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.

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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

1. 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.
2. 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.
3. 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.
4. 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.
5. 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.
6. 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.
7. 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.
8. 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.

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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

1. 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.
2. 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.
3. 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.
4. 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.
5. 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.
6. 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.
7. 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.

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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”.

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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

1. 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.
2. 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.
3. 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.
4. 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.
5. 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.
6. 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.
7. 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.

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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

1. 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.
2. 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.
3. 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.
4. 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.
5. 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.
6. 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.
7. 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.

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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

1. 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.
2. 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.
3. 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.
4. 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.
5. 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.
6. 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.
7. 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.

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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

1. 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.
2. 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.
3. 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.
4. 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.
5. 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.
6. 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.
7. 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.

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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

1. 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.
2. 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.
3. 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.
4. 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.
5. 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.
6. 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.
7. 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.

Welcome to Stewart Squared podcast with the two Stewart Alsops. In this episode, they unpack the rise of Satya Nadella and how his leadership reshaped Microsoft’s culture, capital strategy, and role in the AI boom. The conversation traces the company’s shift from a Windows-obsessed, top-down org to a more open, developer-friendly platform player—how Nadella’s quiet power differs from the bombast of past tech CEOs, and why cloud infrastructure has become the real arena for dominance. Along the way, there’s sharp reflection on the limits of the open-source ethos, the nature of modern boardroom influence, and how AI is changing what it means to build “a tech company.”

Check out this GPT we trained on the conversation!

Timestamps

00:00 – Introduction The Stewarts set the stage for the episode, introducing the main themes and providing context for the discussion.

05:00 – Satya Nadella's Leadership Style Exploration of Satya Nadella's approach to leadership and how it contrasts with previous Microsoft CEOs.

10:00 – Cultural Transformation at Microsoft Discussion on the cultural shifts within Microsoft under Nadella's leadership, focusing on openness and collaboration.

15:00 – Microsoft's Strategic Investments Analysis of Microsoft's investments in areas like cloud computing and artificial intelligence, and how these align with the company's long-term vision.

20:00 – Open Source vs. Proprietary Models Debate on Microsoft's stance towards open-source software versus proprietary models, and the implications for the tech industry.

25:00 – The Role of AI in Microsoft's Future Insights into how artificial intelligence is shaping Microsoft's product offerings and strategic direction.

30:00 – Capital Expenditures and Infrastructure Examination of Microsoft's capital expenditure strategies, particularly in building infrastructure to support cloud services and AI.

35:00 – Shifts in CEO Power Dynamics Discussion on how the role and influence of CEOs in the tech industry have evolved, with a focus on Nadella's tenure.

40:00 – Boardroom Dynamics and Decision Making Insights into the interactions between Microsoft's leadership and its board, and how decisions are made at the highest levels.

45:00 – Microsoft's Position in the Tech Ecosystem Analysis of Microsoft's current standing in the broader tech landscape and its relationships with competitors and partners.

50:00 – Future Outlook and Closing Thoughts The Stewarts share their perspectives on where Microsoft is headed and summarize key takeaways from the discussion.

Key Insights

1. Satya Nadella’s leadership marked a cultural reset at Microsoft: The episode underscores how Nadella’s quiet, empathetic style replaced the old guard’s combative, Windows-first mentality. He reframed the company’s mission around cloud services and developer friendliness, signaling a departure from Ballmer-era arrogance. This wasn’t just PR—it shifted internal incentives, breaking down silos and reorienting the company toward learning and collaboration.
2. Microsoft’s capital expenditure strategy is central to its AI and cloud dominance: A major throughline is how much Microsoft is willing to spend to stay ahead. The Stewarts highlight that CapEx isn’t just about server farms—it's a reflection of commitment to long-term infrastructure, especially in the AI arms race. Unlike smaller players or startups, Microsoft can afford to bet billions on future capacity, giving it structural advantages in scalability and resilience.
3. The company’s embrace of open source was pragmatic, not ideological: Nadella didn’t turn Microsoft into an open-source evangelist out of belief—he did it because it made strategic sense. The podcast draws attention to how the move to support Linux and acquire GitHub signaled to developers that Microsoft was no longer hostile. But this wasn’t a moral shift; it was about relevance and platform gravity in a world where developers had the power.
4. Azure, not Windows, became the new center of gravity: One of the episode’s key insights is how Azure, Microsoft’s cloud platform, quietly became the company’s core business. The transition from being a consumer-facing software company to an infrastructure provider happened gradually but decisively. This move changed who Microsoft’s real customers were—from end users to enterprises and developers—and that changed everything about how the company operated.
5. AI is amplifying the importance of infrastructure, not replacing it: While many are captivated by flashy AI tools and chatbots, the Stewarts point out that the real value lies in the systems underneath. Microsoft’s partnership with OpenAI is important, but even more critical is the company's ability to host, distribute, and monetize those models at scale. AI isn't removing the need for infrastructure—it's making it more central than ever.
6. Boardroom dynamics and CEO power are shifting: The conversation touches on how the modern CEO, especially in big tech, operates more like a statesman than an operator. Nadella’s influence stems from narrative control, capital allocation, and trust, not from barking orders. It reflects a broader shift in corporate governance, where trust from the board and market means more than charisma or micromanagement.
7. Microsoft’s transformation reflects a broader arc in tech history: The episode situates Microsoft’s evolution within a longer timeline—from the PC era’s software dominance to the internet’s platform wars, and now the AI-infrastructure age. Nadella’s Microsoft isn’t just a turnaround story—it’s a case study in how companies survive by shedding their original identity without losing their core ambition.

