Jumpers Jump podcast join us to unpack their wild theories for the season. Plus, Phil and Kiera face off in a high-stakes round of “Hot Sweet Potato.” SPOILER ALERT! Make sure you watch Squid Game Season 3 Episode 1 before listening on. Play one last time. IG - @SquidGameNetflix X (f.k.a. Twitter) - @SquidGame Check out more from Phil Yu @angryasianman , Kiera Please @kieraplease and the Jumpers Jump podcast Listen to more from Netflix Podcasts . Squid Game: The Official Podcast is produced by Netflix and The Mash-Up Americans.…
Stewart Alsop III reviews a broad range of topics with his father Stewart Alsop II, who started his career in the personal computer industry and is still actively involved in investing in startup technology companies. Stewart Alsop III is fascinated by what his father was doing as SAIII was growing up in the Golden Age of Silicon Valley. Topics include: - How the personal computing revolution led to the internet, which led to the mobile revolution - Now we are covering the future of the internet and computing - How AI ties the personal computer, the smartphone and the internet together
Stewart Alsop III reviews a broad range of topics with his father Stewart Alsop II, who started his career in the personal computer industry and is still actively involved in investing in startup technology companies. Stewart Alsop III is fascinated by what his father was doing as SAIII was growing up in the Golden Age of Silicon Valley. Topics include: - How the personal computing revolution led to the internet, which led to the mobile revolution - Now we are covering the future of the internet and computing - How AI ties the personal computer, the smartphone and the internet together
Welcome to Stewart Squared podcast with the two Stewart Alsops. In this episode, they explore the OpenAI–Microsoft partnership through the lens of historic “stupid agreements” in tech, starting with Software Arts and VisiCorp’s flawed VisiCalc deal. The conversation traces the evolution of tech bubbles from the early software industry to today’s AI hype, questioning whether artificial general intelligence (AGI) is a real milestone or just a moving target. They discuss DARPA’s shifting role from Cold War-era innovation to grantmaking and debate whether private companies like Elon Musk’s ventures or Anduril are now the true engines of R&D. The episode also examines drone warfare’s impact on modern conflicts, Israel’s Iron Dome under pressure, and whether drones are redefining the roles of missiles and artillery. Alongside these threads, they touch on social media’s possible collapse under the weight of AI companions and how military tech spillovers have historically fueled civilian innovation. Check out this GPT we trained on the conversation Timestamps 00:00 – Opening with the OpenAI–Microsoft partnership, comparing it to the VisiCalc deal between Software Arts and VisiCorp as an early example of “stupid agreements” in tech. 05:00 – Exploring AGI as a moving target, historical shifts in AI definitions, and Zuckerberg’s push for a superintelligence lab with Jan LeCun and Alexander Wang in the spotlight. 10:00 – Early tech bubbles from 1979–1983, the rise of software distribution models, and parallels to modern AI and social media ecosystems. 15:00 – The decline of DARPA’s direct innovation role, outsourcing research to academia and private R&D, and the rise of venture capital replacing the “D” in R&D. 20:00 – Elon Musk’s Neuralink and SpaceX as examples of private moonshots, with reflections on China’s industrial strategy and Anduril’s challenge to defense giants. 25:00 – Drone warfare’s transformative role in Ukraine and Israel, Iron Dome’s performance under Iranian missile barrages, and hypersonic missile threats. 30:00 – Predictions about the death of social media, the rise of AI companions replacing human interaction, and concerns over dependency on chatbots. Key Insights The episode opens by framing the OpenAI–Microsoft partnership as part of a long lineage of “stupid agreements” in tech history, comparing it to the 1979 deal between Software Arts and VisiCorp over VisiCalc. That deal, which offered unusually high royalties to the developer, illustrates how early software companies lacked models for fair agreements, much like today’s AI partnerships are navigating uncharted territory without clear definitions of AGI or its implications. AGI itself is questioned as a concept, with the Stewarts noting it has always been a moving target. What was considered “intelligent” decades ago—like natural language processing or chatbot interactions—no longer qualifies, and they suggest AGI may never arrive in the way science fiction imagines. Instead, the focus has shifted to “superintelligence” as a rebranded goal, driven as much by marketing and competition as by real technical progress. The discussion highlights how DARPA’s role has diminished since its Cold War peak, transitioning from direct research leadership to a grant-disbursing organization. Today, the best researchers are often lured away by private firms offering massive pay packages, leading to concerns that the U.S. government has lost the capacity for “moonshot” innovation and now depends on companies like SpaceX, Neuralink, and Anduril to carry the torch. The Stewarts examine the rise of Anduril and similar startups as existential threats to legacy defense contractors like Lockheed Martin and Northrop Grumman. These incumbents are described as slow-moving monopolies that rely on cost-plus contracts, while newcomers promise faster, cheaper, and more modern systems to meet evolving military needs. Drones emerge as a central theme in discussing the changing nature of warfare. Rather than replacing missiles outright, drones are creating new tactical possibilities, from Ukraine’s improvised attacks on Russian bombers to Israel’s use of drones to preempt missile launches. This shift suggests a future where drones and missiles coexist but with differentiated roles. The episode also critiques the societal impact of AI, noting growing reports of “ChatGPT psychosis,” where users form unhealthy dependencies on chatbots. This feeds into a broader prediction about the “death of social media,” as AI companions may one day supplant human relationships online, raising ethical and psychological concerns. Finally, they reflect on the cyclical nature of technology bubbles—from semiconductors and personal computing to social media and AI—arguing that hype cycles are inevitable but also essential for driving experimentation, investment, and eventual breakthroughs, even if most fail to deliver on their promises.…
Welcome to Stewart Squared podcast with the two Stewart Alsops, where they explore the evolution of software from 1.0’s “magical incantations” to 3.0’s natural language interfaces, discuss operating systems and their hardware roots, and unpack the significance of vertical integration exemplified by Apple’s silicon and software unification. This episode touches on large language models as cognitive prosthetics and the intimate, sometimes emotional, relationships people are forming with them, while also questioning their potential as operating systems for an “Internet-as-a-computer” paradigm. Alongside reflections on curiosity versus intelligence and the risks of Skynet-like scenarios, the Alsops weave in insights from Andrej Karpathy and Stephen Wolfram. Check out this GPT we trained on the conversation Timestamps 00:00 Software 1.0 to 3.0 evolution, natural language as programming, operating systems history with Apple II and early hardware tinkering 05:00 Open versus closed systems, Apple’s vertical integration, hardware limitations, early networking with Ethernet and modems 10:00 Distributed computing, Internet as a computer, LLMs as potential operating systems, differences between real-time systems and batch processing 15:00 Cognitive prosthetics, LLMs enabling new forms of software creation, emotional relationships with AI, sycophancy and “glazing” effects 20:00 Skynet fears, military applications of AI, robotics as physical extensions of AI, IoT devices and infrastructure vulnerability 25:00 Device Authority, over-the-air updates, challenges of retrofitting legacy hardware, enterprise resistance to innovation, IT culture dynamics 30:00 Curiosity versus intelligence, human adaptability, LLMs lack of intrinsic curiosity, future of AI-human collaboration, ending reflections on staying engaged with technology Key Insights The transition from software 1.0 to 3.0 marks a profound shift in how humans interact with machines, moving from cryptic programming languages to natural language interfaces that let anyone issue commands without technical expertise. This evolution democratizes programming but also raises questions about how much control we’re surrendering to systems we no longer fully understand. Operating systems once served as the invisible backbone of personal computing, managing resources and hardware interactions in machines like the Apple II. Today, as computing shifts into distributed networks and cloud systems, the concept of an OS is becoming more abstract, raising the possibility that LLMs could function as an “Internet-wide operating system” in the future. Vertical integration, as exemplified by Apple’s control over both hardware (Apple Silicon) and software (macOS), creates performance and efficiency advantages that competitors like Microsoft struggle to match. However, it also limits user freedom and reinforces a “walled garden” model that frustrates programmers who crave open systems. Large language models are increasingly viewed as cognitive prosthetics—tools that augment human thinking, accelerate research, and enable non-programmers to build software. Yet their growing intimacy with users sparks debates about the emotional bonds people are forming with AI and whether these relationships fulfill or erode our social and emotional needs. The Skynet metaphor highlights fears that AI could one day control critical infrastructure, but for now, the more immediate issue may be subtle—how LLMs shape human cognition, amplify sycophancy (“glazing”), and replace real human interactions with simulated ones that feel authentic but lack depth. Curiosity, not raw intelligence, emerges as the defining trait for effectively engaging with new technologies. Unlike AI, which lacks intrinsic curiosity, humans have the ability to wonder and explore, positioning us as perpetual learners even in an age of rapid technological advancement. The integration of IoT devices into legacy systems, as seen with companies like Device Authority, underscores both the promise and complexity of connecting the physical world to the Internet. Real-time updates and over-the-air security patches hint at a future where all devices are online, but this also amplifies vulnerabilities in critical infrastructure if AI systems gain too much autonomous control.…
