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PitchThePM

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.

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  • 22 episodes
  • weekly
  • Avg 48 min
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  • #39
    Thursday · 37 min

    EP.52 Why Point72 Wins–20 Years Next to Steve Cohen with Chandler Bocklage, Head of Business Development

    Chandler Bocklage spent nearly two decades working alongside Steve Cohen, managing a portfolio before leading Business Development at Point72. In this episode, we discuss what separates good investors from great ones, how Point72 develops portfolio managers, why intellectual curiosity matters more than almost anything else, and how AI is reshaping the future of fundamental investing. If you've ever wondered what it really takes to become a successful PM, this is one of the most candid conversations from inside the walls of legendary investment firm Point72. “Alpha decay has been compressing and compressing. There are more and more people chasing the same alphas.” “You have to have different duration, you have to have different catalyst paths, you have to have different thought processes because” “Honestly, I think that's what it really comes down to. The sacrifices…” "We don't think AI replaces analysts or PMs." Highlights: (01:31) The intellectual curiosity that defines Steve Cohen (04:24) The unspoken sacrifices behind being great at this job (04:56) The Kobe, Jordan, and Brady comparison to elite investing (07:48) The origins of LaunchPoint and building a real development path (10:24) Why AI won't replace analysts or portfolio managers (14:41) What actually makes an investment process repeatable (29:47) The talent war, mega-guarantees, and buy versus build (33:12) The biggest mistake of his career — and what it taught him (35:18) Why Steve Cohen stepped back from trading to build the firm Topics: Point72, Steve Cohen, Portfolio Management, AI, Fundamental Investing, Risk Management, Analyst Development ______________________________________________________________________ 💡 This episode is presented by Carbon Arc–The Infrastructure for the AI Economy. 30 Days free with code PTPM30 Research Sponsors:Oxford Data Plan–The Home of Alternative Data. Ping Makay Redd for a trial. AlphaSense–Decision Grade AI. Free trial at https://www.alpha-sense.com/pitch/ Fiscal.AI–Delivering Modern Financial Data Infrastructure. Use code PITCH for 15% off______________________________________________________________________ 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://linkedin.com/in/doug-garber-42aa508 Point72 Links:Chandler Bocklage on LinkedIn: https://www.linkedin.com/in/chandler-bocklage-476518a6/Point 72: https://point72.com/ ______________________________________________________________________

  • S1 · E36
    September 18 · 50 min

    DoorDash’s ($DASH) Growth Upside–A High-Conviction Investment with TimeSquare’s Consumer PM Ed Salib

    In 2001, Ed Salib walked into TimesSquare Capital Management as the firm's first intern. Twenty-five years later, he's co-PM of the TimesSquare Quality Mid Cap Growth ETF ($TSCM). So what does a 25-year fundamental investor do when one of the market's most debated stocks goes on sale? Ed passed on DoorDash's 2021 IPO, kept it in his research “bullpen,” and bought the 20% sell-off on conservative early-2025 guidance. He got a second bite when the stock fell from the mid-200s to ~$140 this spring on fears it could be "vibe-coded away." In the episode, we dig into why scale and density are the moat Grubhub never built, how DashPass and grocery are lifting order values, why Ed forecasts mid-20s growth through decade-end vs. the Street's high teens, and why the end of an internal investment cycle could surprise investors to the upside on margins. "They gave initial guidance in early 2025 for EBITDA that disappointed and the stock sold off twenty percent. That was our entry point." “We think they can go low to mid twenties versus the Street more like high teens over the next several years till the end of the decade.” “I'm looking at the real-time Oxford data. It has August growing 31%...the Street’s at 21% for the quarter.” We cover: ● TimesSquare's consumer filter: durable, needs-based demand, and why "fashion was a four-letter word" ● The three-sided marketplace, two-thirds US restaurant share, and why Grubhub lost the suburbs ● DashPass, grocery and DoubleDash: how grocery lifts order value and driver economics ● Why Ed passed on the IPO, what changed in 2024, and how he sized the 2025 entry ● The variant view: low-to-mid-20s growth vs. the Street's high teens ● The bear case: cost to grow, Instacart, Uber, PE-backed competition, and Deliveroo/ERP ● How Ed sets base, bull and bear price targets ● How TimesSquare uses Claude, MCPs and AlphaSense in research Highlights: (0:48) Ed's 25 years at TimesSquare, from first intern to co-PM (3:16) What TimesSquare looks for in a consumer stock (8:08) Why DoorDash is compelling: scale, founder-led, and capital allocation (11:06) Why the business exists and where Grubhub went wrong (13:20) DashPass, 45M members, and grocery (16:09) Carbon Arc data: grocery order values rising from ~$51 to ~$63 (18:11) Robotaxis and drones: bull-case upside (20:44) Passing on the 2021 IPO and what changed in 2024 (23:50) The 2025 guidance sell-off: "That was our entry point" (25:36) The 2026 AI sell-off and "vibe-coded away" bear case (28:55) Low-to-mid-20s growth vs. the Street's high teens (30:52) Incremental margins, ERP, and EBITDA revisions (32:23) Deliveroo integration and the 2026 investment year (35:25) ODP shows August accelerating to +31% YoY (37:20) DoorDash beyond restaurants (40:01) Valuation at ~22x NTM EV/EBITDA and the bear case (45:29) Economics with merchants and drivers (49:27) Base, bull and bear price targets (52:05) "We're a Claude shop": AI in research (54:47) Security and ring-fencing research 💡 This episode is presented by Oxford Data Plan–The Home of Alternative Data. Ping Makay Redd for a trial (professional investors only) — https://www.linkedin.com/in/makay-redd-122a4364/ Research Sponsors: AlphaSense–Decision Grade AI. Complimentary trial at https://www.alpha-sense.com/pitch/ Carbon Arc–The Infrastructure for the AI Economy. 30 Days free with code PTPM30 Fiscal.AI–Delivering Modern Financial Data Infrastructure. Use code PITCH for 15% discount Pitch The PM Links: 📩 Subscribe to our Substack for research updates and new high-conviction episodes from top PMs, and our Job Board: https://pitchthepm.substack.com Doug Garber on LinkedIn for daily market color: https://linkedin.com/in/doug-garber-42aa508 TimesSquare Links: TimesSquare Capital Management: https://www.tscmllc.com/ TimesSquare Quality Mid Cap Growth ETF ($TSCM): https://tscmetfs.com/funds/tscm/ Stocks mentioned: $DASH Not Investment Advice.