Welcome to Stewart Squared podcast with the two Stewart Alsops. In this episode, the conversation winds through a rich mix of personal history, editorial philosophy, and the evolution of tech—from getting fired (twice) to putting Steve Jobs on the cover of Inc. in 1981, from the impact of VisiCalc on Apple II adoption to the deeper meaning of what it means to be an editor. Alongside reflections on the newsletter era, the internet boom, and the looming AI shift, there’s a core thread about editing as a form of pattern recognition and meaning-making.

Check out this GPT we trained on the conversation!

Timestamps

00:00 Welcome to the Stewart Squared Podcast

00:21 Writing a Book with AI

00:57 First Time Getting Fired

02:12 Conflict at Bank Magazine

04:43 Steve Jobs and the Apple II

10:40 Transition to Boston Computer Society

15:06 Starting a Newsletter

19:06 The Role of an Editor

25:20 Discovering Personal Computers

27:25 The Early Days of Apple II

28:11 The Magic of Spreadsheets

29:20 AI and Business: A Modern Parallel

31:42 The Rise and Fall of Tech Giants

34:56 The Dot-Com Boom and Bust

43:16 The Evolution of Online Banking

48:06 The Future of AI and Technology

52:12 Conclusion and Upcoming Topics

Key Insights

1. Getting fired can be formative, not just traumatic: The episode opens with a reflection on the first time Stewart Alsop was fired, tracing how a power struggle with an inexperienced editor-in-chief led to his dismissal from Inc. Magazine. Rather than framing it solely as a failure, he acknowledges how it pushed him toward more independent paths, including editing a user group magazine for free and eventually launching his own influential newsletter. The act of being fired becomes a recurring milestone that reorients his career.
2. Editing is about structure, clarity, and coherence at multiple levels: Stewart distinguishes between different kinds of editing—line editing, copy editing, and the editorial vision that shapes an entire publication. He credits a mentor at Marine Business magazine for teaching him foundational principles: every article needs a premise, development, and conclusion. These ideas anchor the episode’s broader conversation about what editing means, especially as they consider how to transform podcast transcripts into a book.
3. VisiCalc transformed the personal computer from hobbyist gadget to business tool: The story of how business people began taking personal computing seriously centers on the spreadsheet. VisiCalc, running on the Apple II, created a breakthrough moment because it solved a real problem for professionals. Stewart recalls buying an Apple II, struggling to set it up, and then being captivated by the power and immediacy of the software—a turning point not just for him but for the industry.
4. Newsletters became a medium for synthesis and pattern recognition: After his second firing, this time from InfoWorld, Stewart decided he was done working for others. Inspired by Ben Rosen and later Esther Dyson, he launched his own newsletter to track trends in tech. This format allowed him to highlight weak signals, identify inflection points, and say things others weren’t yet seeing. Pattern recognition became not only a skill but a way of establishing voice and authority.
5. Much of the AI hype echoes the dot-com boom, but with faster cycles: Drawing on past experience, Stewart compares today’s AI investment frenzy to the speculative fervor of the late '90s internet bubble. He notes how large sums of money are pouring into companies, many of which may not survive. The key difference, perhaps, is the acceleration—developments like DeepSeek’s low-cost LLM could rapidly undercut many players, triggering what he calls an “AI apocalypse.”
6. Protocols, not platforms, may be the real legacy of AI and internet revolutions: Stewart emphasizes how lasting impact often lies not in individual companies but in underlying infrastructure. The protocols established during the internet’s early years—HTTP, domains, security layers—continue to define it. Similarly, he predicts AI will leave behind layers like markdown, JSON, and new personal-device-level architectures that quietly shape future interaction, regardless of which companies survive.
7. The editor’s job is to see things before others do and say them clearly: Whether in print, newsletters, or now AI-facilitated writing, Stewart frames editing as the disciplined practice of saying what others are only beginning to sense. His credibility was built not on data alone but on intuition grounded in experience, allowing him to make bold claims that time later affirmed. Editing, then, becomes both a craft and a mode of perception—shaping not just texts but how trends are named and understood.