Pitch The PM

PitchThePM
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Pitch The PM is the professional investor’s podcast where host Doug Garber dives deep into high-conviction stock ideas using his Variant View Investment Checklist. It’s a real-time look at the research process, blending lessons from Buffett, Munger, and Lynch with modern AI tools. Join Doug, ex-Citadel top analyst and Millennium Sr PM, as he works through his Buffett-inspired 20-slot punch card. Learn, laugh, and sharpen your edge.

  1. 1 day ago

    EP.50: Why Stanley Drunkenmiller seeded Rich to build the next Bloomberg!l–with Rich Falk-Wallace, CEO & Co-Founder or Arcana

    In 2019, Ken Griffin, Founder & CEO of Citadel, was looking for some of the best risk-takers on Wall Street. He landed on Rich Falk-Wallace, then a top analyst at Viking, who went on to become a Portfolio Manager at Citadel’s Surveyor Capital. So what comes next after becoming a PM at Citadel at 29? For the past five years, Rich has been building Arcana, a financial technology platform designed to help the world’s top hedge funds and asset managers make smarter decisions, faster. His philosophy is heavily influenced by Steve Jobs: obsess over the details and build products that genuinely delight customers. In this episode, Rich breaks down the secular growth of beta-zero products, the rapid expansion of separately managed accounts (SMAs), the rise of alpha capture, and how human investment signals can complement quantitative systems. We also discuss portfolio construction, product-market fit, and how Arcana is integrating AI across its platform while staying focused on the customer. “How did you convince Stanley Druckenmiller to be your seed investor?” “The problem of portfolio construction is way closer to solved than that last mile of, ‘What’s a good idea?’” “The allocation of dollars in public markets is headed towards beta one or beta zero products.” “SMA-type products are growing massively in every direction. And that comes from allocators of every kind — sovereign wealth funds, endowments…” Topics: Arcana, Citadel, Surveyor Capital, Viking, Hedge Funds, Financial Technology, Separately Managed Accounts, Beta Zero, Alpha Capture, Portfolio Construction, Investment Research, Artificial Intelligence, APIs, MCPs, Product-Market Fit *Not Investment Advice [00:00:27] Rich’s journey from distressed credit and public equities into financial technology. [00:02:20] Why timing, experience, and energy pushed him to make the entrepreneurial leap. [00:04:07] Why domain expertise helps — but nobody has a “right to win.” [00:08:43] What it takes to earn backing and why product obsession matters. [00:11:07] Arcana’s “platform maximalist” approach to software, APIs, MCPs, Excel, and LLMs. [00:14:35] “If you think something is easy, it’s because you’re the buyer.” [00:17:11] Why founders need to forget how hard something is and focus on the customer experience. [00:19:56] Learning to love the incremental process of building. [00:22:38] Finding product-market fit and the shift toward beta-one and beta-zero products. [00:26:52] Why separately managed accounts are growing explosively. [00:28:11] What an SMA is and how it differs from a commingled fund. [00:31:03] How Arcana helps allocators analyze risk, performance, attribution, and repeatability. [00:34:20] Mock portfolios, analyst tracking, and creating better feedback loops for investment talent. [00:40:58] Alpha capture and turning human conviction signals into systematic portfolios. [00:45:45] How Arcana uses AI internally to build software. [00:47:32] Measuring the ROI of AI and token spending. [00:49:58] MCPs, on-platform AI, and giving different investors different ways to access the same insights. [00:54:51] Is Arcana a software company or a data company? Why Rich sees it as both. [00:59:17] Rich’s philosophy of delighting customers and continually improving the product. 💡 This episode is powered by: Fiscal.AI: Delivering Modern Financial Data Infrastructurehttps://fiscal.ai/ Pitch The PM Links: 📩 Subscribe to our Substack for research updates, new high-conviction episodes from top PMs, and our Job Board:https://pitchthepm.substack.com/ Doug Garber on LinkedIn for daily market color:https://www.linkedin.com/in/doug-garber-42aa508 Rich Falk-Wallace Links: Rich Falk-Wallace on LinkedIn:https://www.linkedin.com/in/rich-falk-wallace/ Arcana:https://www.arcana.io/

