→ WHAT IT COVERS Matthew Smith, founder of Cronometer Partners, presents well-level modeling of every US natural gas asset to argue that AI data center demand plus committed LNG exports totaling 35 BCF/day will exhaust US working gas storage by 2030, creating an unprecedented structural energy crisis with unbounded upside price risk. → KEY INSIGHTS - **Supply-Demand Gap:** US natural gas production can realistically grow to 128–132 BCF/day maximum, but committed LNG exports alone will reach 35...
This Week's Recap
1 episode · Jul 13 – Jul 19
Latest Insights
Key takeaways from recent episodes
Matthew Smith — Natural Gas: The Next Bottleneck - [Invest Like the Best, EP.483]
- ✓**Supply-Demand Gap:** US natural gas production can realistically grow to 128–132 BCF/day maximum, but committed LNG exports alone will reach 35 BCF/day by 2030, consuming roughly 27% of total output. Adding ~5 BCF/day of credible AI compute demand at P50 probability creates a structural deficit starting in 2028 that storage cannot absorb.
- ✓**Storage Depletion Timeline:** US working gas storage sits at roughly 4 TCF total. Smith's modeling shows storage breaking below all historical ranges by mid-2028, dropping below any recorded level by 2029, and approaching near-zero by 2030. At that point, gas prices become structurally uncapped—not a weather spike but a permanent structural shortage driving electricity prices exponentially higher.
John Kim - How to Raise a Few Billion Dollars - [Invest Like the Best, EP.482]
- ✓**Persuasion Formula:** Persuasion equals desire minus fear, where desire encompasses far more than financial greed — it includes ego, legacy, and values. To move capital, identify what the specific investor actually desires (recognition, access, co-investment rights), then systematically reduce their fear through trust-building rather than logic-heavy pitches alone.
- ✓**Belief vs. Trust Gap:** Investors can fully believe a thesis is correct and still decline to commit capital. Belief is intellectual agreement; trust is emotional conviction that you will deliver. Closing this gap — not winning the logical argument — determines whether money moves. Address fear directly in every meeting rather than adding more data.
Jeremy Giffon - The Billion Dollar PDF - [Invest Like the Best, EP.481]
- ✓**Cap Table Optionality in Volatile Markets:** Founders facing uncertain pivots should prioritize cap table flexibility over maximizing valuation. Insider bridge rounds frequently carry 3x liquidation preferences, warrants, or ratchets that extract value upside rather than downside. In high-volatility periods, raising less capital from investors with wider mandates preserves the ability to shift business models — from per-seat to usage pricing, or from software to services — without structural constraints forcing a single outcome.
- ✓**Narrative Reframing for Stalled Companies:** A company seven years old with 200% growth last year but only $8M revenue struggles to raise because the story starts at founding. The practical fix is reframing the narrative clock — treating the recent inflection point as the company's effective start date. Investors price stories, not spreadsheets. Founders in this position should explicitly reset the narrative anchor rather than defending the full historical timeline.
Etched - Building AI Hardware to Make Inference Faster and Cheaper - [Invest Like the Best, EP.480]
- ✓**Low-Voltage Inference Architecture:** GPUs thermal-throttle because voltage scales quadratically with power — doubling voltage quadruples power draw. Etched runs at under half the voltage of any competing AI chip by redesigning power delivery planes entirely. This unlocks significantly higher flop density without thermal throttling, enabling more compute per watt. Bitcoin miners already proved sub-quarter-voltage operation was physically possible; the question was whether transformer workloads could be restructured to support it.
- ✓**Cluster-Scale Memory as Decode Advantage:** The correct metric for decode performance is not single-chip memory bandwidth but full cluster memory bandwidth. NVIDIA Blackwell chip-to-chip latency runs approximately 4,000 nanoseconds point-to-point, meaning 8-chip tensor-parallel setups deliver far less than 8x throughput gains. Etched built a fully custom interconnect stack above Layer 2, cutting latency by more than 5x, enabling the entire cluster's SRAM and HBM to function as a unified memory pool for token generation.