Welcome to Stewart Squared podcast with the two Stewart Alsops. In this episode, they explore why consultants often fail in the tech world, how leadership skills are (or aren’t) taught in business schools, and the historical tension between technical and non-technical CEOs. They trace the evolution of Silicon Valley’s culture, from the idealistic hackers of the PC revolution to Amazon’s strategic rise with AWS and its CIA contract, and discuss whether institutional knowledge should be centralized or decentralized inside corporations. The conversation ranges from the origins of corporations and supply chain mastery at Apple, to predictions with LLMs, IoT security challenges, and even why Google struggles to innovate beyond its search monopoly. Show notes include a recommendation to read Apple in China for deeper insight into Apple’s role in training millions of Chinese factory workers. Check out this GPT we trained on the conversation Timestamps 00:00 – Opening with Stewart Alsop III teasing topics like why consultants fail in tech and the theory that post-founder CEOs rarely succeed, leading into the history of McKinsey and the Big Five consulting firms. 05:00 – Critique of MBA programs for focusing on analysis over leadership , discussion of Stanford GSB and Harvard HBS networks, and whether leadership can be taught . 10:00 – Exploration of technical vs non-technical CEOs in Silicon Valley, examples like Steve Jobs , Larry Ellison , and the early PC industry’s bias against consultants. 15:00 – Deep dive into Amazon Web Services , Andy Jassy’s startup-first strategy, and AWS’s CIA cloud contract , plus Oracle’s legal battles over DoD’s JEDI contract. 20:00 – Debate on AI prediction limits , the MIT SEAL framework for updating LLM weights, and real-time adaptability in AI models. 25:00 – Examination of corporations as knowledge bodies , historical roots in Dutch East India Company , and the tension between centralized vs decentralized knowledge . 30:00 – Focus on institutional memory , Apple’s supply chain with Tim Cook, United Airlines’ IT transformation , and IoT security risks . 35:00 – Insights on device authentication , Device Authority’s IoT security approach, and vulnerabilities like Stuxnet . Key Insights Consultants often fail in tech leadership because they lack deep domain expertise and tend to focus on analytical frameworks over practical execution. The Alsops argue that consultants are great at creating presentations and identifying what companies should have done but struggle to navigate the messy realities of running large, complex organizations—highlighted by the Webvan example where a consultant-turned-CEO helped drive the company into bankruptcy. Business schools train analysts, not leaders , equipping graduates with skills in spreadsheets, case studies, and presentations rather than fostering the hands-on leadership required in startups and tech firms. While MBAs can be valuable for networking and strategy roles, they often fall short in preparing executives to scale companies or inspire teams in rapidly changing environments. Technical and non-technical CEOs shape companies differently , with early Silicon Valley favoring technical founders like Gates and Wozniak. However, leaders like Steve Jobs and Larry Ellison thrived without deep technical skills by surrounding themselves with strong technical co-founders, showing that vision and communication can sometimes outweigh engineering chops in the CEO role. Amazon’s AWS strategy illustrates effective knowledge transfer and scaling , starting with a focus on startups and evolving to win contracts like the CIA’s cloud infrastructure. Andy Jassy’s ability to scale AWS from an internal tool to a dominant cloud service underscores how decentralized initiatives can later become centralized strengths when aligned with leadership vision. The SEAL framework represents a breakthrough for LLMs , enabling models to update their weights post-deployment for real-time learning. This adaptation could blur the line between static and dynamic AI systems and marks an early step toward meta-learning, raising both exciting possibilities and existential concerns about machine autonomy. Institutional knowledge must balance centralization and decentralization . Centralized databases simplify operations, as seen in United Airlines’ customer system, but decentralized human knowledge prevents organizations from collapsing when key people leave. Apple’s reliance on Tim Cook as its operational brain is cited as both a strength and a cautionary tale about knowledge bottlenecks. IoT security remains a critical and under-addressed challenge , with billions of devices running outdated software and exposing organizations to risk. Companies like Device Authority are working on real-time device identification and updates, but widespread implementation lags, creating vulnerabilities that even nation-state hackers have exploited, as in the Stuxnet incident.…
Welcome to Stewart Squared podcast with the two Stewart Alsops. In this wide-ranging conversation, the Stewarts kick off with a personal dive into the early days of Internet telephony via Netscape and InSoft, but quickly spiral into the present, grappling with the geopolitical consequences of space-based surveillance, the moral bankruptcy of Trump’s crypto antics, and the disturbing creep of domestic surveillance powers enabled by legal shifts like the Patriot Act and recent Supreme Court decisions. They challenge the legitimacy of the “information age,” weigh the ethical decay of digital privacy, and question whether secrets still even exist in a world of ubiquitous data exhaust. There’s a nostalgic look back at the Internet’s libertarian roots and a skeptical examination of Silicon Valley’s AI singularity fantasies. Check out this GPT we trained on the conversation Timestamps 00:00 – The Stewarts open with a discussion about Dan Harple, InSoft, and early VoIP innovations that shaped the collaborative Internet. 05:00 – Reflections on Internet fuzziness, recording tech like Riverside, and technical limitations tied to real-time protocols. 10:00 – Elon Musk’s disregard for users, contrasts with Steve Jobs’ proxy-customer mindset, and Musk's link to Dogecoin and meme coins. 15:00 – Trump’s exploitation of crypto, his meme coin grift, and the strategic chaos of his economic and political volatility. 20:00 – Low Earth orbit satellites, surveillance capabilities from Planet Labs and Starlink, and their implications for military intelligence. 25:00 – The U.S. surveillance state's evolution, with concerns over the Supreme Court's stance on personal data access. 30:00 – Facebook’s shift from dopamine to precise micro-targeting, the power of digital exhaust, and the illusion of privacy. 35:00 – Decline of the open web, rise of mobile walled gardens, AI’s role in the singularity debate, and tech overload. 40:00 – Conservation tech, fish genetics, hatchery ethics, and sustainable trout farming. 45:00 – Sushi quality, fish farming economics, and Argentine immigration policy linked to investment and potential farm ventures. Key Insights From VoIP to Surveillance Infrastructure : The episode highlighted how early innovations like Voice over Internet Protocol (VoIP) and real-time collaboration tools, pioneered by figures like Dan Harple, laid the groundwork for today’s surveillance capabilities. Originally developed for open communication, these technologies now serve as key components in data collection and monitoring systems. Musk vs. Trump – Competing Archetypes of Tech Power : The discussion contrasted Elon Musk’s technocratic ambition with Donald Trump’s transactional politics. While Musk is portrayed as indifferent to individuals but driven by achievement, Trump’s embrace of meme coins and political spectacle reflects a more cynical, extractive use of technology for personal gain. Low Earth Orbit and the New Geopolitics : With companies like Starlink and Planet Labs dominating satellite deployment, space has become a platform for near-constant Earth surveillance. The episode underscored how these technologies reshape global power dynamics, enabling both transparency and escalation in geopolitical conflicts. The Quiet Collapse of Privacy Norms : Once a bipartisan value, data privacy has eroded under legal and technological pressures. The episode referenced a recent Supreme Court decision as a symbol of this shift, where previously protected personal information is now more accessible to both state and commercial actors. Facebook and the Commodification of Attention : The podcast explored how Facebook transitioned from building user engagement through dopamine-driven interaction to enabling hyper-targeted advertising. This commodification of “digital exhaust” allows even small businesses to exploit personal data, narrowing the gap between mass surveillance and marketing. The Decline of the Open Web : The once-promised free and open Internet has given way to walled gardens dominated by mobile apps and corporate platforms. The episode positioned this shift as a betrayal of 1990s digital idealism, reducing user agency and consolidating power in the hands of a few tech giants. The Singularity as a Sci-Fi Distraction : The notion of merging with machines to prevent AI apocalypse was critiqued as a fantasy peddled by Silicon Valley elites. Instead, the real danger lies in how humans are already misusing AI to consolidate control, erode privacy, and perpetuate inequality.…