  • #50
    September 10 · 54 min

    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 Infrastructure https://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/

  • #49
    September 2 · 1 hr 4 min

    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/

  • #48
    August 25 · 56 min

    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

  • August 20 · 43 min

    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

  • August 13 · 34 min

    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/

  • #45
    August 11 · 56 min

    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

  • #44
    August 6 · 59 min

    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/

  • S1 · E43
    July 30 · 1 hr 6 min

    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

  • July 23 · 55 min

    EP. 42: Building Data-as-a-Service using AI tokens–Making Decisions on Complete Gut!

    "Our data is powering the infrastructure of this massive new market." "Building Data-as-a-Service is a very, very hard business." "difficult problems have big rewards" "You're making decisions on complete gut." Braden Dennis is the true definition of an entrepreneur. He started a podcast in his college dorm room and now runs an industry leading Fintech. Fiscal.ai has pivoted three times since inception and is now focused on building the latest generation financial data company using delivery speed and rapid product iteration as its competitive advantage. Companies mentioned: Google Finance ($GOOGL), Claude, OpenAI, Bloomberg, Fiscal AI, Perplexity. Thank you to Fiscal.AI, our sponsor of the Wall Street Entrepreneur series! ______________________________________________________________________ Highlights [00:00:18] Introduction to Braden Dennis and Fiscal AI [00:01:44] Braden Dennis's investing background and early podcasting journey [00:02:58] Influential investing books and lessons that shaped his entrepreneurial approach [00:05:27] Overview of Fiscal AI's financial data business and competitive advantages [00:07:29] Origins of Stratosphere and the launch of FinChat [00:08:39] FinChat's viral growth following the release of large language models [00:11:09] Raising seed capital and demonstrating early startup traction [00:11:27] Product-market fit and the importance of rapid iteration [00:13:22] Advice for founders on fundraising and seed-stage milestones [00:15:26] Why the company shifted from a retail investing platform toward data infrastructure [00:16:07] Building proprietary financial datasets and owning the underlying content [00:19:11] Transitioning from software subscriptions to B2B data feeds [00:20:00] Startup decision-making, uncertainty, and operating on imperfect information [00:21:59] Startup moats, competition, and scaling from zero to one [00:24:09] Customer retention, activation, and key business metrics [00:25:52] AI infrastructure, token usage, and building data products at scale [00:28:32] Product roadmap, data coverage expansion, and competitive positioning [00:30:18] MCP integrations and delivering financial data directly into AI workflows [00:31:36] Global data coverage, ownership data, transcripts, and company KPIs [00:34:22] Total addressable market for financial data and long-term revenue goals [00:36:40] Scaling from $10 million to $50 million in annual recurring revenue [00:38:41] Creating a news product focused on signal rather than noise [00:42:36] Managing emotions and maintaining perspective as a founder [00:43:23] Leadership lessons and the risks of impulsive decision-making [00:44:18] Demonstration of Fiscal AI's terminal, API, and investor tools [00:46:37] AI-powered research workflows using Claude, Codex, and MCP integrations [00:49:27] Data ownership, model training, and the value of accurate financial information [00:53:00] Handling adjusted financial metrics and analyst workflows [00:53:58] Building custom investor dashboards and the future of AI-assisted research ______________________________________________________________________ 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 Fiscal.AI Links: Braden Dennis on LinkedIn: https://www.linkedin.com/in/braden-dennis-881a88b0/ Fiscal AI - https://fiscal.ai/