  2. 2 Sept

    EP.49: Why the AI Boom Is Still Early with Daniel Pilling from Sands Capital

    Daniel Pilling, Co-PM of the Sands Capital Global Growth Fund, has spent nearly 20 years investing across long-only and long-short strategies, including time at Fidelity, Millennium, and Balyasny. Today at Sands Capital, he takes a very different approach: concentrated, deep-dive investing in high-quality growth companies with the potential to compound for years. In this episode, Daniel breaks down why he believes the AI investment cycle is still incredibly early. We discuss $NVDIA, $TSMC, $ASML, memory, AI agents, the return on GPU infrastructure, and why compute could remain supply constrained for a long time. Daniel also explains why Anthropic's growth has been unlike anything he's seen before and how Sands thinks about finding the long-term winners as AI diffuses across the economy. If you're wondering whether the AI trade has gone too far—or whether we're still at the beginning of a much larger cycle—this conversation offers a long-term investor's framework for thinking about what comes next. "I've never seen anything like this." "We're going to be supply constrained in terms of compute for a very long time." “The reason for that is, again, the low penetration and the high ROI of what’s happening.” "Anthropic and agentic AI is incredible. And it's just going viral and the pace of adoption is unheard of." Stocks: $NVDA, $TSM, $MU, $ASML, $AMZN, $GOOGL, $META, $AMD, $ZM Topics: Sands Capital, Artificial Intelligence, NVIDIA, TSMC, ASML, Memory, AI Agents, Anthropic, Compute, Semiconductors, GPU Economics, Long-Term Investing, AI Infrastructure, AI Innovator Fund *Not Investment Advice [00:00:00] Introduction to Daniel Pilling, Co-PM of the Sands Capital Global Growth Fund. [00:01:15] Daniel’s path from banking and multi-manager investing to long-term growth. [00:03:02] How Daniel became obsessed with investing at 12. [00:04:13] Why Daniel left Millennium and Balyasny for Sands Capital. [00:05:14] Sands Capital’s philosophy: concentrated portfolios, deep research, and long-term ownership. [00:07:32] Why memory and NVIDIA remain high-conviction AI investments. [00:09:54] NVIDIA’s market share and why open-source AI could support GPU demand. [00:12:20] Why NVIDIA, Cerebras, Trainium, and TPUs can all win. [00:14:13] The case for a memory shortage as AI agents scale. [00:19:00] Why memory may not follow a traditional cyclical pattern. [00:22:13] AI infrastructure returns and increasingly valuable compute. [00:23:48] Why rising older-GPU prices challenge depreciation concerns. [00:24:23] Anthropic’s growth, Zoom during COVID, and rapid agentic AI adoption. [00:26:46] Why AI compute could remain supply constrained and create an “upside cliff.” [00:28:34] Why Daniel compares AI adoption to electricity. [00:30:42] How AI could make investment research faster and more effective. [00:32:03] Why ASML and TSMC remain key AI infrastructure constraints. [00:34:28] Generating differentiated returns through multi-year views. [00:37:52] Why 99% of daily market information doesn’t matter. [00:39:52] Humility in investing and recognizing when the Zoom thesis changed. [00:43:42] Why AI remains early, underpenetrated, and rapidly improving. [00:46:22] Sands Capital’s AI exposure across semis, memory, cloud, and software. [00:52:56] The case for Meta despite rising CapEx and declining free cash flow. [00:56:45] The fund’s AI exposure and global diversification. [00:58:14] The AI Innovator Fund thesis: low penetration, constrained compute, and AI winners. 💡 This episode is powered by: Oxford Data Plan: Request a Demo  AlphaSense: Request a Demo Pitch The PM Links: 📩 Subscribe to our Substack for research updates and new high-conviction episodes from top PMs, and our Job Board: ⁠https://pitchthepm.substack.com/⁠Doug Garber on LinkedIn: https://www.linkedin.com/in/doug-garber-42aa508  Sands Capital Links:Daniel Pilling on Linkedin: https://www.linkedin.com/in/daniel-pilling-14343116/Sands Capital: https://www.sandscapital.com/

