AI & Robotics Stealing Crypto's Thunder? | EP 73

This episode dissects the stark contrast between the current crypto market's focus on internal competition and incremental gains versus the explosive, attention-grabbing innovation happening in AI and robotics, exploring the strategic implications for investors and builders in both spaces.

The Shifting Tides of Innovation: AI & Robotics vs. Crypto

• The speakers open by observing a significant shift in attention and excitement away from crypto towards AI and robotics. They characterize the current AI and robotics landscape as being in a period of rapid innovation capturing "minds and hearts," while crypto appears to be in a "rebuilding process."
• Strategic Implication: Investors should recognize that capital and talent attention are currently flowing heavily towards AI and robotics, potentially impacting crypto project valuations and the pace of crypto-native innovation in the near term.

Crypto's Dominant Narratives: Stablecoins and Tokenization

• The conversation highlights that the prevailing narratives within crypto, among builders, investors, and even "degens," revolve around stablecoins and tokenization. Stablecoins are cryptocurrencies designed to maintain a stable value, typically pegged to a fiat currency like the US dollar.
• Tokenization involves representing traditional assets (like real estate or securities) as digital tokens on a blockchain. While acknowledging these are now consensus plays, the speakers note a lack of groundbreaking innovation, framing it more as "reinventing the wheels" by putting traditional assets on-chain.
• Fidelity's recent stablecoin announcement is cited as an example of institutional adoption within this existing framework.
• Actionable Insight: While stablecoins and tokenization offer infrastructure plays, investors should critically assess the innovative edge of new projects in this space, as the core concept is becoming increasingly commoditized by large institutions.

Crypto's Competitive Battlefield: Exchanges and Protocols Clash

• The discussion paints a picture of intense, zero-sum competition within crypto, particularly in trading. Binance's actions are analyzed as evidence:
• Their public stance against Hyperliquid (a decentralized derivatives exchange) is seen as a move to neutralize a competitive threat to their core exchange business.
• Binance listing meme coins originating from Pump.fun (described as a copycat of Pump.fun on the BNB chain) is interpreted as a direct competitive response to the success of Pump.fun and Jupiter exchange on Solana. Pump.fun is a platform allowing rapid creation and trading of tokens, primarily meme coins, on Solana.
• The speakers frame this as an "on-chain versus off-chain war," where established centralized exchanges (like Binance) and newer decentralized protocols (like Hyperliquid, Pump.fun, Jupiter) are fighting aggressively for the same trading revenue and user base.
• Quote: "Everyone is going after the same businesses exactly which is basically trading exactly trading on one side and then stable on the other."
• Strategic Implication: The intense competition suggests margin compression is likely. Investors should favor platforms with clear differentiation, strong network effects, or unique value propositions beyond basic trading, as incumbents aggressively defend their market share.

Robin Hood's Multi-Pronged Strategy and Crypto Threat

• Robin Hood's recent strategy presentation reveals ambitious plans impacting both traditional finance and crypto. Key takeaways include:
• A strong belief in the "tokenization of everything" thesis, leveraging their significant distribution network.
• Plans to introduce tokenized real estate trading, potentially via derivatives rather than spot assets, aligning with their user base's appetite for leverage.
• A surprising "cash delivery service," potentially aimed at capturing deposits, competing with ATMs, and tapping into the demand for financial privacy, moving users away from traditional banks.
• The speakers identify Robin Hood as a major competitive threat not only to established crypto exchanges like Coinbase but also to crypto startups focused on tokenization, given Robin Hood's distribution power.
• Actionable Insight: Robin Hood's aggressive expansion across TradFi, crypto trading, and potentially banking services makes it a key player to watch. Its success could significantly alter the competitive dynamics for existing crypto platforms and tokenization startups.

Crypto Market Consolidation and the Search for Growth

• The discussion reinforces the theme of a shrinking competitive landscape where major players (Binance, Hyperliquid, Coinbase, Pump.fun, Jupiter) vie for the same limited pool of trading activity. Data points like Pump.fun's volume rivaling Radium (a major Solana Automated Market Maker or AMM) underscore this dynamic shift.
• An AMM is a type of decentralized exchange protocol that relies on mathematical formulas to price assets. The core challenge identified is the need to "open up the pie" and attract new users to crypto, moving beyond the current zero-sum competition.
• Key Stat: Pump.fun's 24-hour volume was cited as roughly $294 million, rivaling Radium's volume, indicating significant market share capture in the meme coin/small-cap trading niche.
• Strategic Implication: Sustainable growth in crypto likely requires moving beyond optimizing existing trading models. Investors should look for projects focused on onboarding new users, creating novel use cases, or bridging crypto with real-world applications in ways that expand the overall market.