Welcome to Stewart Squared podcast with the two Stewart Alsops. This episode navigates the arc of the Internet’s transformation from the promise of an open network to the reign of closed platforms, tracing roots from AOL to mobile Facebook. The Stewarts debate algorithmic influence on user agency, reflect on early computing culture through anecdotes about VisiCalc and orthogonality, and critique the rise of AI devices like the Limitless pendant—linking it to Sam Altman's tangled investment trail and speculative visions of screenless tech. Their dialogue touches on Silicon Valley's philosophical shift—from engineering pragmatism to fantastical thinking—and asks whether companies like Google and Apple have the institutional structures to evolve meaningfully in the AI era. Check out this GPT we trained on the conversation Timestamps 00:00 – Discussion opens on the walled garden concept, contrasting early open Internet ideals with Facebook and AOL's closed models. 05:00 – Shift to Facebook mobile and how the app's design deepened platform control, suppressing outbound links via algorithmic downgrading . 10:00 – Exploration of what algorithms are, including foundational insights from VisiCalc and orthogonal programming logic. 15:00 – Critique of fantastical thinking in Silicon Valley: effective altruism , Singularity , and AI determinism vs. randomness. 20:00 – Deep dive into AI devices , focusing on the Limitless Pendant , its usability issues , and Sam Altman's conflicted role as early investor. 25:00 – Speculation on hardware innovation , Raspberry Pi and Arduino , and ethical concerns around investing in competitors. 30:00 – Analysis of Google’s product culture , its failure in product management , and DeepMind's limited integration. 35:00 – Reflection on monopolistic behavior , moonshot divisions , and overfunding as a source of magical thinking . 40:00 – Final thoughts on institutional IT , comparing Apple , Netflix , and Chinese firms like Huawei in real-time software integration . Key Insights The Internet's Evolution into Walled Gardens : The Stewarts reflect on the shift from an open, user-driven Internet to a closed ecosystem dominated by platforms like Facebook and Twitter. While early services like AOL were walled gardens, there was a middle era of openness with the rise of the web. The arrival of mobile apps—especially Facebook's mobile transition—cemented a new kind of user lock-in, where links out are suppressed and attention is algorithmically contained. Mobile as the Turning Point : The transition of Facebook to mobile marked a pivotal shift. Initially resistant to app development because of its open web ethos, Facebook eventually embraced mobile, realizing it granted total control over the user experience. This catalyzed the modern model of platform dominance, where linking out is discouraged and algorithmic prioritization curates user attention. Algorithm Awareness and Cultural Impact : The rise of social media brought public awareness of algorithms as tools that influence behavior and visibility. What was once a backend concept known only to programmers became part of everyday language. The Stewarts trace this shift to platforms like Instagram and Facebook, which made algorithmic curation central to user experience and discourse. AI Devices and the Limitless Pendant : Stewart II reviews the Limitless pendant, a wearable AI device that records conversations and summarizes them, calling it a “peek into the future” with usability flaws. The device’s origins as Rewind AI and its investment from Sam Altman raise ethical questions, especially now that Altman is backing potentially competing ventures like Jony Ive’s AI projects. Magical Thinking in Silicon Valley : The episode critiques Silicon Valley’s drift from engineering rigor to speculative idealism—highlighting effective altruism, singularity thinking, and techno-utopian visions. They note how once-practical cultures are now marked by dualisms: doomer vs. accelerationist, utopian vs. dystopian, with little room for nuanced middle grounds. China’s Role in Tech Innovation : Huawei’s expansion into cars prompts a reflection on whether Chinese firms’ multi-domain innovation reflects cultural differences. The Stewarts ponder whether China’s success is driven by collective orientation or state direction, and what it implies for U.S. competitiveness in hardware and manufacturing. Institutional Knowledge and IT Competence : The episode closes on the importance of institutional IT knowledge, citing Apple and Netflix as companies that deeply understand their operational infrastructure. This understanding, they argue, enables better product development and company coherence—unlike firms that spray money across moonshots without disciplined management.…
Welcome to Stewart Squared podcast with the two Stewart Alsops. In this episode, father and son trace the tectonic shifts that shaped Silicon Valley—from the amateur hardware tinkerers at the Homebrew Computer Club to the institutional rise of venture capital and its entanglement with military-industrial imperatives. They explore how Boston, Texas, and even Johannesburg played pivotal but ultimately eclipsed roles in the story, and how Silicon Valley's dominance crystallized through a nexus of research labs, open-minded capital, and cultural disruption. Alongside this historical cartography, they reflect on the layered timelines of big science, Cold War paranoia, and the countercultural refusal of institutional baggage, ultimately turning to how recent phenomena like zero interest rate policies and AI threaten—or promise—to rewire the very conditions of innovation. Check out this GPT we trained on the conversation Timestamps 00:00 – The episode opens with a discussion of the Homebrew Computer Club , where Steve Jobs and Wozniak famously appeared, and the early culture of chip-based computing. 05:00 – Stewart II contrasts Boston’s tech scene with Silicon Valley, highlighting early software like VisiCalc and mentioning Digital Equipment Corporation. 10:00 – Texas enters the conversation with references to Texas Instruments , TRS-80 , and Dell , showing how multiple regions once vied for tech dominance. 15:00 – The idea of Silicon Valley as a nexus of research, capital, and counterculture is traced to figures like William Shockley and institutions like Xerox PARC and SRI . 20:00 – Discussion shifts to San Francisco’s rise in the 2000s, the scale explosion brought by Y Combinator , and Stewart’s discomfort with billion-dollar VC models. 25:00 – Reflection on entrepreneurship as career path , StartX , and the emotional legacy of the ZIRP era —the “decade of free money.” 30:00 – A generational lens is applied to AI’s existential questions , with Stewart II offering faith in humanity’s adaptive capacity through technological transition. 35:00 – Dialogue deepens around digital finance , WeChat , and legacy infrastructure , using China’s leapfrogging as a case study in systemic change. 40:00 – Final reflections explore AI as a systemic renovator , drawing analogies to mobile adoption in South Africa and the potential for additive manufacturing to reinvent U.S. industry. Key Insights The Mythos of the Homebrew Club and Its Absences The Homebrew Computer Club emerges as a foundational myth in Silicon Valley lore, but Stewart Alsop II never attended—an absence that frames a broader reflection on who gets written into the tech origin story. The club’s significance lies in its function as a pre-commercial commons for chip enthusiasts and its symbolic association with the birth of Apple, even though it was already fading by the early 1980s. Geographies of Innovation Before Silicon Valley's Ascendance The episode underscores that early tech innovation was not confined to the Bay Area. Boston, with its minicomputer firms like DEC, and Texas, home to Radio Shack and Dell, were vibrant nodes in a decentralized network of technological experimentation. Each region had its moment—Boston through software like VisiCalc, Texas through hardware initiatives—but ultimately lacked the long-term convergence of capital, talent, and ideology found in Silicon Valley. Shockley’s Migration as a Founding Event William Shockley’s relocation to Menlo Park is framed as a peculiar yet pivotal act that catalyzed the formation of Silicon Valley. His recruitment of engineers to form Shockley Labs inadvertently seeded the future semiconductor industry, triggering spin-offs that would define the region’s trajectory. Dual Timelines: Big Science and Cold War Contracts The rise of Silicon Valley is interwoven with two orthogonal timelines: one of entrepreneurial experimentation and the other of military-industrial entrenchment. The Manhattan Project and Cold War defense spending created institutional pathways and research funding structures that undergirded the region's growth, even as the countercultural ethos outwardly rejected such alignment. Venture Capital as Cultural Infrastructure Beyond just funding, venture capital is described as a social technology. Early figures like Arthur Rock provided not just money but validation and narrative momentum. The episode notes how this infrastructure matured into a formal system in the late 1970s, providing the necessary scaffolding for the explosion of startups in the 1980s and beyond. Counterculture and the Refusal of Legacy Systems The desire to break with the mainframe era and build something radically new—personal computing—was driven by a generation influenced by the 1960s counterculture. This ethos not only shaped the values of founders like Steve Jobs but also informed the informality and improvisational quality of early Silicon Valley ventures. Contemporary Fractures and the Leapfrog Metaphor Finally, the episode situates current technological disruptions—AI, digital finance, additive manufacturing—as opportunities to “leapfrog” outdated systems. This mirrors how South Africa bypassed wired infrastructure with mobile networks. Silicon Valley’s challenge now is whether it can reinvent itself without being bound by its own myths and legacy.…
