Stewart Squared

About Stewart Squared

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

Publisher

Stewart Alsop II, Stewart Alsop III

Category

business · technology

Language

en

Explicit

No

First episode

13 Jul 2024

Latest episode

5 Nov 2026

Latest episodes

114 episodes in the feed.

1. 

   5 Nov 2026

   Episode #114: Moonwalks Cost Extra: Adventures with a $3000 Chinese Robot Dog

   In this episode, host Stewart Alsop welcomes back his father, Stewart Alsop II for another wide-ranging conversation that touches on everything from robotic dog demonstrations in Buenos Aires to the intricacies of Anthropic's IPO filing. The two dive into Anthropic CEO Dario Amodei's disciplined strategic approach, dissecting the company's unusual corporate governance structure featuring five stock classes and a public benefit oversight board. They explore how Anthropic has maintained profitability while renting data center capacity rather than building their own infrastructure, contrasting this with OpenAI's more scattered approach. The discussion weaves through comparisons of iconic tech founders, the nature of strategic partnerships versus customer relationships, and culminates in examining Elon Musk's risky bets across Tesla and SpaceX, including his pivot toward humanoid robots and satellite-based data centers. Key Insights Here are 7 key insights from this episode: 1. Anthropic demonstrates exceptional strategic discipline compared to its competitors, particularly OpenAI. The company has focused on enterprise customers from the start rather than consumer chatbots, evident in their customer base where they have numerous clients spending over a million dollars annually and many more at six-figure levels. Unlike OpenAI which built its own data centers, Anthropic leases capacity from others, including a notable arrangement with SpaceX AI for 13 billion dollars per quarter. This disciplined approach has allowed them to reach near break-even on an operating basis by the second quarter, proving their business model works without burning excessive capital. 2. The episode establishes that Dario Amodei possesses the rare quality of strategic vision that marks generational CEOs. Strategy differs from tactics in that it concerns what happens five or more years out, not just next quarter. The comparison is made to figures like Steve Jobs who could see the future, contrasted with Bill Gates who was brilliant tactically but failed to anticipate major shifts like the Internet and AI. Dario left OpenAI with a clear vision, built a team around it, and has remained remarkably consistent in executing that strategy over five years, suggesting he has this critical long-term thinking ability. 3. Anthropic has created an unprecedented governance structure featuring five classes of stock and a two-layer control system that has never been seen before in tech IPOs. There is a five-member long-term benefit trust structured as an LLC whose board members receive no equity, just 100,000 dollars annually, tasked with ensuring the company fulfills its public benefit mission around AI safety. Meanwhile, Dario and four other founders control 50.1 percent through special stock that trumps everything else. This complex structure reflects the unique challenge of governing a company trying to build superintelligence while ensuring it remains safe. 4. The robotics industry is experiencing a fundamental shift where software has no moat, which has major implications for both hardware makers and foundation model labs. Chinese company Unitree is leading in accessible robotics with products ranging from 3,000 dollar dog robots to 17,000 dollar advanced models and humanoid robots, all with open software. The discussion reveals that reactions to robots vary culturally, with Americans more fearful due to media like Black Mirror, while Argentines show greater curiosity. This suggests the robot adoption curve may vary significantly by geography and cultural factors. 5. The competitive landscape in AI is consolidating around a few key players with different approaches. Anthropic explicitly names only OpenAI and Google as competitors in their IPO documents, not naming Meta despite their significant AI work. The partnership structures matter enormously, with Anthropic partnering with Amazon, Google, Microsoft and Nvidia while avoiding building their own infrastructure. Meanwhile, SpaceX AI built massive data center capacity for Grok but found they did not need it all, allowing them to rent it to Anthropic and transform their revenue from 24 billion annually to potentially 40 billion plus with just this one arrangement. 6. The episode reveals that established tech companies are struggling with strategic transitions as the personal computing era ends. Microsoft failed to anticipate both Linux and mobile phones despite their Wintel partnership dominance. Current PC sales are described as apocalyptic except for Apple products. The Wintel partnership itself, while successful, was marked by conflict because both Microsoft and Intel wanted monopoly control in their domains, showing that even successful partnerships involve significant tension and compromise when companies must find common ground between different strategies. 7. There is an emerging theme that the most successful bets in tech involve believing in specific visionary founders rather than safe, diversified strategies. The example is given of someone investing 80 percent in Tesla and 20 percent in Apple using a buy, borrow, die strategy, which works specifically because of belief in Elon Musk's ability to execute risky bets like pivoting Tesla entirely to humanoid robots. Similarly, Google is beginning to put AI compute in space with TPUs on satellites, while Schmidt separately builds rockets through Relativity Space, showing how the new competitive landscape requires finding and backing founders with legitimate long-term vision in uncertain domains. Timestamps 00:00 Robot dog demo, and why Argentines are curious while Americans are afraid 03:27 Waymos in San Francisco and Unitree's $3,000 dog vs the $17,000 one 06:12 Chef Robotics: robots that pack food, and why robot software has no moat 10:07 The Anthropic IPO: building god or dying trying, and renting compute from SpaceX AI 14:19 Enterprise customers vs chatbot users, and Opus 5.5's new pricing 16:33 OpenAI went out to raise $30 billion and got $11 billion 18:02 The S-1, the five classes of stock and a board with no equity 20:39 Character analysis: who is Dario Amodei? 21:47 Strategy vs tactics: Atlassian, Jobs, Gates and Zuckerberg 27:32 Back to Dario: discipline, leased data centers, near breakeven 29:25 Governance: the long-term benefit trust and the 50.1% founder stock 35:15 Only two competitors named in the S-1: OpenAI and Google 36:23 Partners vs customers: who pays Anthropic 42:28 Wintel: a partnership full of conflict 44:27 PC sales collapse and Apple's touchscreen MacBook 45:44 80% Tesla, 20% Apple: buy, borrow, die 47:48 Elon's bet on humanoid robots and data centers in space 50:12 Google's TPUs in orbit and Rocket Lab