Exploring Niche Crypto Innovations: Financializing Attention

• While major innovation seems slow, some experiments are noted, such as Noise on MegaETH. This platform reportedly uses Kaido (described as an oracle for mindshare data) to allow users to long or short trends, essentially "financializing attention." Kaido provides data feeds used as a source of truth for smart contracts, in this case, tracking attention or trends.
• Although viewed as a "regurgitation" of older theses, it represents attempts to find new crypto-native applications.
• Actionable Insight: While niche experiments like attention markets may not be landscape-changing yet, they signal ongoing exploration for novel crypto use cases. Researchers should track these experiments for early signs of potentially disruptive models.

Circle's IPO and Strategic Challenges

• Circle's planned IPO reveals significant business model dependencies. Key points include:
• A valuation likely in the $4-5 billion range.
• A crucial reliance on Coinbase for USDC distribution, evidenced by Circle paying 50% of its reserve revenue (yield earned on USDC reserves) to Coinbase – amounting to $800 million on $1.7 billion revenue last year. This highlights Coinbase's leverage as the primary distribution channel.
• This dynamic mirrors the Pump.fun/Radium situation, where control over the end-user grants significant bargaining power.
• An existential risk looms if treasury yields drop significantly, impacting Circle's core revenue stream.
• USDC's dominance is largely US-centric, with USDT (Tether) prevailing globally, particularly noted in Latin America ("USDC is pretty cooked in LatAm at the street level.")
• Despite challenges, Circle's cctp (Cross-Chain Transfer Protocol) is praised as a valuable, centralized bridge solution for moving USDC between chains efficiently and securely. cctp allows users to burn USDC on one chain and mint an equivalent amount on another, facilitated by Circle.
• Strategic Implication: Circle's IPO filing underscores the critical importance of distribution channels in crypto. Investors evaluating stablecoin issuers or protocols should scrutinize their distribution partnerships and revenue dependencies. The potential impact of falling interest rates on reserve-based revenue models is a key risk factor.

Crypto Incumbents Expand Horizons: M&A Activity

• Recent M&A activity signals a push by established crypto players to diversify beyond core crypto trading:
• Kraken's acquisition of NinjaTrader (a traditional derivatives platform).
• Rumors of Coinbase making an offer for Deribit (a major crypto derivatives exchange).
• This trend suggests incumbents recognize the limitations of relying solely on the existing crypto market and are seeking growth in adjacent traditional finance sectors or consolidating power within crypto derivatives.
• Actionable Insight: Consolidation and diversification by major crypto exchanges are key trends. This could present opportunities for acquired companies, but also increase competitive pressure on smaller, specialized platforms.

Market Sentiment Check: Caution and Key Players

• Market sentiment appears cautious, influenced by macroeconomic factors and actions of large players.
• Michael Saylor's MicroStrategy continues its aggressive Bitcoin accumulation ($2 billion offering used to buy near the local top). While his liquidation risk seems low (<$20k BTC), the strategy is noted as "very aggressive."
• GameStop's $1.6 billion offering mirrors Saylor's approach, potentially signaling market tops or opportunistic capital raises.
• The speakers highlight the potential market impact of political statements, specifically mentioning Donald Trump's influence.
• Strategic Implication: Investors should remain aware of macro influences and the actions of large holders like MicroStrategy, which can impact short-term market sentiment and volatility. Political developments related to crypto regulation remain a critical factor.

Public Market Bets: AI, Robotics, and Distribution

• The discussion shifts to attractive public market investments, favoring companies deeply involved in AI and robotics or possessing strong distribution:
• Google: Seen as making a comeback in AI with a "reasonable" valuation (forward P/E ~17). Its deep software DNA is considered well-suited for the AI race.
• Tesla: Described as the "most liquid venture bet" on the future of Full Self-Driving (FSD) and humanoid robots (Optimus, potentially rolling out late 2026/2027). Personal anecdotes highlight rapid improvements in FSD performance.
• Robin Hood: Considered a strong contender due to its distribution and strategic positioning across TradFi and crypto, potentially favored over Coinbase.
• Actionable Insight: For investors seeking exposure to AI/robotics via public markets, Google and Tesla represent distinct bets on core AI development and applied robotics/autonomy, respectively. Robin Hood offers a play on financial market disruption leveraging distribution.