  3. 25 Aug

    EP.48: Tipper X The Hedge Fund Analyst Who Became an FBI Informant

    Tom Hardin, formerly known as “Tipper X,” helped the FBI unravel one of the largest insider trading investigations in hedge fund history. The FBI flipped him, convinced him to wear a wire that built more than 20 cases. The hero of the story was Tom’s wife, who stood by him the entire time, allowing him to survive the intense emotional weight. In this episode, Tom walks through how he crossed the line, how easy it was to rationalize small trades as harmless, and how a handful of decisions ultimately destroyed his career. He explains what happened when the FBI approached him on the street, what it was like wearing a wire for two years, and why the $46,000 he made from four trades ended up being the price of his career.  We also discuss the practical lessons investors should take from his story: why who you surround yourself with is the most important decision of your career, why compliance should be treated as a career protector, and how being in a pressured performance situation can change how good people act.  Tom is now the author of Wired on Wall Street "I blew up my career for $46,000."  "Cheating is a choice." “You have to think about who you're surrounding yourself with.”  “If you're even that close to the line, you have to have a conversation with compliance.”  *Not investment or legal advice. Topics: Insider Trading, Tipper X, Hedge Funds, FBI, MNPI, Compliance,Securities Fraud, Risk Management, Investment Research, Wall Street    [00:00:00] Introduction [00:00:30] Tom Hardin’s history as Tipper X and role in the FBI insider trading investigation [00:01:51] The FBI confronts Tom about four trades [00:04:36] Why Tom advises contacting a lawyer before speaking to law enforcement [00:05:03] How fund pressure began shifting Tom’s decision-making [00:10:52] Receiving an acquisition tip and deciding whether to act [00:11:10] Crossing the line by passing the tip to another investor [00:13:17] The need, opportunity, and rationalization behind Tom’s trade [00:14:53] How his boss’s response reinforced Tom’s rationalization [00:16:42] How information-sharing escalated into a $15,000 payoff [00:18:57] Discovering others had already cooperated with law enforcement [00:21:41] Wearing a wire without a lawyer or cooperation agreement [00:24:24] Drawing a line with the FBI and being exposed as Tipper X [00:25:46] How cooperation affected sentencing and Tom’s felony convictions [00:27:58] The line between cooperation and entrapment as an informant [00:31:51] Telling his wife, panic attacks, and her support during the investigation [00:36:03] How running gave Tom structure after his career ended [00:37:03] Insider trading: material, non-public information and breach of duty [00:39:42] Compliance questions around using LLMs in investment research [00:40:38] Why research notes matter when trades are questioned later [00:42:29] Risks from an investor’s research and outside relationships [00:44:05] Expert networks and risks around political intelligence firms [00:46:53] Risks for public company board members with material information [00:47:41] Congressional stock trading and proposed restrictions [00:50:21] The lasting effects of a felony conviction and federal expungement [00:53:33] Why Tom calls compliance the “chief career protector” 💡 This episode is powered by: Fiscal.AI: - Delivering Modern Financial Data Infrastructure AlphaSense: Request a Demo Pitch The PM Links: 📩 Subscribe to our Substack for research updates and new high-conviction episodes from top PMs, and our Job Board: ⁠https://pitchthepm.substack.com/⁠Doug Garber on LinkedIn: https://www.linkedin.com/in/doug-garber-42aa508  Tipper X Links:  Tom Hardin on LinkedIn: https://www.linkedin.com/in/tipperx  Tipper X: https://www.tipperx.com/  Wired On Wall Street Book: https://www.tipperx.com/book Tipper X on X: https://x.com/iamtipperx