Recent Episode Summaries
20 AI-powered summaries available
→ WHAT IT COVERS John Kim, former General Catalyst fundraiser who helped build the firm into a multi-billion dollar operation and now leads capital formation at Lila Sciences, breaks down the mechanics of raising capital — covering trust-building frameworks, the three laws of fundraising, and how consensus moves large institutional pools of money. → KEY INSIGHTS - **Persuasion Formula:** Persuasion equals desire minus fear, where desire encompasses far more than financial greed — it includes...
→ WHAT IT COVERS Jeremy Giffon, investor and frequent collaborator with Patrick O'Shaughnessy, covers eighteen months of observations from hundreds of conversations with founders and capital allocators in private markets. Topics span cap table strategy, the rise of "poster class" influence over billionaires, SaaS structural decline, the shift from debt-driven to equity-driven finance culture, and how to evaluate emerging fund managers.
→ WHAT IT COVERS Etched founders Gavin Huberti and Rob Walken explain how they built a transformer-specific AI inference chip on the first tape-out attempt, raising $800M with over $1B in customer demand. They detail their low-voltage inference architecture, cluster-scale memory interconnects, and the vertical integration strategy behind their full rack-scale inference product launched in 2023.
→ WHAT IT COVERS Vlad Barbalat, CIO of Liberty Mutual Investments, explains how the firm deploys $120 billion in permanent insurance capital across private equity, direct lending, real estate, energy, and infrastructure. He covers the mutual insurance structure's investment advantages, portfolio construction philosophy, AI's impact on asset valuations, and how growing up in Soviet Moldova shaped his approach to risk-taking and capital allocation.
→ WHAT IT COVERS Kareem Amin, cofounder and CEO of Clay — a go-to-market software company valued at over $4 billion — shares the unconventional principles behind Clay's growth, including three core values (truth, justice, courage), risk-taking philosophy, and why creating from wholeness rather than lack produces better outcomes. → KEY INSIGHTS - **Three-decision framework:** Clay's entire company strategy flows from three core assumptions: give go-to-market teams the most powerful tool rather...
→ WHAT IT COVERS WhaleRock Capital founder Alex Sacerdote explains his three-part investment framework — S-curves, competitive advantage, and underappreciated earnings power — applied across AI infrastructure, foundational models, and enterprise software. He details his highest-conviction position in Anthropic at a $180B valuation, the decommoditization of hardware, and why enterprise software faces structural headwinds from AI disruption.
Dara Khosrowshahi - Uber's Bet on AVs, AI, and Building a Super-App - [Invest Like the Best, EP.476]
→ WHAT IT COVERS Uber CEO Dara Khosrowshahi outlines how Uber positions itself as the demand aggregator in an autonomous vehicle world, explains the company's path to $10B+ free cash flow, and details expansion into hotels, drones, and a super-app model built around 50 million Uber One members growing 50% annually. → KEY INSIGHTS - **AV Supply Aggregation:** Uber's competitive moat in autonomous vehicles is supply aggregation, not technology ownership.
→ WHAT IT COVERS Dan Loeb, founder of Third Point managing $25B across equities, credit, and insurance, reflects on 30 years of investing evolution — from event-driven deep value in 1995 to quality investing, thematic tech, and a $7B CLO business — while sharing his current conviction that AI-related semiconductors remain the most attractive sector despite the SOX index rising 40%.
→ WHAT IT COVERS Darren Farber, managing partner of Albion River defense investment firm, analyzes the Iranian military contingency, U.S. magazine depth deficiencies, China's structural illegitimacy, and what Congress must change in procurement law to enable neo-prime defense companies to scale and replace legacy prime contractors over the next decade.
→ WHAT IT COVERS Gavin Baker, CIO of Atreides Management, analyzes the two physical constraints shaping AI's next phase: power (Watts) and semiconductor manufacturing capacity (Wafers). He covers TSMC's role in preventing an AI bubble, orbital compute as a long-term power solution, GPU disaggregation extending hardware lifespans, and where economic value accrues across the AI stack.
→ WHAT IT COVERS Anthropic CFO Krishna Rao explains how the company manages compute as its core strategic resource, covering the allocation framework across training, internal use, and customer demand, the economics behind frontier model pricing, the $9B to $30B ARR growth in one quarter, and why enterprise returns to frontier intelligence continue accelerating rather than plateauing.