The US-China Tech Race: Competition Intensifies

• A significant portion focuses on the escalating technological competition between the US and China, drawing parallels to historical periods like Japan's post-war industrial rise. Key observations include:
• The US strategy of "shutting out" imports/exports and focusing on domestic production (reshoring) carries risks like higher consumer prices and acknowledges historical US struggles with manufacturing yield (e.g., early chip manufacturing).
• China's dominance in manufacturing is seen as a strategic advantage, enabling rapid iteration and cost reduction. Palmer Luckey (Anduril founder) is cited comparing Chinese (300/day) vs. US (10-12/day) battleship production capacity as an example of this manufacturing gap.
• China is rapidly closing the gap or even surpassing the US in key areas:
• AI: Deep Seek AI model presented an "existential crisis" moment for US dominance.
• Electric Vehicles: BYD and other Chinese EVs are seen as potentially better designed, more performant, and cheaper than competitors like Tesla, with autonomy (FSD) being Tesla's main remaining edge.
• Humanoids: The expectation is that China will quickly copy and improve upon initial humanoid robots developed by companies like Tesla.
• The speakers note the pattern: US innovates (EVs, solar, AI, social media), China learns, manufactures efficiently, and often produces better, cheaper products within generations.
• Strategic Implication: The US-China tech rivalry is a critical geopolitical and investment factor. China's manufacturing prowess and rapid AI development present both competitive threats and potential investment opportunities (e.g., selected Chinese tech stocks like Tencent, PDD). Investors must factor this dynamic into global tech allocation strategies.

AI Model Landscape: Fierce Competition, No Moats

• The AI model space is characterized by intense competition and a lack of durable moats.
• Experiences with models like Manus, Google Gemini, and ChatGPT show rapid capability leaps and shifting user preferences based on specific tasks. Gemini is highlighted for its strong deep research capabilities and new live conversational features.
• Sesame is mentioned as a highly advanced voice AI model, potentially passing the Turing Test in its human-like interaction.
• Google's comeback is emphasized, fueled by its AI DNA, ability to leverage unique data (like YouTube transcripts for research), and the return of co-founder Sergey Brin.
• High valuations persist, with OpenAI reportedly raising at a $300 billion valuation (SoftBank involved).
• Big Tech is all-in: Amazon launched a browser-based AI product, and Jeff Bezos is reportedly re-engaged and focused on AI.
• Quote: (Regarding switching between AI models) "It's like every couple weeks I have to change my behavior to use the latest thing so there's no mo."
• Actionable Insight: The rapid iteration in AI models means investors should be wary of betting on a single "winner." Focus may shift towards infrastructure, specialized applications, or companies effectively integrating multiple leading models. Google's resurgence makes it a key player to monitor closely.

The Transformative Power of AI Coding

• AI's impact on software development is profound and accelerating.
• The Replit CEO's viral comment ("I no longer think you should learn to code") is discussed, clarified as likely meaning you don't have to rather than you shouldn't.
• Founders report significant productivity gains (2x-4x) using AI coding assistants like Cursor and GitHub Copilot (implicitly referenced via "Windsruf" likely being a transcription error for Copilot/similar).
• "Vibe coding" emerges: Non-technical founders can now translate their vision directly into functional front-end code using AI tools, bridging the gap with technical co-founders and accelerating prototyping.
• Personal anecdotes confirm non-technical individuals can now build functional applications (like Telegram bots) using AI assistance.
• Strategic Implication: AI coding drastically lowers the barrier to entry for software creation. This empowers non-technical founders, accelerates startup iteration ("era of the idea guy,") and potentially reduces the capital needed to reach MVP or even unicorn status. Investors should anticipate a surge in software-based startups and tools enabling this trend (like Poof, mentioned as building "vibe coding for crypto.")