  4. 20 Aug

    EP.47: Activist Investor Pushing for an Epic Turnaround at Eagle Bancorp ($EGBN)

    My former colleague and banking guru, James Abbott, is living his passion with the launch of Diligence Capital Management (DCM). DCM runs a concentrated, net-long financials strategy alongside a tighter-net long/short financials portfolio. James and his team bring more than 50 years of combined experience in financial services—and a deep understanding of how banks operate, where they underperform, and what it takes to improve them. In this episode, James explains why DCM became actively involved with Eagle Bancorp ($EGBN), how he identified an underperforming bank in need of change, and why he believes the market is still underestimating its earnings power. We also discuss lessons from the 2008 financial crisis and the collapse of Silicon Valley Bank, as well as why spending time inside a business can create an investing edge that is difficult to replicate from the outside. "My goal was to be a portfolio manager just like Peter Lynch."  "The market just doesn't really appreciate what's going on here."  "The deep homework concept... go deeper than anybody else does."  "The company should be earning about $6 a share."  Stocks: $EGBN, $ZION  Not Investment Advice.  ______________________________________________________________________ [00:00:00] Introduction to James Abbott and the Eagle Bancorp investment thesis  [00:02:14] How a Peter Lynch article inspired James Abbott’s investing career  [00:03:46] Early career experiences at SNL Financial and FBR  [00:05:44] Reflections on FBR’s research culture and working alongside Dan Ives  [00:07:03] Lessons from generating positive returns during the 2008 financial crisis  [00:08:07] Moving from the sell side to executive leadership at Zions Bancorporation  [00:09:17] Building a significant ownership stake in Zions through personal investment  [00:10:28] Founding Diligence Capital Management and launching the firm  [00:11:46] The impact of Silicon Valley Bank’s collapse and banking sector contagion  [00:13:43] How market narratives and deposit flows can pressure banks  [00:15:02] Diligence Capital Management’s portfolio construction and leverage approach  [00:16:22] Activist investing through special purpose vehicles and concentrated opportunities  [00:16:37] Why Eagle Bancorp became a high-conviction investment  [00:17:48] Assessing Eagle Bancorp’s earnings power and excess capital  [00:19:09] Concentration risk and the challenges facing Eagle Bancorp  [00:20:47] Commercial real estate exposure and concerns around stale loan-to-value metrics  [00:22:31] Insights into bank credit quality, appraisals, and regulatory oversight  [00:24:35] Recommendations to strengthen Eagle Bancorp’s board composition  [00:27:32] Office loan concentration and portfolio risk management  [00:29:57] The process of engaging management and advocating for change  [00:31:51] Corporate governance reforms and separating the chairman and CEO roles  [00:34:22] Historical governance challenges at Eagle Bancorp  [00:36:09] Proposed board additions and turnaround expertise  [00:37:14] The push for a three-year performance improvement plan  [00:38:48] Market reaction to credit loss reserves and the stock’s recovery  [00:40:27] Why Diligence Capital believed the market mispriced Eagle Bancorp  [00:41:14] The path to achieving $6 per share in earnings power  [00:42:20] Closing thoughts on activism, value creation, and the future of Eagle  ______________________________________________________________________ Pitch The PM Episode Links: Doug Garber on LinkedIn: https://www.linkedin.com/in/doug-garber-42aa508  📩 Subscribe to our Substack for research updates and new high-conviction episodes from top PMs, and our Job Board: ⁠https://pitchthepm.substack.com/⁠ James Abbott on LinkedIn: https://www.linkedin.com/in/james-r-abbott-investor   This episode is powered by: 💡Oxford Data Plan: Request a Demo 💡AlphaSense: Request a Demo