  • July 20 · 1 hr 1 min

    EP.41: Student Stock Competition Winners: Is the Magic Show Over? $HAS Short Pitch

    "When I see short interest go up into the right... I want to dig deeper." "We came in as a long at first... then we followed the evidence to get to the short side." "Magic has been the crown jewel of the company—but we think expectations have gotten too high." [Using Carbon Arc data] “average weekly users on the app through quarter to date to q2 it's down 11 percent” "You have to be intellectually honest. You can't just ignore evidence because it doesn't support your thesis." Glenn and Vito won both the Fordham and Notre Dame Stock Pitch Competitions with a contrarian short thesis on Hasbro ($HAS). What began as a long idea quickly turned into a short after they dug into Magic: The Gathering, channel checks, local game store surveys, player sentiment, and Wizards of the Coast's product strategy. In this episode, they walk through the full research process behind their pitch, discuss why they believe Magic's recent growth is unsustainable, and explain how primary research, financial modeling, channel checks, and alternative data on Carbon Arc helped shape their view. Stocks: $HAS *Not Investment Advice Disclosure: I have a short position. That may change at anytime. ______________________________________________________________________ [01:00:00] Introduction to Glenn Lee and Vito, winners of the Fordham and Notre Dame Stock Pitch Competitions, and their Hasbro short thesis. [01:03:03] How the investment idea evolved from a long thesis into a short after deeper financial analysis. [01:05:54] The two pillars of the Hasbro short thesis: slowing Magic: The Gathering demand and weakness in consumer products. [01:09:18] Doug explains how to think about short interest, positioning, and identifying crowded trades. [01:11:39] Breaking down Hasbro's business segments and why Wizards of the Coast drives nearly all of the company's profitability. [01:15:41] Why Magic: The Gathering has maintained its competitive advantage for more than 30 years. [01:21:43] The Universes Beyond strategy and why the team believes it changes Magic's long-term growth profile. [01:23:04] Hasbro's recent growth, management expectations, and why the students believe Wall Street is too optimistic. [01:30:15] Doug's framework for continuously testing an investment thesis and remaining intellectually honest as new evidence emerges. [01:34:11] The research process behind forecasting Magic: The Gathering demand using channel checks and industry expertise. [01:36:35] How product releases and aggressive pricing have accelerated Magic's recent growth. [01:38:21] Survey results, player backlash, and the debate around the Universes Beyond product strategy. [01:43:19] Channel checks with local game stores and what retailer ordering patterns reveal about future demand. [01:52:26] Using secondary market pricing to measure player demand and forecast future Magic sales. [01:56:14] The key bull case for Hasbro, why attracting new players may not be enough, and the team's concluding thoughts on the investment thesis. ______________________________________________________________________ 💡 This episode is powered by: Carbon Arc: 30 Days Free with Code PITCHTHEPM30 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