Welcome to Stewart Squared podcast with the two Stewart Alsops, where this episode takes you on a ride through vibe coding experiments, AI-powered doom loops, and the fading utility of language learning apps like Duolingo in a world of real-time translation glasses. Stewart Alsop shares how he replaced Descript with Claude-generated code, while Stewart II unpacks the uncanny valley between needing to understand code and getting the machine to do it for you. They riff on the evolution of Apple’s infrastructure, Unix origins, the role of kernels, and Microsoft’s unlikely embrace of open source. There’s also a tribute to Cursor, the AI-infused IDE built on VS Code, and talk of enterprise LLMs like McKinsey’s internal model. Expect a whirlwind of anecdotes from student visa bureaucracy in Buenos Aires to early software packaging in Ziploc bags. Check out this GPT we trained on the conversation Timestamps 00:01 Stewart Alsop introduces "vibe coding" and his experience replacing Descript with an AI-built solution. 01:28 Stewart II discusses Google's real-time transcription and translation technologies and their potential impact on language learning. 04:24 Stewart Alsop explains his probabilistic "vibe coding" workflow using Claude and Gemini to build applications. 06:19 The role of Cursor IDE in providing visibility into AI-generated code and the dilemma of learning versus relying on AI. 12:50 Discussing the fundamental shift from deterministic to probabilistic approaches in computer science due to LLMs. 18:48 Tracing the history of Unix, Apple, and Microsoft operating systems and their respective kernel developments. 45:03 How AI might fulfill the promise of integrating siloed enterprise data, a concept Ray Ozzie explored with Lotus Notes. 47:57 Examining Apple's highly integrated IT system as a model for enterprise efficiency and control. 56:35 The potential impact of tariffs on global manufacturing, supply chains, and the economy. Key Insights Probabilistic "Vibe Coding" : AI-driven coding is inherently probabilistic. Unlike traditional deterministic programming, using LLMs like Claude for coding, or "vibe coding" as I call it, means outcomes aren't guaranteed. Prompts can yield perfect results, better-than-expected innovations, or frustrating "doom loops" of errors, making it a psychologically unique experience. The Uncanny Valley of AI Skill : Navigating AI coding puts users in an "uncanny valley" of knowledge. One needs enough understanding to craft effective prompts and debug AI-generated code (e.g., using tools like Cursor for visibility), yet deep traditional coding expertise might become less critical as AI improves, creating a difficult balance. Legacy Tech's LLM Adaptation Challenge : Established companies may struggle to adapt to the LLM revolution. Businesses like Descript or Duolingo, with set processes and products, might find it hard to pivot quickly and fully leverage LLMs, potentially falling behind more agile or AI-native solutions. Real-Time AI's Transformative Potential : Real-time AI for tasks like transcription and translation is becoming highly effective. Tools like Google Live Transcribe and Translate demonstrate near-perfect capabilities, which could fundamentally change the necessity and approach to learning foreign languages for purely functional communication. The Shift from Deterministic to Probabilistic Computing : LLMs signify a major paradigm shift in computer science. We're moving from an era dominated by deterministic logic, where inputs predictably produce specific outputs, to a probabilistic one where AI generates responses based on likelihood, requiring new ways of thinking and working. Enterprise AI for Data Integration : AI holds significant promise for solving enterprise data silos. Just as Ray Ozzie envisioned with Lotus Notes, modern AI, especially custom-trained LLMs, could enable companies to integrate vast, disparate datasets, unlocking new insights and efficiencies, though this remains a complex challenge. Apple's Vertically Integrated IT Prowess : Apple's sophisticated, vertically integrated IT system is a masterclass in operational control. Their ability to manage the entire chain from silicon design to manufacturing, software, and customer delivery through tightly integrated systems showcases a level of control and efficiency few other companies achieve.…
Welcome to Stewart Squared podcast with the two Stewart Alsops. In this episode, we talk about what happened to trust—why it’s gone, where it went, and whether it can be rebuilt. We go from the 1990s paranoia about driver’s licenses to today’s AI-powered pendants that record everything, from the erosion of open internet ideals to the rise of app store monopolies. We compare Apple’s branding collapse to meme coin absurdity, reflect on the fallout from 2008, and wrestle with whether open source and individual agency can still offer an exit ramp. Sam Altman, Trump, China, and the App Store all make appearances. Check out this GPT we trained on the conversation Timestamps 00:45 Stewart Alsop II on the evolution of driver's licenses, digital identity, and government ID. 03:31 Discussing the Limitless Pendant: real-time transcription, unmet expectations, and the "Life Log" concept. 09:06 From "vaporware" announcements to today's premature product releases in the tech and AI space. 11:26 Apple Intelligence as a case study in how tech companies can damage long-built consumer trust. 18:47 How the iPhone's App Store model fundamentally created walled gardens and changed the open internet. 22:36 Revisiting the "Evernet" thesis: the implications of persistent, high-speed internet connectivity. 35:33 The argument that declining trust in US institutions predates and influenced the social media explosion. 44:56 Exploring whether open-source AI offers a decentralized alternative to trust issues with big tech AI. 51:18 Delving into the origins of the Evernet thesis (circa 2008-2009) and its relevance today for cloud storage and enterprise. Key Insights The Privacy Shift: We've journeyed from a 90s-era paranoia about government surveillance surrounding things like driver's licenses to an age where personal data is constantly captured and processed by AI, often through devices like the Limitless Pendant. This marks a significant societal recalibration of privacy expectations and acceptance of ubiquitous recording. From Vaporware to Premature Release: The tech industry's historical issue with "vaporware"—products announced far ahead of actual delivery—has largely inverted. Now, particularly in the AI sector, companies frequently release products in a nascent state, effectively making early adopters beta testers and risking an initial erosion of trust. Trust as the Core Commodity: Echoing Steve Jobs' philosophy, brand strength is fundamentally built on trust, which is earned through positive experiences and diminished by negative ones. Current trends, such as Apple's "Apple Intelligence" announcement perceived as overpromising, and the broader rush to market with unfinished AI, are actively damaging this crucial trust with consumers. The iPhone's Internet Reformation: The introduction of the iPhone, and specifically its App Store ecosystem, represented a pivotal moment that reshaped the internet. It guided users away from the open web and into curated "walled gardens," granting platform owners like Apple considerable control and arguably curtailing the initial promise of a completely open internet. The Evernet Manifested: My "Evernet" thesis, predicting persistent, high-speed internet connectivity across all devices, has largely become our reality. This constant connection is the bedrock of modern cloud services, social media, and our digital interactions, but it also facilitates the continuous data flow central to current privacy and trust dilemmas. Pre-Existing Institutional Distrust: The decline in public trust towards institutions like government and mainstream media was a trend already in motion before the rise of social media. This pre-existing skepticism may have actually fueled social media's explosive growth, as these platforms emerged in an environment where traditional authorities were already losing credibility. AI: A Localized Path to Trust?: While large, centralized AI models from major corporations might perpetuate existing trust issues, there's a glimmer of hope in open-source AI and locally-run applications. Empowering individuals to build, customize, and control their own AI tools could foster a more personal and reliable form of trust and utility, independent of big tech. The Challenge of Relevancy in Rapid Change: The breathtaking pace of technological advancement, especially in AI, makes it incredibly difficult for individuals to stay informed and for companies to remain relevant. This dynamic often leads to a concentration of attention on a few dominant platforms, like ChatGPT, even as innovative alternatives struggle for visibility.…
