They Beat All US Stock Funds Since 2003 | Michael Baron on the AI Winners Investors Miss

Episode Summary

Executive Summary: Baron Capital co-president Michael Barrett describes a growth-investing philosophy centered on competitive advantage, long-term ownership, and deep primary research. He argues AI is real but won’t create only a few winners; instead, it will reshape many sectors, including software, financial services, real estate, Tesla, and SpaceX. He emphasizes mission-driven leadership, valuation discipline, portfolio balance, and AI as a force that enhances active management rather than commoditizing it.

Main Topics: Baron Capital’s growth-investing philosophy (Priority: 5/5): Barrett explains that Baron seeks growth across sectors, not just technology, and builds balanced portfolios to reduce correlation and volatility. The firm focuses on long-term performance, not quarterly outperformance, and tries to find growth in overlooked areas like financials, real estate, and consumer businesses. AI as a real, transformative, but uneven trend (Priority: 5/5): He rejects the idea that AI is a bubble and says it will generate both winners and losers. Baron looks for companies that either enable AI or benefit from AI via proprietary data and execution, rather than assuming all AI-adjacent companies will win. Why software companies are not automatically disrupted (Priority: 5/5): Barrett argues that many software and data businesses have defensible moats because AI needs proprietary, high-quality data. He cites Shopify, Guidewire, FactSet, MSCI, and Gartner as examples of companies that can use AI rather than be displaced by it. Tesla as a mission-driven, multi-phase investment (Priority: 5/5): Barrett recounts Baron’s long relationship with Elon Musk and Tesla, describing the investment thesis as moving from premium EV manufacturer to mass-market platform to software and energy business. He stresses Tesla’s vertical integration, autonomy, and energy optionality. SpaceX, Starlink, and the economics of access to space (Priority: 5/5): He frames SpaceX as a once-in-a-generation infrastructure business with dramatic cost declines in space launch and Starlink as a communications platform with global scale. He also extends the idea to AI in space, data centers, and satellite-based compute. Valuation, position sizing, and selling discipline (Priority: 4/5): Barrett says Baron is valuation-focused, but valuation must be judged on future optionality, not just today’s numbers. The firm lets winners run, trims when needed, and sells only when competitive advantage deteriorates—not simply because a stock has appreciated. People, curiosity, and active management in the AI era (Priority: 4/5): He says investing is fundamentally about people, competitive advantage, and doing independent research. His contrarian view is that AI will make active management more important by democratizing data but not judgment.

Key Arguments: AI is real and transformative, but it will create a broad set of winners and losers rather than a single concentrated winner set. Baron Capital’s edge comes from looking for growth in many sectors and building portfolios with different drivers to reduce correlation. Software is not universally threatened by AI because many companies own proprietary data that cannot be easily replicated or disintermediated. Tesla should be valued as a mission-led platform spanning EVs, autonomy, software, and energy—not as a simple car manufacturer. SpaceX’s economics could dramatically expand the addressable market for launch, communications, and eventually space-based computing. Selling decisions are based on changes in competitive advantage, not price targets or arbitrary time horizons. AI will likely strengthen active management because it amplifies the value of judgment, research, and differentiated insight. Curiosity and primary research are central to conviction; investors should directly engage with executives and businesses rather than rely on secondhand research.

Data Points: Baron Capital client assets: $69 billion - Size of the firm mentioned in the introduction. Baron Capital strategy performance: 97%-98% of strategies/assets beat their index since inception - Barrett cites long-term performance across the firm’s strategies. Top-quartile performance: 92% of funds are in the top quartile - He describes the distribution of fund rankings over time. Top-decile/top 1% performance: Over half of funds are in the top 1% of their categories - Barrett highlights how many funds rank among the best in their peer groups. Baron Capital average holding period: 8 or 9 years - Used to explain long-term ownership and why winners can compound for years. Tesla vehicles produced then vs. now: ~30,000 then to ~2 million today - Illustrates Tesla’s growth since Baron first invested. Tesla revenue then vs. now: ~$3.5-$4 billion then to ~$100 billion today - Shows how Tesla scaled beyond its original business model. Tesla vehicle economics: ~15% profit margin on a $40,000 vehicle; about $6,000 per vehicle - Used to compare current auto economics with software subscription potential. Tesla software subscription: ~$100 per month - Barrett uses this to argue that software/autonomy can double profitability over several years. Tesla full-service driving adoption: About half of customers already signing up - Presented as evidence of demand for autonomy-related features. Cybercab target price: Below $30,000, possibly low $20,000s - Part of Tesla’s future autonomy/manufacturing thesis. Cybercab operating cost target: ~30 cents per mile total; ~60 cents per passenger mile - Used to explain potential economics of autonomous transport. SpaceX launch cost comparison: NASA ~ $50,000 per kilo; competitors ~ $20,000 per kilo; SpaceX ~ $1,000 per kilo - Highlights SpaceX’s launch cost advantage. Future SpaceX launch cost target: Hundreds of dollars per kilo - Barrett says Starship could drive costs down further. SpaceX launch share of mass to orbit: ~90% - He says Falcon currently dominates mass-to-orbit launches. Starlink customers: ~13 million - Used to show rapid growth in global internet service adoption. Fiber cost range: $3,000 to $100,000 per mile - Compared against Starlink’s economics for internet access. Satellite count: ~11,000 current satellites; could grow to ~100,000 - Barrett outlines the scale of future constellation expansion. Satellite capability multiplier: 10x more capability per satellite and 10x more satellites - He frames this as a potential 100x increase in functionality. AI winners vs. losers performance in 2024: Winners +51%; losers +23% - Illustrates the large gap in market performance across AI-related buckets. AI winners vs. losers performance in 2025: 15.5% delta - Shows the widening or continuing spread between the two groups. AI winners vs. losers performance in first half of 2026: 47.5 percentage points delta - Demonstrates even more extreme divergence before a recent reversal. Tesla allocation example: ~8%-9% initially in Baron Partners Fund; later over 40% at peak - Used to explain how winners can become very large portfolio weights. Baron Capital staffing and holdings: ~45 investment professionals covering ~500 holdings - Shows the breadth of research resources relative to the number of investments. SpaceX/Starship test timing: A Starship test launch was scheduled for the following week - Used to discuss iterative engineering and uncertainty in frontier projects. SpaceX/AI infrastructure buildout: 1.4 gigawatts in the ground, expected to end the year near 2 and next year 5-10 - Describes rapid data-center-related capacity expansion.

Pivotal Quotes: "AI is going to democratize data, but it's going to democratize judgment." — Michael Barrett: He explains why AI should strengthen rather than weaken active management. "If you want to achieve this, you're going to be going from 30,000 vehicles back then... to how do you get into the mass?" — Michael Barrett: Describing the Tesla thesis from niche EV producer to mass-market platform. "It's not the growth that is most important to us. It's the competitive advantage." — Michael Barrett: He states Baron’s core investment filter and long-term framework.

Implications: For investors, the message is to look beyond headlines and evaluate AI through competitive advantage, data ownership, and leadership quality. The biggest opportunities may be in companies that use AI well, not just pure AI names. Long-term, AI may reward active managers who do deeper research and stay patient.