2. 

   29 Oct 2026

   Episode #113: The Infinite Slop Cannon in the Sky: How Elon's Building His Empire

   In this episode of the Stewart Squared podcast, host Stewart Alsop and his son Stewart Alsop II explore the convergence of autonomous robotics, corporate consolidation, and network infrastructure. The conversation kicks off with speculation about a potential Tesla-SpaceX merger, drawing parallels to Japanese keiretsus and examining how Elon Musk might be building what they dub "Musk X"—a unified empire spanning rockets, AI, autonomous vehicles, and satellite networks. From there, they venture into the world of dog bots and robotic operating systems, with Stewart II demonstrating real-time AI-generated web content and discussing his plans to build mesh networks for dance-battling robots. The elder Alsop brings decades of venture capital perspective to bear on topics ranging from Amazon's distribution superiority over Walmart to Salesforce's bold pivot toward agent-based pricing, while they both grapple with fundamental questions about what constitutes an operating system in an age where the boundaries between physical robots, digital networks, and creative tools are rapidly dissolving. Key Insights Here are seven key insights from this episode: 1. Elon Musk appears to be consolidating his various companies into what could be called a modern American keiretsu, similar to the Japanese and Korean conglomerates that organized multiple industries under unified control. The recent Tesla Roadster demo featuring SpaceX thrusters signals a potential merger between Tesla and SpaceX. This consolidation strategy would create an integrated empire spanning rockets, satellites, AI, solar energy, tunneling, and automotive technologies. Musk seems to be moving toward a single company structure that allows investors to bet on him personally rather than individual business units, though the complexity makes it difficult for analysts to properly value the combined entity. 2. The concept of operating systems is evolving beyond traditional definitions as technology moves into robotics and autonomous systems. Historically, operating systems were tied to specific hardware architectures with CPUs and memory, but now the term is being applied loosely to networks and platforms. For robots and autonomous vehicles, operating systems must manage both local hardware and network connectivity simultaneously. Companies like Amazon have developed fleet level coordination systems that function as operating systems for managing thousands of warehouse robots, while Tesla and Waymo have built proprietary systems for their vehicles. The emergence of robotic operating systems represents a fundamental shift in how we think about computing infrastructure. 3. Amazon has successfully built a purpose designed distribution system that competitors like Walmart struggle to match because Amazon anticipated future needs rather than modifying existing infrastructure. Amazon created an ontology that modeled people, warehouses, and distribution centers as an integrated system from the beginning. Walmart faces difficulties because their distribution system was originally designed to serve stores rather than individual consumers. This demonstrates how companies that build systems with future scalability in mind gain significant competitive advantages. Amazon's ability to deliver products next day even in smaller cities like Santa Fe illustrates the power of this forward thinking approach. 4. The economic models for AI companies remain unclear and unstable, with Character AI becoming potentially the first major AI casualty by filing for bankruptcy despite user engagement. Many companies that built applications on top of foundation models are now struggling as those foundation models absorb market value. Salesforce represents an interesting case study as CEO Marc Benioff pivots the entire business model from traditional SaaS subscriptions to charging for AI agent usage and token consumption. This willingness to abandon the old business model before being forced to shows sophisticated awareness of the innovator's dilemma. However, the rapid deflation in API pricing across the industry makes long term revenue modeling extremely challenging. 