  • July 15 · 54 min

    EP.40: The Next Phase of the Oil Cycle: Why Refiners Win

    “These [oil] cycles, and we can get into it, they move up in three waves. They go doubt, pullback, optimism, a pullback, and then parabolic euphoria.” “The well count is starting to bottom out, and even as of the latest Texas Railroad Commission data that was just updating for this call, it looks like that's bottoming out too.” “So I think the best ones that is now front and center is obviously the refiners, and I still think that there's a lot left in the tank.” "If you go back and look at the mega tech capex... there is not one single metric around meeting a capital budget." Robert Connors, the author of Crude Chronicles and advisor to funds that manage over $1 trillion such as T. Rowe Price walks us through his bullish oil cycle call in great detail with all the supporting charts. The logic is simple: well productivity is declining and the marginal cost of production is increasing. Therefore, oil prices are on the rise. Drawing on more than a century of industry data gathered by hand at the Library of Congress, Robert explains how oil cycles are driven not just by supply and demand, but by long-term productivity trends, capital allocation, and marginal production costs. Stocks mentioned: PSX, MPC, VLO, CVX, XOM, BP, TTW, RIG, NE, DO, VAL ______________________________________________________________________ [00:00:00] Highlights [00:00:26] Introduction to Robert Connors and his long-cycle approach to energy research. [00:02:10] How the Iran conflict fits into Robert's three-wave commodity cycle framework. [00:04:28] Why well productivity—not traditional supply and demand forecasts—drives long-term oil cycles. [00:09:13] Evidence that U.S. shale productivity growth is slowing and what that means for future oil prices. [00:11:38] Comparing productivity trends across Bakken, Permian E&Ps, and integrated oil companies. [00:14:21] Where future global oil supply growth could come from beyond the Permian. [00:18:15] Understanding marginal production costs and why they establish the long-term floor for oil prices. [00:20:44] Robert's framework for estimating a sustainable oil price range despite geopolitical volatility. [00:24:35] Why refining margins are driven by secondary processing capacity rather than simple utilization rates. [00:29:50] Global refining capacity outlook and why Robert remains bullish on refiners. [00:32:54] Similarities between today's AI infrastructure spending and previous shale investment cycles. [00:36:41] Productivity cycles, technology investment, and the relationship between energy and growth stocks. [00:39:54] Robert's preferred investment opportunities, including refiners, integrated majors, and offshore drillers. [00:44:47] Why offshore drilling may be entering a favorable cycle with limited new rig supply. [00:51:24] How executive incentive structures influence capital allocation and shareholder returns in the offshore sector. [00:52:53] Where listeners can follow Robert Connors and Crude Chronicles. ______________________________________________________________________ 💡 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/⁠Doug Garber on LinkedIn: https://www.linkedin.com/in/doug-garber-42aa508 Crude Chronicles Links: Robert Connors on LinkedIn: https://www.linkedin.com/in/robert-connors-cfa-cpa-oilinvestor/ The Crude Chronicles: https://thecrudechronicles.substack.com/

  • July 9 · 1 hr 2 min

    EP.39: Bull or Bear debate on META’s AI Capex? With Avory’s CIO Sean Emory

    Sean Emory, CIO and Founder of Avory & Co., is one of my go-to investors when I want to pressure-test an investment thesis. While I tend to focus on earnings revisions and the Variant View checklist , Sean goes deep on products, competitive positioning, and invests where the world is heading. In this episode, we debate one of the biggest questions in tech investing today: Is Meta overspending on AI, or is Zuckerberg making the right long-term bet? We break down if Meta's AI strategy is working and what is driving the stock? "Don't bet against Zuckerberg." "They have the biggest distribution platform in the world." "If you don't own your infrastructure, you run a lot of risk." "Distribution is arguably the most important strategic place to be here." "The burden on your brain—the cognitive load—amplifies." Stocks: $META, $NVDA, $AMD, $GOOGL, $MSFT Thank you to our episode sponsors Oxford Data Plan and Alpha Sense. *Not Investment Advice ______________________________________________________________________ [00:00:00] Introduction to Sean Emory, Avory & Co., and the firm's investment approach. [00:01:24] Building Avory around disciplined research and long-term investing. [00:03:28] Why Meta has remained a core holding over the past decade. [00:04:34] Mark Zuckerberg's leadership and Meta's long-term execution. [00:09:00] Examining Meta's capital expenditure strategy and valuation. [00:11:15] Why Meta's distribution advantage supports its AI investments. [00:15:04] Sean's outlook for hyperscaler capital spending and infrastructure investment. [00:16:42] Why owning AI infrastructure matters for large technology platforms. [00:21:57] Discussion around potential equity financing and investor concerns. [00:23:40] Balancing near-term free cash flow with long-term investment returns. [00:26:48] What catalysts could change investor sentiment toward Meta. [00:32:39] Meta's AI model development, product strategy, and competitive positioning. [00:35:01] The AI tools Sean uses throughout his investment process. [00:37:28] Using AI workflows, automation, and productivity systems within an investment firm. [00:43:58] Portfolio sizing and valuation discipline for Meta. [00:48:24] Whether investors should support Meta's aggressive AI investment strategy. [00:52:10] Long-term expectations for Meta's free cash flow as capital spending stabilizes. [00:57:15] Additional upside from Meta's AI partnerships and infrastructure investments. 💡 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 Avory & Co Links: Sean Emory on LinkedIn: https://www.linkedin.com/in/seanemoryavory Avory & Co https://www.avory.xyz/

  • S1 · E38
    June 30 · 43 min

    EP038: AI's Next Surprise Inflection–Construction Rentals? With Jarrett Harris from Iron Advisor Insights