  5. 13 Aug

    EP.46 He Trained Bryce Young Before Anyone Knew the Name — Then Built the Fastest-Growing Independent Research Platform on Wall Street

    I met Tim Arthurs, the second week when I joined Millennium and knew he was an “A” player. He still has notes from every time he called me on a stock. He’s a process guy. And it has led to his success.  He founded Seaport Research Partners, which has become the fastest-growing independent equity research platform by attracting the top research analysts and empowering them with aligned incentives. Early in his career, he moonlighted as a QB coach for Heisman winner and #1 overall pick Bryce Young teaching him the importance of the right motion and process.   “What have I learned from some of my biggest failures is keep getting up. You're bendable, you're not breakable” "You can't be a big man at night and a little man in the morning" We cover: The Bryce Young story — a Craigslist posting, a dad who lied about his kid's age, and six months of tennis balls and candy wrappers before he ever touched a football. It starts with good habits The MiFID II unlock: how unbundling and vote/rate-card transparency exposed what individual analysts are actually worth — and made an eat-what-you-kill platform possible for the first time The brutal math of the sell side: ~3,500 published analysts in North America, and two-thirds of coverage is "watered-down, check-the-box" — subsidized by banking and syndicate How Seaport recruits the top 1% of the 1%: never a recruiter, 550+ interviews, ~40 offers, 30+ conversions — the clients feed the talent The reference-check questions that actually work: "When did they make you money?" and "What's a 60-minute meeting with them worth?" — asked across 20-30 buy-siders until the trend is undeniable The 3-step analyst checklist: investment judgment (best call, worst call, the consensus view you think is wrong), research edge (what do you produce that clients can't get elsewhere — and what's proprietary in the process), and client franchise (your top 15 advocates who raise their hand no matter what) The salesperson hierarchy: good salespeople are concierge, great ones sell outcomes — "we get paid to anticipate, not analyze" — and the cream of the crop sell feelings: becoming an extension of the client's investment process "You can't be a big man at night and a little man in the morning" Why analysts leave the bulge: "Why do I get comped down 10-15% a year when my franchise wasn't down?" — and what they control at Seaport: coverage, distribution, pricing, input and output The three-stage distribution model: ~400-500 readership, top-100 tactical, top-40 opt-in Proof of concept: #1 global market-share gainer at some of the biggest wallets on the planet, 3 → 30+ analysts in five years, and only one analyst ever lost The next five years: the best 45 analysts in the U.S., replicating the model in Europe and Asia, and filling the void the bulge brackets left Triathlons, 1,440 minutes a day, and the 5% you owe yourself — plus the cause closest to home: the Epilepsy Foundation of Chicago and his daughter Athena _______________________________________________________________ 💡 This episode is powered by Fiscal.AI - Delivering Modern Financial Data Infrastructure Pitch The PM Episode Links: Doug Garber on LinkedIn: https://www.linkedin.com/in/doug-garber-42aa508  📩 Subscribe to our Substack for research updates and new high-conviction episodes from top PMs, and our Job Board: ⁠https://pitchthepm.substack.com/⁠ Links: Tim Arthurs on LinkedIn: https://www.linkedin.com/in/timothy-arthurs-06b3179/ Seaport Research Partners: https://seaportrp.com/ Seaport Global: https://seaportglobal.com/ Chicago Epilepsy Foundation: https://epilepsychicago.org/

  6. 11 Aug

    EP.45 Palantir ($PLTR): Is the Leading Growth Rate Sustainable? With Gil Luria, Head of Technology Research at D. A. Davidson