5. Intellectual property protections are fundamentally changing in both technology and creative fields due to AI capabilities. In technology, proprietary data is replacing patents as the primary defense mechanism since foundation models cannot be easily patented. In creative industries, the core issue is whether AI generated content can be copyrighted when the fundamental concept of copyright assumes human creation. Companies like Adobe, Canva, and Figma that built businesses around design tools now face existential threats because foundation models can generate similar outputs directly. The traditional boundaries between fair use, training data, and copyright infringement remain legally and philosophically unresolved. 6. Mesh networks are transitioning from theoretical concept to practical implementation after decades of being discussed but not realized. A mesh network allows all devices to communicate at equal levels with routing capability distributed across the entire system rather than centralized. Starlink represents a functioning mesh network with satellites constantly moving through space while coordinating coverage and load distribution. The technology enables new applications like coordinated robot systems and autonomous vehicle fleets. However, successful implementation typically requires a single visionary leader with technical depth and resources to force the coordination to happen, which partly explains why competitors struggle to replicate systems like Starlink. 7. The creative capabilities enabled by AI tools are producing unprecedented outputs at minimal cost compared to just two years ago. Work that would have required hiring specialized developers and cost tens of thousands of dollars can now be accomplished overnight by individuals. This democratization of creative and technical capabilities is creating new business opportunities while simultaneously making existing business models obsolete. The challenge lies in finding sustainable economic models when production costs approach zero. Companies must navigate between physical and digital experiences, as demonstrated by immersive experience companies like Meow Wolf potentially facing their own innovator's dilemma as digital technologies advance. Timestamps 00:00 Welcome and episode overview discussing dog bots, Chinese spyware containment, and potential Tesla SpaceX merger speculation following recent demo 05:00 SpaceX going public raises questions about Elon building Japanese keiretsu-style empire consolidating all his companies under single Musk Inc entity 10:00 Exploring keiretsu concept from Japan's postwar economy with horizontal financial clusters and vertical supply chain models like Mitsubishi and Toyota 15:00 Flying Roadster demo was pure stunt using SpaceX thrusters, signaling possible merger while Elon battles SEC over public company regulations 20:00 Robotic operating systems explained as network and hardware coordination requiring autonomy, with Amazon building massive warehouse fleet management systems 25:00 Amazon's purpose-built distribution ontology beats Walmart's store-focused model, demonstrating importance of modeling people not just physical locations 30:00 Linux forks power everything from Android to Starlink satellites as operating systems evolve for multicore CPUs and autonomous robot coordination 35:00 Character AI bankruptcy shows no economic model despite user obsession, while IP protection shifts from patents to proprietary data 40:00 Creative abundance enables rapid website development and potential automation consulting for Argentine custom automotive manufacturers using robotic implementations 45:00 Salesforce pivots to agent-based token pricing abandoning traditional SaaS, while Adobe faces existential threat from foundation models replacing design tools 50:00 Mesh networks evolving from thirty-year concept to reality through Starlink's satellite coordination, with Tesla collecting data versus Waymo's command network 55:00 Next episode promises DogBert demo showcasing mesh network between robot dog, ESP32 microcontrollers, and Raspberry Pi establishing distributed device communication

3. 

   22 Oct 2026

   Episode #112: From the PC to the Robot Dog: How Do Normal People Get Through the Next Shift?