    Jarrett Harris, from Iron Advisor Insights was my go to person for industrial channel checks when I was at Citadel and Millennium. He’s from Peoria, IL, the original HQ of Caterpillar ($CAT) and spends his days talking to heavy equipment dealers. He is now part of Iron Connect, a dealer wholesale network with proprietary data that gives me an edge on when the heavy equipment cycles are inflecting. After catching-up with Jarrett in this episode, it is likely we are seeing early signs of a price inflection for rental equipment potentially impacting: $URI, $EQPT, $SUNB, $HRI "The data center build out is reshaping everything." “Supply versus demand is normalized and is now edging toward scarcity rather than abundance." "We've started to get more indications that rental rates are going higher." "We're starting to hear more people in the used equipment market that are hoarding equipment." “north of 80% of the equipment on their site was selling within two weeks. If I go back to September of ‘25, it was about 30%.” Stocks:$URI, $CAT, $EQPT, $SUNB, $HRI *Not Investment Advice ______________________________________________________________________ [00:00:00] Introduction and highlights. [00:00:25] Jarrett Harris introduces Iron Advisor Insights and its field research approach. [00:01:44] Building a research business focused exclusively on heavy equipment and industrial machinery. [00:03:48] How dealer, contractor, supplier, and equipment data are combined to identify industry trends. [00:04:55] The machinery manufacturers and rental companies covered by Iron Advisor Insights. [00:05:39] Why Caterpillar and equipment rentals are at the center of investor conversations. [00:07:04] How AI data centers are changing construction demand and equipment utilization. [00:09:39] Equipment supply, lead times, pricing, and the shift from abundance toward scarcity. [00:12:09] Caterpillar's growing role in powering AI data centers. [00:15:09] Why Caterpillar's dealer network creates a competitive advantage. [00:17:19] Used equipment markets, dealer inventory, and signs of tightening supply. [00:20:14] Rental rate trends and early indications of improving pricing power. [00:21:55] How dynamic pricing is changing the equipment rental industry. [00:24:09] EquipmentShare's impact on competition and rental pricing strategies. [00:26:44] Why rental companies may be approaching an important pricing inflection point. [00:28:38] How large data center projects are influencing equipment demand and contractor behavior. [00:30:12] Geographic expansion of data center construction across North America. [00:31:51] Comparing pricing between new and used construction equipment. [00:33:07] Dealer inventory strategies and growing conviction around future equipment demand. [00:35:33] Investor sentiment toward AI-driven construction versus broader economic activity. [00:36:17] Infrastructure spending and improving conditions in construction markets. [00:39:50] The long-term growth outlook for equipment rentals and OEM-backed rental fleets. ______________________________________________________________________ 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/⁠ Iron Advisor Insights Links:Jarret Harris on LinkedIn: https://www.linkedin.com/in/jarrettharris/Iron Advisors Insights: https://ironconnect.com/

  • S1 · E37
    June 26 · 36 min

    EP037: SNOW: 1st Inning on AI Cloud Data Winner! With Sonu Chawla, PM of $TSCM

    Part 2 of the interview with Sonu Chawla, Co-Portfolio Manager at TimesSquare Capital Management, about one of her team's highest-conviction investment ideas in enterprise AI. Sonu explains why Snowflake sits at the center of the AI data ecosystem, how her team developed conviction to increase its position during a sharp software selloff, and why they believe enterprise AI adoption remains in its earliest stages. The conversation examines primary research, expert networks, valuation discipline, and the role of AI tools in investment research, highlighting how experienced analysts combine domain expertise with fundamental research to identify long-term growth opportunities before they become widely recognized. ETF: TSCMTickers: SNOW *Not Investment Advice. ______________________________________________________________________ [00:00:00] Introduction and highlights to part 2 of this interview with Sonu Chawla. [00:02:20] Snowflake's business model and why it is foundational to enterprise AI infrastructure. [00:05:50] Why enterprise AI adoption is still in its earliest innings. [00:08:05] How Snowflake differentiates itself from hyperscale cloud providers and competing data platforms. [00:15:06] The investment thesis behind increasing the firm's Snowflake position during the software selloff. [00:17:49] Why Cortex Code (CoCo) created a variant perception and wasn't reflected in company guidance. [00:18:16] Customer adoption data, channel checks, and primary research that strengthened conviction. [00:22:17] Using LinkedIn, expert calls, and management commentary as part of the research process. [00:22:17] Balancing valuation discipline with high-growth investment opportunities. [00:26:53] Why discounted cash flow analysis and free cash flow remain central to investment decisions. [00:29:48] Comparing Snowflake's growth profile with Palantir and the broader enterprise AI landscape. [00:31:20] How Times Square uses AI tools to accelerate investment research and improve productivity. [00:33:20] Building an internal AI-enabled research ecosystem and connecting proprietary data sources. ______________________________________________________________________ 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/⁠ TimesSquare Links:Sonu Chawla on LinkedIn: https://www.linkedin.com/in/sonu-chawla-cfa-0093612/TimesSquare: https://tscmllc.com/ 💡 This episode is powered by AlphaSense. Use the link here for Complimentary access — https://www.alpha-sense.com/PTPM/