Welcome to Stewart Squared podcast with the two Stewart Alsops. In this episode, they track the transformation of business from the IBM-dominated 1980s to today's AI-driven landscape, exploring how personal computing, the rise of the internet, and eventually search and social media changed the way companies operate. The conversation moves from early account control tactics to the disruptive power of Google Search and the monetization model sparked by Bill Gross, all the way to current questions around AI's role in search, advertising, and persuasion. Along the way, they unpack shifting cultural attitudes toward NDAs, the evolution of email protocols, and the structural consequences of tech monopolies under regulatory scrutiny. The episode features reflections on digital infrastructure, geopolitical standardization, and how a changing information ecosystem could impact future business models. Check out this GPT we trained on the conversation Timestamps 00:00 The Tech Landscape of the 80s: IBM's dominance, minicomputers, and the dawn of PCs. 04:10 The Rise of the Internet: How the internet began to dissolve the lines between the tech industry and the broader economy, leading to the second convergence. 09:56 Business in the Pre-Internet Era: Relying on telephones, faxes, and crucial personal connections. 16:00 The Email Revolution: How adopting new technologies like email, despite early proprietary systems, became a competitive necessity. 19:45 Standardization and US Hegemony: The US role in setting global tech standards, like email protocols, during its period of global influence in the 90s. 23:32 The Dollar as Reserve Currency: Discussing its resilience, the historical context, and the current lack of viable global alternatives. 28:20 Evolution of SEO: Tracing search engine optimization from buying search terms with Google to demographic targeting on social media. 31:50 AI's Impact on Search and Persuasion: How AI is poised to change information access and the concerning potential of AI-driven persuasion. 34:40 The End of Social Media?: My thoughts on why the era of social media's dominance might be waning. Key Insights Business Has Been Rewritten by Tech—More Than We Realize: The conversation highlights a major shift in how business has operated from the 1980s to today, emphasizing that early practices centered around monopolistic control, like IBM’s account control, have been replaced by tech-driven dynamism. The evolution of the personal computer and the internet didn’t just create new tools—they completely reshaped the rules of engagement across industries. Business norms are no longer just culturally or economically constructed but increasingly technologically defined. SEO Emerged From the Commercialization of Search: Search engine optimization wasn’t inevitable—it came from the discovery that search could be bought. Bill Gross’s innovation to monetize search by selling keywords laid the foundation for Google’s eventual advertising empire. What began as an informational utility became a battleground for visibility and commerce, fundamentally altering how companies think about presence, relevance, and value in the digital space. The Medium Really Did Change the Message—and the Messenger: From fax machines and FedEx to iPhones and digital maps, the medium of business communication has continually reshaped expectations and behaviors. One anecdote recounts how finding a restaurant in Hong Kong via an iPhone marked a turning point—not just in convenience, but in how information access alters our experience of place and decision-making. The mediums businesses use now define the kind of relationships and decisions they make. Social Media Killed SEO—Until AI Killed Social Media: There’s a compelling argument that while SEO once ruled digital visibility, its power was overtaken by social media’s targeted advertising. But now that social media itself is fragmenting—partly due to regulatory pressure, partly due to user disillusionment—AI is disrupting both. The episode touches on how tools like ChatGPT with memory are creating individualized knowledge and influence channels, raising questions about what optimization even means in an AI-mediated world. AI’s Persuasion Power Raises New Kinds of Risks: The discussion around AI agents and their potential to persuade humans touches on an underexplored frontier—how machines might be used not just to inform, but to influence. The shift from targeting groups (as in social media) to profiling individuals emotionally and perceptually introduces new cognitive security threats. What’s at stake isn’t just privacy but autonomy and belief formation. Trust, Not Contracts, Built the Old VC Model: An important moment in the conversation points out that in earlier eras, venture capitalists didn’t need NDAs. The business ran on trust and reputation—if a VC violated that trust, they’d be out. This points to a broader theme: the erosion of informal norms that governed the old economy and the slow build-up of bureaucratic safeguards to compensate for declining interpersonal trust. Standardization Was a Form of Soft Power: The global adoption of internet protocols and email conventions was shaped by U.S. dominance in the 90s, reflecting not just technological leadership but geopolitical influence. Standards became instruments of global alignment, akin to the U.S. dollar’s status as a reserve currency. This reveals how deeply intertwined technology, business, and power structures have become—and how changes in one domain ripple through the others.…
I, Stewart Alsop, was absolutely thrilled to have my dad, Stewart Alsop II, and our very special guest, Gilman Louie, on this episode of Crazy Wisdom. We journeyed through Gilman's incredible career, from pioneering video games in the 80s with severe hardware limitations and the whirlwind of the Pokemon card craze, to his instrumental work founding In-Q-Tel for the CIA and the eventual creation of Alsop Louie Partners. It was a fascinating look at decades of technological evolution, strategic thinking, and the stories behind some major innovations. Check out this GPT we trained on the conversation Timestamps 00:53 Gilman Louie on meeting Stewart Alsop II and the challenges of 1980s video game development, including 16K memory flight sims and early multiplayer. 08:28 From commercial flight simulators to military training: How Gilman's F-16 game, Falcon 3.0, evolved after an unexpected Air Force inquiry. 13:16 The Pokemon card craze: Gilman Louie details his involvement with Wizards of the Coast and the game's explosive, $200M+ US launch. 18:25 Gilman Louie recounts his transition from Hasbro to being recruited to establish and lead In-Q-Tel, the CIA's innovative venture capital arm. 20:42 The founding of Alsop Louie Partners: A timely call and a pivotal career shift for both Stewart Alsop II and Gilman Louie. 27:30 Gilman Louie explains In-Q-Tel's unique non-profit 501c3 structure, designed for independence and trust in bridging government needs with commercial tech. 34:58 Knowledge Management for Impact: Gilman Louie’s distinctive technique of visualizing future solutions as "movies in his head" to guide In-Q-Tel's investments. 41:34 Future of Defense: Gilman Louie discusses the strategic shift from large, "exquisite systems" towards "swarms of attritables," aiming for transformation by the late 2020s. 46:52 Envisioning "Unit of One" Economics: The future of personalized, on-demand, decentralized manufacturing that could reshape global supply chains. 56:20 The origin story of Alsop Louie Partners' "Geek and Gadfly" moniker and how this compelling narrative contributed to their fundraising success. Key Insights Pioneering Spirit in Early Tech: The 1980s were a crucible for innovation, with developers like Gilman Louie creating complex experiences like flight simulators on severely constrained hardware (e.g., 16KB of RAM). This era demanded immense creativity and resourcefulness, laying the groundwork for future technological leaps. From Games to Government: Commercial entertainment, particularly Gilman's flight simulators, found unexpected and critical applications in military training. This highlights how innovations in one sector can organically diffuse and be adapted for entirely different, high-stakes purposes, influencing even national defense. The Power of Narrative in Venture: The "Geek and Gadfly" story crafted by Gilman Louie and Stewart Alsop II for Alsop Louie Partners significantly aided their fundraising. A clear, authentic, and memorable narrative that encapsulates the founders' complementary strengths can be a powerful tool in gaining investor confidence. In-Q-Tel's Groundbreaking Model: In-Q-Tel was established as a non-profit entity to provide the CIA with access to cutting-edge commercial technology. This novel structure, intentionally kept separate from direct government control, fostered agility, trust, and an effective way to scout and invest in innovations relevant to national security. Visualizing the Future to Solve Problems: Gilman Louie's method of "scripting movies in his head" is a unique approach to knowledge management and complex problem-solving. By envisioning a desired future state and identifying the missing technological pieces, he can effectively direct investment and strategy. The Evolution of Defense Strategy: Future military capabilities are shifting away from large, expensive "exquisite systems" towards more numerous, adaptable, and potentially attritable assets like drone swarms. This paradigm shift aims for a more resilient and flexible defense posture, with significant changes anticipated by the late 2020s. The Promise of "Unit of One" Manufacturing: The concept of "unit of one" economics, where products are manufactured cost-effectively and personalized on demand, represents a major future trend. Driven by AI, advanced robotics, and localized production, this could revolutionize consumption, reduce waste, and make highly customized goods accessible. Serendipity and Seizing Opportunity: Key turning points in Gilman's career, such as the Pokemon license acquisition or the founding of Alsop Louie Partners, involved elements of serendipity and being prepared to act on unforeseen opportunities. This underscores the importance of adaptability and recognizing pivotal moments. Contact Information * Alsop Louie Partners…