    Gil Luria and I dig into the bull case after another blockbuster quarter with 93% YoY growth. The reason Palantir wins is their head start on building an enterprise-wide ontology, unconventional usage of forward-deployed engineers in their SaaS model, and customer-aligned, outcome-based pricing. We debate $PLTR’s valuation, future growth trajectory, and AI-driven software budget crowd-out. “Retail investors figured it out first, bid it up all the way to $200. Institutional investors were always caught a step behind, including most of the sell side.” “The bull case is that the stocks’ valuation is now, 50x forward cash flow, not $200, 2% yield, and they're growing 90%, 93% up from 85% last quarter”  “They get to cherry pick customer, deliver results, and win. (8:24) That's when we learned over the last year.” “This is the best software company in the world. Maybe the best company in the world.” Stocks mentioned: $PLTR, $AI, $IBM, $MSFT, $NVDA, $SNOW, $DDOG, $CRWD, $SHOP *Not Investment Advice. Disclosure: The author has a short position in PLTR as of the episode recording; that may change at any time.  ______________________________________________________________________ Highlights: (1:26) Palantir accelerates — 93% U.S. commercial growth and strong government demand. (2:18) How Gil went from valuation skeptic to calling Palantir one of the world’s best companies. (5:13) What makes Palantir different: forward deployed engineers, ontology, AI and outcome-based pricing. (8:26) How Palantir delivers customized solutions at scale. (9:06) Why its engineering talent and brand are hard to replicate. (10:34) Ontology explained — mapping company data to how the business works. (13:29) Palantir’s post-9/11 origin story and original problem. (15:23) A 157% net retention rate and expansion within large customers. (16:42) Why Palantir’s chief revenue officer came from a legal background. (17:48) Gil’s valuation framework: Palantir deserves a premium to software peers. (19:42) Why Palantir customers may be seeing unusually strong AI returns. (21:43) Enterprise AI shifts from structured to probabilistic unstructured data. (23:46) How AI spending is crowding out other technology budgets. (26:48) From GPU hours to tokens to cost per task — AI economics move toward labor. (29:10) Why AI-driven productivity could lead companies to hire more people. (30:29) How AI compressed Gil’s research workflow from weeks to near real time. (35:06) Gil’s AI stack and Microsoft as D.A. Davidson’s enterprise control plane. (37:41) Are companies handing proprietary advantage to frontier AI models? (38:38) Palantir’s sovereignty pitch and risks of relying on one frontier model. (42:45) Why Palantir prefers model flexibility and NVIDIA’s Nemotron models. (43:52) NVIDIA’s strategy: coordinate the AI ecosystem, not just sell chips. (46:08) The Palantir bear case — extraordinary growth eventually decelerates. (48:02) Why slower growth could still support a larger future cash-flow base. (50:35) Why Gil’s Palantir estimates remain close to consensus despite his bullish view. (52:14) The institutional-investor problem: limited revenue disclosure. (53:49) Gil’s belief in Palantir’s mission. (54:04) Doug summarizes the bull and bear cases: ontology, engineering, valuation, and deceleration. ______________________________________________________________________ 💡 This episode is powered by AlphaSense. Use the link here for Complimentary access — https://www.alpha-sense.com/Pitch/💡 Fiscal.AI - Delivering Modern Financial Data Infrastructure Pitch The PM Links: 📩 Subscribe to our Substack for research updates and new high-conviction episodes from top PMs, and our Job Board: ⁠https://pitchthepm.substack.com/⁠Doug Garber on LinkedIn for daily market color: : https://www.linkedin.com/in/doug-garber-42aa508  Gil Luria Links:DA Davidson: https://www.dadavidson.com/ Gil Luria on LinkedIn: https://www.linkedin.com/in/gil-luria-79347a2/ Gil Luria on X: https://x.com/gilluria

  7. 6 Aug

    EP. 44 - She Quit at 29 With No Code, No Co-Founder, No Funding – Now Hudson Labs Is Finance AI that has a “No Hallucination Guarantee”