→ WHAT IT COVERS Airbnb cofounder Brian Chesky traces his path from industrial design training at RISD through the pandemic crisis that forced him into founder mode, explaining how those same principles now apply to AI-era company building, product market fit methodology, recruiting strategy, and shifting from adulation-driven to craft-driven motivation.
→ WHAT IT COVERS Paul Tudor Jones reflects on 50 years of macro trading with Patrick O'Shaughnessy, covering the structural differences between trading and investing, current equity market overvaluation at 252% of GDP, AI safety risks, the mechanics of identifying major market moves, and how kindness and philanthropy shape a meaningful life beyond markets. → KEY INSIGHTS - **Trading vs. Investing Identity:** Jones envies long-term investors like Buffett but acknowledges his fund maintains a -0.
→ WHAT IT COVERS Dylan Patel of Semianalysis details how AI token demand is growing faster than infrastructure can supply it, using Semianalysis's own spending trajectory from tens of thousands to $7M annually as a case study, while mapping semiconductor bottlenecks in memory, logic, and fab equipment that constrain scaling through 2028. → KEY INSIGHTS - **Token spend as competitive moat:** Enterprise AI contracts with Anthropic now include rate limit increases as a strategic asset.
→ WHAT IT COVERS Biotech investor Alex Karnal outlines a five-layer "health stack" framework covering lipid optimization, cardiometabolic health, neurocognitive health, inflammation, and blood pressure. He argues that existing medicines — GLP-1 agonists, PCSK9 inhibitors, and anti-amyloid therapies — can already extend human lifespan by a decade if deployed proactively, and that AI-driven drug discovery will compress development timelines from years to months.
→ WHAT IT COVERS Scott Nolan — SpaceX early engineer, Founders Fund investor for 12+ years — explains his framework for identifying underappreciated problems, the contrarian investment philosophy behind Founders Fund's biggest wins, and why he left investing to build General Matter, a startup rebuilding US uranium enrichment capacity that vanished entirely after the 1990s.
→ WHAT IT COVERS Alan Waxman of Sixth Street traces the U.S. financial system through three regulatory eras—Glass-Steagall (1933), its 1999 repeal, and post-2008 Basel III reforms—to explain how private credit grew from $500B to $2T, why the "factory model" of capital raising now dominates, and what asset-liability mismatches mean for markets today. → KEY INSIGHTS - **Three-System Framework:** U.S.
→ WHAT IT COVERS Sergey Levine, cofounder of Physical Intelligence, explains why building general-purpose robotic foundation models — systems that control any robot for any task — is more tractable than narrow domain-specific approaches, drawing direct parallels to how large language models outcompeted specialized NLP systems by leveraging broad, weakly-labeled data at scale.
→ WHAT IT COVERS Mitchell Green, founder of LeadEdge Capital, details the systematic investment machine he built over 15 years with partners Brian and Nima — covering their 9,000 annual cold calls, eight-point company criteria, LP network of 800 executives, and disciplined focus on 2–2.25x net returns across 20-position funds. → KEY INSIGHTS - **LP Network as Competitive Moat:** LeadEdge's 800 LPs are 95% senior executives and entrepreneurs — not institutions — deployed across the full...
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Resources mentioned on Invest Like the Best with Patrick O'Shaughnessy
Books, tools, and gear cited by guests across episodes we've summarized.
- tool
Ridgeline
Cited in 8 episodes of Invest Like the Best with Patrick O'Shaughnessy
- company
OpenAI
Cited in 7 episodes of Invest Like the Best with Patrick O'Shaughnessy
- tool
Ramp
Cited in 7 episodes of Invest Like the Best with Patrick O'Shaughnessy
- tool
WorkOS
Cited in 7 episodes of Invest Like the Best with Patrick O'Shaughnessy
- company
Anthropic
Cited in 6 episodes of Invest Like the Best with Patrick O'Shaughnessy
- tool
Vanta
Cited in 6 episodes of Invest Like the Best with Patrick O'Shaughnessy
- tool
Claude
by Anthropic
Cited in 3 episodes of Invest Like the Best with Patrick O'Shaughnessy
- company
Databricks
Cited in 3 episodes of Invest Like the Best with Patrick O'Shaughnessy
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