Welcome to Stewart Squared podcast with the two Stewart Alsops. In this episode, the conversation ranges across the years that saw Apple shift from a struggling personal computer company to the launch of the iPhone, marking a deeper convergence of mobile technology and cloud infrastructure. The Stewarts explore how the so-called "Web 2.0" years—deceptively quiet between the dot-com crash and the smartphone boom—were in fact the foundation for the modern Internet, with fiber laid during the crash powering today's broadband-dependent innovations. From Apple's cautious approach to third-party apps to the implications of subscription economics born partly out of mobile gaming and cloud SaaS, the discussion weaves technical detail with personal anecdotes—like a missed investment opportunity in Elon Musk's x.com, or the early struggles and eventual transformation of Justin.tv into Twitch. For listeners curious about Apple's trajectory post-Steve Jobs, Stewart Alsop II references a relevant article, “Dear Tim Cook, Maybe You Should Consider Retiring”. Check out this GPT we trained on the conversation! Timestamps 00:00 Apple’s transition from personal computers to the iPhone, Web 2.0’s rise, and early broadband limitations. 05:00 The iPhone as a pocket computer, initial app limitations, and the creation of the App Store pushed by Scott Forstall. 10:00 Investing dynamics of the early 2000s, the dot-com crash aftermath, and a missed opportunity with Elon Musk’s x.com. 15:00 AI comparisons to past tech waves, cloud computing’s economics, and the rise of the subscription model. 20:00 Claude as a developer’s tool, DIY infrastructure, and the economics of replacing SaaS like Descript. 25:00 The emergence of the cloud via AWS, SaaS adoption, and enterprise migration toward 40% cloud usage. 30:00 Infrastructure’s silent buildup during the bust years, fiber-optic backbones, and Tim O'Reilly’s Web 2.0 framing. 35:00 Investment in Justin.tv, the origin of Twitch, and early challenges in monetizing live streaming. 40:00 Legal issues with content rights, programming for dollars, and the pivot to gaming as Twitch. 45:00 Differentiating investor influence vs. founder-driven execution, social media’s emergence, and missed deals like Twitter. 50:00 Regrets around early venture decisions, rationality vs. intuition, and the limits of journalistic thinking in VC. 55:00 Reflections on truth, timing, and the impact of historical perspective in investment thinking. Key Insights The iPhone was not just a product—it was a platform shift. Initially perceived as a compact personal computer, the iPhone’s release in 2007 marked a pivotal transition in computing. Its eventual reliance on connectivity, cloud infrastructure, and a curated App Store created an entirely new ecosystem that transcended Apple’s roots in standalone devices. This revealed that the smartphone's power lay not just in hardware but in its entanglement with the growing capabilities of cloud computing. Web 2.0 emerged from an in-between era where ‘nothing’ and ‘everything’ happened. Between the collapse of the dot-com bubble and the arrival of smartphones, the early 2000s seemed quiet on the surface but were actually fertile with infrastructure development. Fiber was laid, foundational software tools evolved, and key internet services like Google began forming. This paradox—an uneventful time that seeded today’s tech landscape—challenges how we measure technological progress. Apple’s walled garden approach to apps reflected a deep-seated tension. While the introduction of the App Store was a game-changer, it clashed with Apple’s control-oriented DNA. Stewart Alsop II observed that despite apps fueling the iPhone’s success, Apple maintained a wary stance toward third-party developers. This tension continues to shape how innovation on the platform is regulated and monetized. Cloud infrastructure reshaped the economic model of software. SaaS and cloud computing, catalyzed by AWS and others, introduced a shift from transactional to subscription-based revenue. The conversation draws a line from magazine subscriptions to software licensing and the rise of mobile app monetization, revealing how financial predictability became central to Internet business models. Missed opportunities often stem from rational overthinking. The anecdote about passing on Elon Musk’s x.com underscores a broader pattern: being “right” doesn’t always lead to good investment outcomes. The rational investor might miss out on transformational bets simply because the risk doesn’t fit the prevailing model—a cautionary tale about the limits of logic in venture capital. Twitch’s success grew from improvisation, not strategy. The journey from Justin.tv to Twitch is a testament to flexibility. Originally a quirky lifecasting experiment, the founders adapted to platform and market realities by focusing on video game streaming. The move wasn’t obvious or universally supported, but it reflected an intuitive grasp of emerging digital behavior—something investors initially overlooked. The shift to real-time infrastructure reshaped identity and interaction. As the conversation touches on Anthropic, Claude, and the “Evernet,” a vision surfaces: one where real-time connectivity isn’t just technical but experiential. From managing servers to engaging with AI that directs our actions, humans are increasingly enmeshed in systems that blur autonomy, guidance, and even the boundary between tool and user.…
Welcome to Stewart Squared podcast with the two Stewart Alsops. Today’s episode moves beyond technology to explore a deeply personal and historical reflection on the Great Society under Lyndon B. Johnson, sparked by a late-night email about the political and cultural shifts of the 1960s. The conversation weaves together vivid childhood memories of JFK’s inauguration and assassination, the dramatic handover of power to LBJ, the sweeping legislative reforms aimed at poverty, civil rights, and education, and the tensions that would later erupt into widespread protest over Vietnam. Along the way, the Alsops draw connections between the centralized American power of the postwar boom and today’s fragmented media environment, touching on how shifting technology, political identity, and military spending continue to echo the seismic changes of that era. Check out this GPT we trained on the conversation! Timestamps 00:00 Talk opens on LBJ, the Great Society, and JFK’s assassination memories. 05:00 Vivid recollections of Kennedy’s inauguration, cultural optimism, and the 1950s American Dream. 10:00 National trauma of JFK's death, the Cold War backdrop, and America's supreme global position. 15:00 LBJ's rise to power, early Vietnam involvement, and the cultural tensions brewing under his presidency. 20:00 Johnson’s domestic legacy: Civil Rights Act, Medicare, Medicaid, Voting Rights Act, immigration reform. 25:00 Great Society programs' immediate impact, growing conservative backlash, and Nixon's political positioning. 30:00 Broader reflections on global superpower dynamics, information warfare, and Cold War paranoia. 35:00 Evolution of American media, decentralized information systems, and the slow political response to social media. 40:00 Technological acceleration, military-industrial complex shifts, and AI’s role in modern defense. 45:00 Discussion on future warfare, proxy conflicts, and America's strategic military adaptations. 50:00 Deep dive into economic power projection, aircraft carriers, and global military dominance. 55:00 Closing thoughts on the psychological impact of rapid change, American identity, and technological overwhelm. Key Insights The assassination of John F. Kennedy marked a psychological turning point for America. The hosts reflect on how the shock of JFK’s death in 1963 shattered a national sense of invulnerability. It challenged the mid-century belief in American supremacy and security, exposing a deep fragility within the country's identity at a time when the economy was booming and postwar optimism was high. Lyndon B. Johnson’s Great Society reshaped American domestic life at a rapid and unprecedented pace. LBJ seized the moment after JFK’s death to push through a sweeping agenda between 1963 and 1968, including the War on Poverty, civil rights legislation, Medicare, Medicaid, and education reform. This short but intense period of activism permanently expanded the federal government's role in citizens' lives. The Vietnam War fueled a generational and political crisis that unraveled the Great Society’s unity. Although Johnson’s domestic programs had strong bipartisan support initially, the escalation of the Vietnam War under his leadership triggered massive protests, especially among students, and ultimately eroded the social consensus that had supported his ambitious reforms. The shift from old-party politics to decentralized political movements weakened institutional power. The conversation points to how LBJ, a master of the traditional, party-driven political system, struggled to maintain control as primaries, media influence, and grassroots activism began to displace the backroom negotiations of the smoke-filled rooms that once governed American politics. Technological change, particularly in media, accelerated the fragmentation of American public life. Television played a pivotal role starting with JFK’s election, but by the 21st century, the rise of social media, decentralized news, and digital communication had fundamentally changed how Americans form opinions and organize politically, contributing to growing national divisions. Defense spending reveals a tension between legacy military systems and emerging technologies. The hosts discuss how traditional defense contractors continue to dominate budgets with massive investments in aircraft carriers and nuclear submarines, even as a new class of technology-driven defense companies pushes to modernize military capabilities through AI, software, and next-generation systems. America’s role as a global superpower remains strong but increasingly questioned both abroad and at home. Although the U.S. still fields unmatched military and economic might, the episode reflects on how the end of the Cold War, rising foreign resentment, and domestic polarization have left the country grappling with its identity and purpose, much like it did during the upheavals of the 1960s.…