   In this episode of the Stewart Squared podcast, Stewart Alsop III sits down with his father, Stewart Alsop II, to unpack the intersection of AI agents and robotics, kicking off with Stewart III's upcoming hands-on experience with a four-legged dog robot running open-source software. The conversation ranges from the fragile state of current AI autonomy—distinguishing between truly autonomous systems and what are essentially sophisticated loops—to the practical challenges of implementing agents like Muse, Hermes, and Claude in daily life. They explore why industrial robots remain automated rather than autonomous, the security implications of Chinese hardware in American robotics (including Waymo's approach), and AMD's massive $8.2 billion acquisition of World Labs to compete with Nvidia's dominance. Stewart Alsop II brings his decades of tech industry perspective to bear on how normies will adapt to this transition, drawing parallels to previous technological shifts while acknowledging this one's unprecedented speed and scope, while Stewart III shares his experiences with vibe coding and the reality that sim-to-real robotics remains largely promotional material aimed at VCs rather than functional autonomy. Key Insights 1. The challenge of autonomy in artificial intelligence and robotics lies in the fact that what companies promise as autonomous systems are actually just sophisticated loops in code rather than true autonomy. In robotics, there are two key concepts: sim to real and real to sim, with sim to real consistently failing because you cannot successfully transfer simulations directly to real-world robot operations. Current agents from companies like Muse, Hermes, and OpenAI use brute force loops to create the appearance of autonomy, but they lack genuine autonomous decision-making capability. 2. The trust and security concerns surrounding AI agents represent a fundamental problem for widespread adoption, particularly when these agents require access to sensitive personal information. Services like Instinct ask users to authorize full access to email accounts including deletion privileges, while platforms like Muse operate without clear boundaries between user authorization and autonomous action. The recommendation from AI systems themselves, such as Gemini, suggests using intermediaries or read-only access rather than direct account connections, highlighting the inherent security risks in current agent implementations. 3. Meta has taken a strategic lead in consumer-facing AI agents by launching Muse as a mobile application rather than just a web-based service or foundation model feature. This represents a natural evolution for Meta given their success with mobile apps like Facebook and Instagram. By creating a dedicated app with personality features and visual representations, Meta has positioned itself ahead of competitors like OpenAI's dots, though this comes with significant risks as the average consumer may not understand the security implications of granting such broad access to an AI agent. 4. The distinction between automation and autonomy is critical for understanding the current state of robotics. Industrial robots that have been successfully deployed in factories for years are automated, meaning they are hard-coded to perform specific tasks reliably and quickly, but they require reprogramming for any changes. True autonomy, where robots can adapt and make decisions independently in changing environments, remains largely unrealized. The demos circulating on social media are typically either teleoperated or functioning in highly controlled conditions, designed primarily to attract venture capital rather than demonstrate practical autonomous capability. 5. Physical AI represents the next major investment wave as capital seeks new outlets beyond traditional large language models. Companies like AMD's acquisition of World Labs for 8.2 billion dollars and the emergence of spatial computing companies like Niantic demonstrate this shift. The hype around physical AI is drawing capital that previously flowed into data centers, but there is uncertainty about whether these investments will deliver on their promises or simply continue a pattern of high-capital-velocity speculation without delivering practical autonomous systems. 6. The transition to an AI-integrated world will be challenging but manageable for average people, similar to how society adapted to previous technological shifts like personal computers, the internet, and mobile devices. However, this transition is happening much faster than historical changes, compressing what might have taken 180 years of industrial evolution into approximately 10 years. Digital natives who are growing up with AI will have advantages, but even industry leaders like Sam Altman and Dario Amodei are making educated guesses rather than operating from certain knowledge about how this future will unfold. 7. Government and bureaucratic institutions will be the last to successfully integrate AI technologies, even as they face increasing pressure to modernize. The structural collapse of bureaucratic efficiency is not apocalyptic but represents a difficult transition period where institutions struggle with outdated paper-based systems and liability concerns that generate excessive red tape. Local governments face particular challenges due to limited resources, as illustrated by county-level water policy committees trying to manage complex issues with minimal staff and budgets, suggesting that full integration of AI into government operations may take a decade or more. Timestamps 00:00 Introduction of podcast covering Anthropic IPO timing for November and discussion of Muse agents versus Hermes open source framework as agent harnesses 07:46 Conversation shifts to autonomy challenges in robotics, explaining sim-to-real simulation failures and how AI companies promise autonomy through code loops rather than true independence 12:46 Discussion of trust issues with AI agents accessing personal data, comparing Gemini's advice about financial account security and the risks of granting write access to applications 17:46 Debate over transparency problems with autonomous systems and black box technology, noting how foundation models create understanding gaps even for developers building with them 22:22 Analysis of Chinese hardware dominance in robotics manufacturing, Waymo's strategy replacing Chinese firmware with American software, and Connected Vehicle Rule banning Chinese components 27:22 Examination of bureaucratic collapse across institutions, comparing American and Argentine regulatory burdens while discussing local government water policy challenges in Santa Fe County 32:22 Exploration of automation versus autonomy distinction in factory robots, AMD's acquisition of World Labs for physical AI development, and Niantic's spatial intelligence advantages 37:22 Discussion of physical AI as next investment frontier, robotics hand manipulation challenges, and reality disturbance concept where digital creativity merges with physical world 42:22 Reflection on normies adapting to AI transitions, comparing current changes to historical industrial revolution, and examining how ChatGPT companions represent bigger shift than coding tools 47:22 Final thoughts on generational transitions affected by AI, podcast mission exploring age perspectives, and conclusion that autonomous agentic robots remain distant future goal

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Score snapshot 15 Sept 2025

Podcast Authority Score: 62 / 100

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97

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0

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68

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