  • S1 · E36
    June 24 · 30 min

    EP036: TimesSquare ($TSCM): The Woman in the Arena with Co-PM Sonu Chawla

    Against all odds, Sonu has shined at every step of her career. From getting into the Indian Institute of Technology to becoming a Co-PM at TimesSquare Capital Management. We get into what it's like to stand in the Wall Street arena everyday after proving the “nah-sayers” wrong. And why she invests in mid-cap equities at TimesSquare Capital Management and the benefits of being early to investing in a transformational, high-growth company. “It was a master class in trying to adapt to a world which did not look like you,” “Working hard like someone who had been repeatedly doubted and told that there were others in line ahead.” “I'm a student. What drives me is intellectual curiosity. I want to learn and get better every day.” “I want to show up every day in the arena.” ETF: TSCMTickers: ARGX, SNOW *Not Investment Advice. ______________________________________________________________________ [00:00:00] Sonu Chawla's early interest in investing and journey through the Indian Institute of Technology. [00:01:50] How consulting at Deloitte led to a career in professional investing. [00:03:43] Growing up in a small town in India, overcoming barriers, and the importance of persistence and mentorship. [00:08:46] Resilience, learning from mistakes, and what continues to motivate Sonu as an investor. [00:10:32] Why TimesSquare Capital focuses on mid-cap growth investing and the long-term case for the asset class. [00:14:27] TimesSquare's analyst-driven investment process and how the team develops investment ideas. [00:19:26] Lessons from hedge fund investing and the importance of valuation discipline. [00:21:09] Sonu's quality growth investment philosophy and investing before profitability inflection points. [00:21:58] The Argenx case study and identifying businesses early in their scaling journey. [00:25:08] How deep sector expertise helps analysts build conviction through primary research. [00:26:24] Why specialized industry knowledge is the firm's competitive advantage. [00:28:30] Launching the TimesSquare Quality Mid-Cap Growth ETF and why active ETFs appeal to investors. ______________________________________________________________________ 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/⁠ TimesSquare Links: Sonu Chawla on LinkedIn: https://www.linkedin.com/in/sonu-chawla-cfa-0093612/ TimesSquare: https://tscmllc.com/

  • S1 · E35
    June 10 · 44 min

    EP035: "From Citadel & Millennium to Building AI for the Buy-Side" with Eric Moster

    In the new Pitch The PM series, The Wall Street Entrepreneur premier, Doug Garber speaks with former Citadel colleague, Eric Moster, CEO of Portrait Analytics and former portfolio manager at Millennium and Analyst at Surveyor Capital. Eric shares his transition from hedge fund investing into building AI-powered research tools purpose-built for institutional investors. The discussion explores how Portrait Research helps analysts monitor information flow, generate investment ideas, and accelerate deep fundamental research workflows. Eric explains the evolution of the platform from productivity software into a customized intelligence engine capable of identifying new opportunities based on an investor’s specific framework. They also examine the challenges of building AI products for hedge funds, balancing signal versus noise, scaling a startup, and why narrowing product focus became critical to Portrait’s growth strategy. _____________________________________________________________ [00:00:00] Introduction to Eric Moster and his move from investing to entrepreneurship. [00:00:36] Eric’s background at Citadel, Millennium, and Surveyor Capital. [00:01:14] How ChatGPT changed Eric’s view of AI and investing. [00:02:24] Joining Portrait Research alongside founder David Plon. [00:03:55] Eric’s path from first business hire to CEO. [00:05:28] Portrait’s evolution and product roadmap. [00:05:36] Overview of Portrait’s AI research and monitoring tools. [00:06:40] Tracking material information across industries. [00:08:04] Doug’s experience using Portrait. [00:08:48] Data quality challenges and filtering noise. [00:10:55] Using Reddit and alternative sources for investment insights. [00:11:50] Monitoring sentiment shifts and public reactions. [00:12:51] Determining what information is truly material. [00:14:29] Management guidance and investor interpretation. [00:16:55] Embedding hedge fund expertise into AI systems. [00:18:18] Why idea generation is the highest-value workflow. [00:20:42] Introduction to Portrait Intelligence. [00:22:03] Applying custom investment frameworks at scale. [00:24:03] Ranking opportunities based on framework fit. [00:25:10] Moving from productivity gains to revenue generation. [00:26:44] Learning from historical investment decisions. [00:29:41] Identifying recurring behavioral patterns. [00:30:34] Conducting objective investment postmortems. [00:31:35] Generating detailed turnaround investment reports. [00:33:58] Expanding the investment funnel with AI. [00:34:37] Why every framework is customized. [00:35:44] Ideal customer profiles and use cases. [00:36:52] Customer growth and adoption metrics. [00:37:55] Team growth, runway, and go-to-market strategy. [00:39:22] Pricing and product positioning. [00:39:59] Lessons on startup focus and prioritization. [00:41:20] Products Portrait intentionally shut down. [00:43:43] Final thoughts on entrepreneurship and investing. Links: Doug Garber on LinkedIn: https://www.linkedin.com/in/doug-garber-42aa508 Eric Moster on LinkedIn: https://www.linkedin.com/in/eric-moster-3006779 📩 Subscribe to our substack: https://pitchthepm.substack.com/