The Rise of Micro Apps and Niche Opportunities

• AI coding enables a new wave of highly customized, niche software applications ("micro apps.")
• Individuals can build personalized apps (e.g., a language learning app tailored to specific needs) far superior for their use case than mass-market alternatives like Duolingo.
• This unlocks opportunities for "micro-unicorns" – businesses serving small, specific global niches profitably (e.g., the Yat phone example, replacing Skype for landline users, reportedly making $10k/month).
• These smaller, profitable ventures may not target IPOs, making tokenization a potentially viable path for achieving liquidity for founders and early backers.
• Actionable Insight: The AI-driven micro-app economy presents new investment avenues, potentially outside traditional VC models. Look for platforms enabling micro-app creation and consider tokenization models for providing liquidity to successful niche businesses.

Shifting Demographics: Younger Founders and the Education Disruption

• AI is coinciding with, and perhaps accelerating, shifts in founder demographics and education.
• Younger founders, including college dropouts, are increasingly launching successful ventures (e.g., the 18-year-old founder of Cal AI, a calorie-tracking app reportedly reaching $10M ARR).
• Nikita Bier's perspective on status is referenced: True status comes from creation and impact (building products, winning elections, taking companies public), not institutional credentials (Harvard, Google).
• The speakers' own experience at Alliance confirms a trend of successful founders being younger, often fresh grads or early 20s (citing Princeton dropouts in their current batch).
• AI is poised to disrupt traditional K-12 education. Examples like Alpha School in Texas show AI tutors enabling students to master academics in significantly less time (2 hours/day) while outperforming peers and focusing on practical skills (startups, TED-style talks). The vision is personalized AI tutors replacing the inefficient classroom model.
• Strategic Implication: Talent identification needs to adapt, recognizing potential in younger, less credentialed founders who leverage AI effectively. The disruption of education by AI creates investment opportunities in EdTech platforms and new schooling models like Alpha School.

Parenting in the Age of AI: Fostering Agency

• The discussion touches on parenting philosophies relevant in an AI-driven world, referencing Naval Ravikant's recommendations.
• The core idea is fostering "agency" in children from a young age by allowing them to make their own decisions and learn from mistakes, rather than simply following instructions. Agency refers to the capacity of individuals to act independently and make their own free choices.
• Practical examples include letting kids manage their own choices (like food) within set boundaries (like required reading/math time), leading to self-discovered understanding (e.g., realizing excessive ice cream isn't healthy).
• Encouraging core skills (reading, math) and then allowing exploration based on interest (e.g., using Kindles for reading, building robots for a child interested in building) is highlighted.
• Actionable Insight: While not direct investment advice, understanding the importance of agency is relevant for identifying founders and talent. Individuals who are self-directed, curious, and capable of independent learning (skills fostered by agency-focused upbringing/education) are likely to thrive in the rapidly changing AI landscape.

AI's Inroads into Healthcare and Professional Services

• AI is making significant strides in healthcare and impacting professional jobs.
• AI Doctors: Apple is seen as ideally positioned due to its vast health data (Apple Watch, HealthKit), but significant startup opportunities exist. Personal anecdotes show AI (like ChatGPT) being used for health advice, checking diagnoses, and getting detailed explanations doctors may not have time for. Telemedicine is viewed as a step towards fully AI-driven personalized healthcare.
• Job Displacement: AI is expected to displace many junior roles across industries – lawyers, venture analysts, researchers. The need for analysts is diminishing as AI handles research tasks.
• Building Reputation: Professionals will need new ways to establish credibility beyond traditional roles, potentially through public demonstration of expertise and intuition (e.g., via Twitter).
• Generalists vs. Specialists: While AI boosts generalists, the most experienced specialists retain an edge due to unique data and intuition AI lacks. However, AI empowers everyone with agency to learn and compete more effectively.
• Strategic Implication: Investment opportunities abound in AI healthcare (diagnostics, personalized medicine, AI doctors). However, investors must also consider the societal impact of AI displacing junior professional roles and how talent development and career paths will evolve.

Potential Market Moves: Amazon and TikTok

• The episode briefly concludes with speculation about Amazon potentially making a bid to acquire TikTok, suggesting ongoing strategic maneuvering among Big Tech players.

This episode paints a picture of divergence: crypto is consolidating and competing internally, while AI drives exponential innovation across multiple sectors. Crypto AI investors and researchers must track AI's cross-industry impact, identify crypto projects genuinely leveraging AI for utility beyond hype, and recognize the shifting competitive landscape shaped by both Big Tech and nimble startups.