    She Quit at 29 With No Code, No Co-Founder, No Funding – Now Hudson Labs Is Finance AI that has a “No Hallucination Guarantee” Kris Bennatti (@)  CEO Hudson Labs (Toronto), a former forensic-accounting data scientist who built the first LLM for finance, back in 2019 before anyone knew what to make of it. Her co-founder/CTO Suhas Pai literally wrote the book – O'Reilly's "Designing Large Language Model Applications." "If you try to pull multi-period KPIs beyond four quarters with a generalist tool, you'll get one wrong number 30% of the time." We cover: The leap: quitting a great job at 29 with no funding, no co-founder, and not one line of code written  "those choices are just a reflection of poor risk assessment capabilities" The first hard lesson: the academic papers claiming AI could predict fraud were poisoned by target leakage, the training data contained the outcome. The product she quit her job to build didn't work, and she rebuilt from scratch The forensic risk score: 70+ means a one-in-three chance of an SEC enforcement action within three years and 3x the likelihood of a securities lawsuit  used by investors, D&O insurers pricing risk, and plaintiff-side class-action firms. "We specialize in selling to the enemy." Why generalist LLMs hallucinate on financial numbers: effective context length vs the advertised window, the two-to-three-earnings-calls attention limit, and why hallucination is really LLM memory bleeding into real data The Hudson Labs answer: AI-specific pre-processing of every filing, transcript, and presentation retrieve the whole table, the units, the currency, consolidated-vs-segment and a no-hallucination guarantee, the first of its kind Tone as a screen: find the most stressed-out CEOs, the most confident CFOs, track deflection on analyst Q&A over time  impossible unless tone is stored in the embeddings The soft-guidance problem: why "capex is now expected to be…" slips past generalist AI, and the pathways built to never miss a guidance cue The server useful-life screen: every hyperscaler raising estimates in a follow-the-leader wave and Amazon as the only one to cut The cost story nobody's pricing: a 500-company AI-ecosystem deep dive that cost $200 on Hudson Labs vs ~$13,000 on a frontier-model API at lower accuracy  and why cost efficiency becomes the tailwind as subsidies fade The business today: ~100 hedge fund clients plus Fortune 100s, insurers, and law firms and a new $100/month tier Highlights:  (1:13) Quitting at 29 with nothing but the problem (5:34) The target-leakage discovery — the papers were wrong (9:46) Suhas Pai — the co-founder who wrote the book (13:10) How Hudson Labs differs from the AI-startup wave (15:30) Why generalist LLMs get numbers wrong — context and attention (23:24) The worst strategic decision — and pivoting when short sellers shrank (28:21) Demo: KPIs with verbatim call commentary, no hallucinations (35:30) The infrastructure behind the guarantee (39:34) Tracking Waymo vs Uber when the stats aren't standard (46:39) The forensic risk score — and Meta's rising off-balance-sheet risk (52:00) The server useful-life wave — everyone up, Amazon down (55:14) $200 vs $13,000 — the deep-dive cost math (57:00) The next three years and the new $100/month tier ______________________________________________________________________ 💡 This episode is powered by: Fiscal.AI: Contact Sales Pitch The PM Links: 📩 Subscribe to our Substack for research updates and new high-conviction episodes from top PMs, and our Job Board: ⁠https://pitchthepm.substack.com/⁠Doug Garber on LinkedIn for daily market color: : https://www.linkedin.com/in/doug-garber-42aa508  Hudson Labs Links:Kris Bennatti: https://www.linkedin.com/in/kbennatti/  Hudson Labs: https://www.hudson-labs.com/

  8. 30 Jul

    EP.43 - SpaceX ($SPCX) Irrational Exuberance? Space Winner or Street 50% Too High