  • June 2 · 33 min

    EP 034: T. Rowe’s TURF, is Bullish the Canadian Oil Sands & The Oil Cycle

    Priyal Maniar, Co-PM of TURF and Global Energy Analyst, dives deep into why T. Rowe - who manages $1.8 Trillion - is structurally bullish the oil cycle.The marginal cost of production is increasing and US shale geology has peaked meaning the next well is more expensive and less productive. The recent U.S. - Iran war, wipes out the over supply from the start of the year and pulls forward the bullish productivity decline thesis. It also puts energy security in focus and improves demand for energy sources like coal. TURF expresses the bullish oil bet through an overweight position in Oil Sands producers such as Suncor (SU), Canadian Natural Resources and Cenovus Energy. Pyrial also highlights her top U.S. oil picks that have idiosyncratic catalysts in their FCF inflections coming up. Her top idea has free cash flow doubling over the next four years at flat prices with a great management team and a great balance sheet and ample low cost inventory. She also highlights three other names with ample inventory and FCF inflections. She notes that these stocks do well when large projects wind down free cash flow inflects. 🔍 What You’ll Learn: Why U.S. shale geology has peaked, and why that’s bullish, not bearish How to think about the marginal barrel at $70+ and rising Why Canadian Oil Sands offer the best duration in global energy How mining-style economics differ from shale (OPEX vs. CAPEX curve) The real math on Venezuela’s revival: $50-100B and 10 years Why energy security is now a structural demand driver How the Strait of Hormuz disruption changes Middle East midstream Global LNG after the Qatar train outages and project delays The coal-to-gas switching dynamic setting global gas prices Why AI power demand extends the runway for U.S. natural gas How electrification, nuclear, and SMRs fit into the energy stack Priyal’s top conviction names: Canadian E&Ps, and….How to use AI in the research process without getting front-runTimestamps[00:00] – Intro: U.S. Shale Peak Debate 01:00 – Why It Doesn't Matter If Shale Peaks: Cost Curve Matters 02:15 – Long Energy Cycles & S&P Energy vs. S&P 500 [03:30] – The Marginal Barrel Today: Guyana, Brazil, Middle East, Shale [05:00] – Shale Elasticity & Where Marginal Cost Goes Next[06:00] – Iran War Impact on the Oil Setup [07:15] – Energy Security as a Structural Demand Driver [08:30] – How to Express the Thesis in TURF[09:30] – Low-Cost U.S. E&Ps with Inventory & Balance Sheet [10:30]– The Canadian Oil Sands Bull Case [11:45] – Oil Sands Economics: Mining vs. Shale Decline Curves [13:00] – Why No New Greenfield Mines Get Sanctioned[14:15]– Venezuela: Heavy Oil Revival Math [15:30] – Chevron's Unique Position & Production Growth [16:45]– Political Risk: Venezuela vs. U.S. Election Cycles[18:00] – Middle East Egress & Pipeline Redundancies [19:15]– Aramco, ADNOC & National Project Dynamics [20:30] – East-West Pipeline Capacity & U.S. Expertise[21:45 ]– Global LNG: Qatar Outages & Project Delays [23:00] – Coal as the New Price-Setting Fuel [26:45] – Long-Term Bullish on Henry Hub [27:45] – Offshore Comeback: Conoco Alaska, Clearwater, Namibia, Guyana [30:30] – AI Power Demand & U.S. Gas Longevity [31:45] – Utilities, Nuclear & SMRs as Part of the Stack[33:00] – Advice for Aspiring Investors: Dig for the Next Insight [34:15] – How Priyal Uses AI in Her Research Process📩 Subscribe to the Pitch the PM newsletter to get the deeper investment framework, key metrics investors should track, and Doug's structured checklist for evaluating the idea.https://pitchthepm.substack.com/💡 Presented by AlphaSenseFree trial access: https://www.alpha-sense.com/Pitch/🎧 Listen on Spotify: https://open.spotify.com/show/4UHbkYE2OJwfhY2MZqGG5YListen on Apple Podcasts:https://podcasts.apple.com/us/podcast/pitch-the-pm/id1797669466This episode is for informational purposes only and does not constitute investment advice. See full disclosures at: https://www.pitchthepm.com/disclaimer