Welcome to Stewart Squared podcast with the two Stewart Alsops. In this wide-ranging conversation, they’re joined by legendary entrepreneur and Idealab founder Bill Gross to trace the arcs of personal computing, the early Internet, and today's AI boom. The episode explores Bill’s early work with products like Lotus Magellan and GoTo.com, reflects on how foundational technologies transformed from niche curiosities into global forces, and questions what comes next in an era of large language models and cognitive prosthetics. Along the way, they revisit pivotal moments from the GUI wars to the Netscape IPO, unpack the birth of paid search advertising, and examine the shift from coding as craft to prompting as interface. For more on Bill’s latest ventures, check out Gist AI and Pro-rata Ads as mentioned in the show notes. Check out this GPT we trained on the conversation! Timestamps 00:00 – Bill Gross is introduced and recalls early software like Lotus Magellan , a hard drive search tool from the 1980s. They discuss its roots in natural language processing and early email indexing . 05:00 – The conversation shifts to GUI wars , Microsoft's DOS strategy , and the rise of Windows over IBM's OS/2. They explore how Excel and Word were part of Microsoft’s application takeover. 10:00 – Discussion of LLMs as productivity tools , comparing their impact to the GUI revolution. They analyze Microsoft’s AI approach and focus on enterprise applications over foundational model improvements. 15:00 – Bill reflects on the pace of change , from weekly PC magazines to hourly AI news. They compare today's AI boom to the dot-com era and the Netscape IPO as a turning point. 20:00 – The birth of GoTo.com , keyword bidding, and the audience backlash at TED. Google’s later adoption of the model is explored as a pivotal monetization moment. 25:00 – Introduction of Pro-rata Ads , which use LLMs for real-time ad relevance . They explore if LLMs are reasoning or just statistically advanced. 30:00 – Reflections on social media emergence , exocortex , and unintended consequences of scale like engagement algorithms driving hate. 35:00 – Gross shares the transition from CD-ROMs to the web browser , leading to Idealab’s founding and early Internet business models . 40:00 – They discuss search before search , the evolution of web discovery , and the promise of LLM-powered knowledge assistants . 45:00 – The future of programming with English , AI whispering , and how prompting is becoming the new interface layer. 50:00 – Final reflections on Idealab's journey , Apple’s AI struggles , and how power dynamics between companies and governments are shifting. Key Insights The Roots of AI Trace Back to Early Search and Natural Language Interfaces: Bill Gross’s early work with Lotus Magellan and a product called HAL (Human Access Language) illustrates how long-standing the desire has been to make machines understand and summarize human input. These early attempts at indexing and parsing natural language on primitive hardware laid the groundwork—conceptually, if not technically—for the large language models we use today. The idea of summarizing content and enabling more intuitive access to information was there decades ago, even if the technology had to catch up. AI as a Business Platform, Not Just a Technical Breakthrough: A recurring theme in the conversation is that the real value in AI—much like the operating systems of old—is in the applications built on top of the foundational models. Bill highlights Satya Nadella’s focus on productivity gains over raw model improvements, emphasizing a strategic pivot from building core tech to crafting useful, business-oriented tools. This parallels earlier shifts in the computing industry, such as the move from DOS to Windows and from command lines to GUIs, where the underlying tech became commoditized and the upper layers captured most of the value. The Origins of Paid Search Were Controversial but Revolutionary: GoTo.com, founded by Gross in 1998, pioneered the idea of bidding on search keywords—a move initially met with hostility from purists who saw search as a public good. Despite the backlash, the model proved transformative, leading to Google’s eventual adoption (and acquisition of the patents) and becoming the backbone of the modern internet economy. It’s a reminder that the most disruptive ideas often start out unpopular, especially when they threaten cherished ideals. Pace of Innovation Is Accelerating Beyond Human Comprehension: The hosts and guest reflect on how the tempo of technological change has shifted from biweekly magazine cycles in the 1980s to real-time developments today, where even stepping away for breakfast might mean missing a major release. Gross notes that a billion dollars a day is being poured into AI, suggesting not only a financial feeding frenzy but also a global race that's orders of magnitude faster and more intense than the dot-com era. Exocortex and the Rise of Digital Cognition: There’s an ongoing philosophical reflection about computers and now LLMs as extensions of human cognition. The term “exocortex” is used to describe this, hinting at a future where machines are not just tools but integral parts of how we think, remember, and make decisions. Social media and LLMs are both seen as forms of this augmentation, with the former demonstrating how unintended consequences can arise when such systems scale globally. Open Source and Abstraction Have Rewired Software Development: The episode touches on how open source software and the rising abstraction layers in programming—from machine code to AI-generated scripts—have democratized the ability to build software. Gross shares his dream of English as a programming language, which is now functionally real through LLMs. This shift doesn’t eliminate coding but expands who can participate in creating software, reframing coding as prompting and design rather than syntax mastery. Power is Shifting From Governments to Tech Companies: In discussing companies like Apple and Google—whose platforms now hold the entirety of users’ personal data—the episode explores how these entities have outgrown traditional government oversight. With market caps exceeding many national GDPs and influence over global communication, there’s a growing tension between private innovation and public governance. Gross points out that while users willingly give up their data for value, there’s limited recourse when these platforms overreach, raising important questions about accountability in the age of AI.…
Welcome to Stewart Squared podcast with the two Stewart Alsops. In this episode, the conversation starts with a personal quest into vector databases and linked data, but opens into a sweeping narrative of how the Internet—built on protocols like TCP/IP and scaffolding like URIs—evolved from Cold War military infrastructure into the backbone of our digital civilization. The Stewarts revisit the intellectual origins of URIs, Tim Berners-Lee’s vision for linked knowledge, and how software layered atop protocol transformed hardware into platforms. They also take a sharp detour into the geopolitics of digital control, discussing China’s Great Firewall and the linguistic imperialism embedded in early Internet standards. From UNIX to Apple’s cultural stagnation, the episode reflects on what it means for a company—or a civilization—to lose touch with the protocols it was built on. Check out this GPT we trained on the conversation! Timestamps 00:00 — The episode opens with Stewart III reflecting on linked data and URIs as the backbone of the Internet, describing them as infrastructure for modern civilization. Stewart II begins to explain the origins of the Internet as a DARPA project, designed to survive catastrophic disruption. 05:00 — They explore how Internet protocols like TCP/IP enabled university networks to connect and how these early layers evolved. The conversation touches on the difference between URIs and URLs and how complexity builds from simple foundational standards. 10:00 — The focus shifts to China’s Great Firewall and its early recognition of the Internet’s disruptive power. They discuss how the dominance of English in technical standards shaped global access and control, highlighting China’s early moves to manage digital infrastructure. 15:00 — Stewart II explains how MAC addresses and Ethernet protocols help avoid data collisions, reinforcing the role of identifiers in enabling a functioning network. Bob Metcalfe’s invention of Ethernet is referenced as part of the foundational stack. 20:00 — They compare the abstract nature of the Internet to past industrial revolutions, noting how its invisibility makes it harder to understand. Systems like electricity and air traffic control are used as analogies for how critical infrastructure can be both essential and obscure. 25:00 — A detour into gaming history and Apple’s hardware limitations in the 90s leads to the significance of Steve Jobs acquiring NeXT. This move laid the groundwork for Apple’s modern operating system and its ability to switch between chip architectures. 