    "Our numbers are not even half of consensus. Treat the syndicate's number as an extremely optimistic bull case." "We think we're already very optimistic—but consensus is even more optimistic." "Launch is what makes 100% of the value of SpaceX." "Frontier AI is building very high barriers to entry." "Everybody wants to be part of the SpaceX story." Pierre Ferragu, Head of Tech Infrastructure at New Street Research, joins the show to break down SPCX’s sum-of-the-parts valuation and the key debates in the stock. We dig into: Why Starlink has a structural cost advantage over traditional broadband. The tell is that Starlink is already sold out in places: raising prices in capacity-limited markets while adding 0.5-1M subs a month — which is why the V3/Starship ramp is now the gating factor. The Starship launch being the next catalyst. The model needs ~1 Starship launch a week; New Street runs ~1 year behind Elon's timeline — a reminder that Musk's targets have a "world-class track record of being late but delivered" The xAI valuation framework: a ~$575B base value from a $750B-$1T 2030 market at ~15% share (on Anthropic/OpenAI's ~4.6x 2030 revenue) — and why it's a balanced oligopoly, not winner-take-all, so no one gets to run away with it. The spot-vs-planned compute arb: ~$50B/GW (the $15B / 0.3GW Anthropic deal) vs CoreWeave's ~$12B/GW — and why that premium may not last. The setup that should keep you honest: consensus was built on Elon-optimism to sell the deal; the stock will trade quarter-to-quarter on "where there's light" (Starlink subs, Starship launches), through 6-12 volatile months of lockup unwinds and index inclusion.  The Debate: Overly optimistic earnings revisions vs a cost advantage in the space frontier led by the great entrepreneur of our time, Elon Musk This episode was originally a Pitch The PM webinar sponsored by Alpha Sense on June 22nd. Get free access to all of our webinars on our substack Stocks: $SPCX, $TSLA Topics: SpaceX, Starlink, Starship, xAI, Frontier AI, Space Economy, Satellite Internet, Launch Economics, Artificial Intelligence, Infrastructure Investing *Not Investment Advice _____________________________________________________________ [00:00:00] Introduction to Pierre Ferragu, New Street Research, and why the firm is uniquely positioned to analyze SpaceX.[00:03:59] How New Street frames the SpaceX investment thesis for institutional investors.[00:06:32] SpaceX sum-of-the-parts valuation: Starlink, Direct-to-Cell, Launch, and xAI.[00:10:05] Why Starlink has a major cost advantage over traditional broadband.[00:15:49] Starlink pricing, subscriber growth, and global expansion.[00:20:23] Pierre’s firsthand experience using Starlink.[00:23:10] Valuing Starlink and its long-term free cash flow potential.[00:27:36] Why Starship is the most important catalyst for SpaceX.[00:37:22] How SpaceX disrupted the launch industry.[00:44:25] Pierre’s valuation framework for xAI and Frontier AI.[00:53:56] Meta, open-source models, and Chinese AI companies.[00:57:19] Why xAI can command premium pricing for compute capacity.[00:59:36] Pierre’s variant view versus Wall Street consensus.[01:01:04] What investors should watch after the IPO.[01:02:45] Pierre’s outlook for SpaceX shares. _____________________________________________________________ 💡 This episode is powered by: AlphaSense: Request a Demo Pitch The PM Links: 📩 Subscribe to our Substack for research updates and new high-conviction episodes from top PMs, and our Job Board: ⁠https://pitchthepm.substack.com/⁠ Follow Doug Garber on LinkedIn for daily market color: https://www.linkedin.com/in/doug-garber-42aa508

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Pitch The PM is the professional investor’s podcast where host Doug Garber dives deep into high-conviction stock ideas using his Variant View Investment Checklist. It’s a real-time look at the research process, blending lessons from Buffett, Munger, and Lynch with modern AI tools. Join Doug, ex-Citadel top analyst and Millennium Sr PM, as he works through his Buffett-inspired 20-slot punch card. Learn, laugh, and sharpen your edge.

Information

  • Creator
    PitchThePM
  • Years Active
    2025 - 2026
  • Episodes
    49
  • Rating
    Clean
  • Copyright
    © PitchThePM
  • Show Website
    Pitch The PM