  • May 20 · 35 min

    EP033 - Cerebras (CBRS): Thematic Winner in AI Compute Shortage with SemiAnalysis’ President

    In this episode of Pitch The PM, Doug Garber speaks with Doug O’Laughlin, President of SemiAnalysis, about the explosive demand for AI infrastructure and the market reaction to Cerebras’ IPO. Doug O breaks down Cerebras’ wafer-scale chip architecture, its advantages in ultra-fast inference, and the limitations caused by memory scaling constraints. The discussion examines how NVIDIA continues to dominate large-scale AI workloads while specialized alternatives carve out niche roles in the broader compute ecosystem. They also explore the rise of agentic AI workflows, the growing economics of tokens and inference demand, and why frontier AI models are reshaping software development, legal work, and enterprise productivity. Doug O shares insights into how SemiAnalysis is using AI internally, why compute demand continues accelerating, and what the next wave of AI IPOs could mean for investors and the semiconductor industry. Tickers: #CBRS, #NVDA, #CRWV _____________________________________________________________ [00:00:00] Doug O’Laughlin compares Cerebras’ inference speed advantage to an F1 car versus NVIDIA as a bus. [00:00:20] Discussion of agentic AI workflows driving a major increase in compute demand. [00:00:31] Introduction to the episode and the focus on Cerebras’ technology and IPO. [00:01:36] Why Cerebras’ niche technology emerged during a historic compute shortage. [00:02:47] Breakdown of Cerebras’ SRAM-based architecture and the original technology bet. [00:03:55] Explanation of SRAM scaling limitations and memory density constraints. [00:05:26] Whether Cerebras can evolve beyond its current inference niche. [00:05:53] Emerging trends in disaggregated inference and hybrid AI architectures. [00:08:46] Why Cerebras can outperform NVIDIA in specific low-latency inference use cases. [00:09:10] The tradeoff between single-user speed and large-scale throughput. [00:13:18] Discussion of small language models versus frontier AI models. [00:13:45] Why Doug believes best-of-breed AI models continue to win in the market. [00:17:18] Legal industry productivity gains and concerns around shared AI training data. [00:18:07] How AI dramatically lowers the cost of accessing professional expertise. [00:19:11] Sponsor discussion and transition into Cerebras’ stock performance. [00:21:01] Doug’s perspective on the broader AI IPO environment and investor demand. [00:24:59] Supply and demand dynamics for AI-related equities and semiconductor exposure. [00:25:54] Comparison between equity enthusiasm and private credit caution in AI infrastructure. [00:26:58] Why GPU pricing increases indicate overwhelming AI compute demand. [00:28:30] Agentic AI workflows and cloud coding as the major inflection point for compute usage. [00:28:38] SemiAnalysis spending over $10,000 per week on APIs to accelerate productivity. [00:29:56] How AI tools are changing hiring needs and software engineering capabilities. [00:30:18] Examples of collapsing information work timelines through AI automation. [00:31:39] Disclosure discussion and SemiAnalysis’ relationships with leading AI companies. [00:32:09] Doug O explains SemiAnalysis’ approach to independent research and updating priors. [00:33:07] Doug O’Laughlin shares his background working on the buy side at Blue Capital. [00:34:10] Future plans for SemiAnalysis and the rise of “tokenomics” research. Links: Doug Garber on LinkedIn: https://www.linkedin.com/in/doug-garber-42aa508 Doug O’Laughlin on LinkedIn: https://www.linkedin.com/in/dougolaughlin/ 💡 This episode is powered by the Oxford Data Plan. Use the link here for Complimentary access 📩 Subscribe to our newsletter for research updates and new high-conviction episodes from top PMs & Analysts: https://pitchthepm.beehiiv.com/subscribe

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