30:00 — The role of UNIX is unpacked as a universal operating system developed at Bell Labs, enabling software to run across different machines. This transitions into a reflection on the birth of the independent software industry and early players like Broderbund. 35:00 — The conversation returns to Apple, critiquing Tim Cook’s leadership and the company’s failure to grasp AI's significance. They contrast Steve Jobs’ integrated vision with Apple’s current stagnation around Siri and “Apple Intelligence.” 40:00 — Other tech giants are evaluated: Microsoft is praised for adapting quickly through OpenAI partnerships, while Amazon and Google are still experimenting. The real challenge, they argue, is not deploying AI but understanding its implications. 45:00 — LLMs are described as cognitive infrastructure rather than just software, possibly marking a new technological revolution. They reference Carlota Perez’s framework to explore whether we’re entering a new deployment phase of a broader cognitive shift. 50:00 — The final stretch touches on physical Internet infrastructure—fiber optics and undersea cables—and geopolitical threats to them. The episode closes with concerns about Apple's insular culture and the idea that true change—organizational or societal—only happens after deep disruption. Key Insights The Internet as Civilizational Infrastructure: The episode frames the Internet not merely as a communication tool, but as a foundational layer of modern civilization—comparable to libraries or the railroad. At its core are URIs (Uniform Resource Identifiers), which structure the way digital knowledge is located and shared. Stewart III’s struggle to understand this system through his own data projects leads into a larger reflection on how protocols quietly govern our relationship to information, revealing that what feels abstract—like a URL—is actually deeply infrastructural. Protocols as the DNA of the Internet: The Internet emerged from Cold War logic, specifically DARPA’s aim to create a distributed network resilient to nuclear attack. This led to the creation of shared protocols like TCP/IP, which enabled universities to interconnect. The conversation emphasizes that these protocols are not just technical trivia—they are agreements that allow machines (and by extension, humans) to understand each other, layer by layer. Without this shared language, there is no Internet. The Political Weight of Language in Technology: One subtle but critical insight is how English, as the default language of Internet protocols and identifiers, embeds geopolitical power into the Internet's foundations. China’s adaptation of these standards required fluency in both English and Western tech culture, raising the question: can any nation truly “sovereignly” participate in a system it didn’t design? This sets the stage for China’s Great Firewall, a state-level intervention to shape digital flow and protect political narratives. China’s Great Firewall as a Technical and Cultural Response: The episode revisits the origins of the Great Firewall (Golden Shield Project), suggesting it was not merely about censorship, but also about technical sovereignty. China began building this system as early as 1998, well before the commercial Internet took off domestically. Stewart II’s personal anecdotes about early Chinese state-sponsored tech conferences reveal how seriously the government was considering the societal implications of computing infrastructure—and how early they moved to manage it. UNIX as the Bridge Between Hardware and Software Worlds: The history of UNIX becomes a throughline to understand how software began detaching from hardware constraints. Developed at Bell Labs, UNIX was designed to be hardware-agnostic, allowing it to run across different machines—a revolutionary shift. This insight connects directly to Apple’s eventual transformation, as Steve Jobs’ decision to bring NeXT’s UNIX-based OS into Apple enabled it to transition across chipsets, from Motorola to Intel to ARM. Apple’s Cultural Rigidity and AI Blindspot: A major critique is leveled at Apple’s current leadership, especially Tim Cook, for failing to grasp the cultural and technical dimensions of artificial intelligence. Stewart II compares Apple’s closed culture to the CIA or CCP, arguing that without openness to external ideas, the company risks becoming irrelevant in the AI era. The decision to announce “Apple Intelligence” before having a product ready breaks with Jobs-era principles and is seen as a symptom of deeper strategic confusion. LLMs as a New Technological Paradigm, Not Just Software: The most future-facing insight is the idea that large language models (LLMs) represent a break from traditional software—they are more like cognitive prosthetics than applications. Stewart III positions LLMs as utilities, akin to electricity or the Internet itself, suggesting we are entering a post-software phase of the information age. This introduces...…
Welcome to Stewart Squared podcast with the two Stewart Alsops. In this episode, the conversation weaves through the evolution of media, venture capital’s long shadow over technology, and how editorial instincts have (or haven’t) adapted to the pace of software. Stewart Alsop II brings firsthand insight into the early days of digital publishing and the structural mismatches that still shape newsrooms and tech companies alike. Topics range from John Doerr’s influence on startup thinking to the archival black holes created by neglected knowledge systems. Check out this GPT we trained on the conversation! Timestamps 00:00 - Opening riff on the confusion between Stewart Alsop Sr., Jr., and III; transition into how legacy media handles its own memory poorly, with a few anecdotes about lost archives and disappearing links. 05:00 - Discussion around venture capital’s influence on media and tech—John Doerr’s role in shaping the “scale or die” mindset, and how that clashed with journalistic values. 10:00 - Breakdown of editorial vs. engineering tension—why newsrooms and product teams often talk past each other, and what gets lost in that misalignment. 15:00 - Stories from early digital publishing: CMS nightmares, how print workflows were just ported online without rethinking them, and the inertia that followed. 20:00 - Exploration of archival decay—missing metadata, broken URLs, and the business implications of failing to preserve intellectual assets. Some sharp takes on institutional amnesia. 25:00 - Pivots to AI and vector databases—what they might enable for content rediscovery, and the risks of relying on tech without editorial intent or context. 30:00 - Richer dive into organizational knowledge and ownership—who controls information, how roles are shifting, and why institutional memory needs its own champion. 35:00 - Personal experiences with failed knowledge systems—both in media and tech startups. Reflection on how internal culture shapes what gets remembered. 40:00 - Pushback on “move fast and break things”—how speed has damaged continuity in publishing, and the cost of constantly reinventing without reflection. 45:00 - Final threads on building more durable systems: not just technology, but incentives, rituals, and cross-functional collaboration to prevent forgetting by design. Let me know if you want a more granular breakdown or direct pull-quotes from any specific section. Key Insights Media organizations often suffer from institutional amnesia. One recurring theme is how publishing companies, especially legacy ones, lose track of their own intellectual assets—past reporting, editorial strategies, or even technological decisions—because they lack durable knowledge systems. This isn’t just a storage issue; it’s a strategic failure that hampers innovation and continuity. Venture capital has reshaped the expectations of both media and tech. Alsop II emphasizes how figures like John Doerr didn’t just fund companies—they pushed a worldview where scale, speed, and disruption became non-negotiable. That logic infiltrated newsrooms too, especially when tech-driven platforms began to dictate the pace and form of publishing. Editorial and engineering cultures have long been misaligned. This tension plays out in product development cycles, CMS design, and decision-making about what constitutes “valuable” content. While journalists prioritize nuance and context, engineers often optimize for efficiency and metrics. Without meaningful bridges, both sides end up frustrated—and organizational progress stalls. Digital publishing inherited many of print’s blind spots. The episode explores how early online media failed to rethink fundamental workflows. Rather than redesigning around the capabilities of the web, many companies simply transferred print-era thinking into a browser. That inertia led to clunky archives, rigid hierarchies, and missed opportunities for interactivity or reader engagement. Archival neglect is a systemic risk, not just a technical oversight. The guest shares examples of entire swaths of reporting being lost due to poor metadata, broken links, or obsolete formats. These failures reflect a deeper undervaluing of historical continuity—when organizations treat content as ephemeral, they erase not just stories but lessons learned. AI and vector databases could offer a partial corrective—but only if used intentionally. There’s a sense that the new wave of tools might help media companies rediscover and recontextualize their archives. But without clear editorial frameworks, even the most advanced systems risk amplifying existing biases or simply surfacing the loudest content. There’s a growing need to rethink who “owns” knowledge in a media org. As roles shift—product managers gaining influence, data scientists becoming gatekeepers—editorial authority is increasingly fragmented. This episode makes the case for more integrated, cross-functional stewardship of institutional knowledge, where content, context, and infrastructure aren’t siloed off from one another.…
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