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Invest Like the Best with Patrick O'Shaughnessy

Mitchell Green - Lessons from Cold Calling 10,000 Companies - [Invest Like the Best, EP.464]

54 min episode · 2 min read

Episode

54 min

Read time

2 min

Topics

Productivity, Relationships, Investing

AI-Generated Summary

Key Takeaways

  • LP Network as Competitive Moat: LeadEdge's 800 LPs are 95% senior executives and entrepreneurs — not institutions — deployed across the full investment cycle: sourcing introductions, diligence back-channels, and post-investment customer referrals. This structure costs more time than managing 20 institutional LPs but creates differentiation that justifies deal access in a crowded market.
  • Cold Calling at Scale: Eighteen junior analysts contact roughly 9,000 companies annually, filtering down to 900 that meet five or more of eight criteria, then 150–175 for diligence, yielding five to seven investments per year. CEO responsiveness during cold outreach serves as a direct signal of management quality — more responsive CEOs correlate with better operators.
  • Eight Criteria, Five Required: LeadEdge's framework requires $10M+ revenue, 25%+ growth, 70%+ gross margins, recurring revenue, capital efficiency (revenues exceeding cumulative cash burn), no bottom-line losses, and no customer concentration. Deals must meet at least five criteria to advance. Notably, eight-criteria deals show no statistically better returns than five-criteria deals — the framework filters deal volume, not outcome quality.
  • Selling Discipline via Disposition Committee: Three founding partners meet one to two times monthly specifically to evaluate exits, tracking forward IRR rather than holding for maximum upside. Roughly one-third of exits are secondaries. Toast exemplifies this: LeadEdge sold $180M in secondary before IPO at $40–50/share; the stock currently trades near $30, validating the forward-underwriting discipline over narrative-driven holding.
  • AI Readiness Scoring for Portfolio Companies: LeadEdge scores each portfolio company on AI readiness across four dimensions: data structure quality, product iteration velocity, number of new AI-driven product releases, and AI-attributable revenue. Rather than cutting engineering headcount as AI improves productivity, Green advocates maintaining headcount so engineers produce more products for sales teams to monetize.

What It Covers

Mitchell Green, founder of LeadEdge Capital, details the systematic investment machine he built over 15 years with partners Brian and Nima — covering their 9,000 annual cold calls, eight-point company criteria, LP network of 800 executives, and disciplined focus on 2–2.25x net returns across 20-position funds.

Key Questions Answered

  • LP Network as Competitive Moat: LeadEdge's 800 LPs are 95% senior executives and entrepreneurs — not institutions — deployed across the full investment cycle: sourcing introductions, diligence back-channels, and post-investment customer referrals. This structure costs more time than managing 20 institutional LPs but creates differentiation that justifies deal access in a crowded market.
  • Cold Calling at Scale: Eighteen junior analysts contact roughly 9,000 companies annually, filtering down to 900 that meet five or more of eight criteria, then 150–175 for diligence, yielding five to seven investments per year. CEO responsiveness during cold outreach serves as a direct signal of management quality — more responsive CEOs correlate with better operators.
  • Eight Criteria, Five Required: LeadEdge's framework requires $10M+ revenue, 25%+ growth, 70%+ gross margins, recurring revenue, capital efficiency (revenues exceeding cumulative cash burn), no bottom-line losses, and no customer concentration. Deals must meet at least five criteria to advance. Notably, eight-criteria deals show no statistically better returns than five-criteria deals — the framework filters deal volume, not outcome quality.
  • Selling Discipline via Disposition Committee: Three founding partners meet one to two times monthly specifically to evaluate exits, tracking forward IRR rather than holding for maximum upside. Roughly one-third of exits are secondaries. Toast exemplifies this: LeadEdge sold $180M in secondary before IPO at $40–50/share; the stock currently trades near $30, validating the forward-underwriting discipline over narrative-driven holding.
  • AI Readiness Scoring for Portfolio Companies: LeadEdge scores each portfolio company on AI readiness across four dimensions: data structure quality, product iteration velocity, number of new AI-driven product releases, and AI-attributable revenue. Rather than cutting engineering headcount as AI improves productivity, Green advocates maintaining headcount so engineers produce more products for sales teams to monetize.

Notable Moment

Green reveals that despite raising a $3.5B seventh fund, he deliberately avoids investing in high-profile AI model companies like OpenAI, calling valuations in the billions personally irrational — while acknowledging he could be entirely wrong if those companies generate a trillion dollars in earnings.

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Episode Transcript

Most software companies try to maximize your time on their app to juice engagement. Ramp does the exact opposite. Ramp understands that no one wants to spend hours chasing receipts, reviewing expense reports, and checking for policy violations. So they built their tools to give that time back, using AI to automate 85% of expense reviews with 99% accuracy. And since Ramp saves companies 5%, it's no wonder that Shopify runs on Ramp, Stripe runs on Ramp, and my business does too. To see what happens when you eliminate the busy work, check out ramp.com/invest. Every investor should know about Rogo because Rogo AI's platform is not just another generic chatbot. Instead, it was designed to support how Wall Street bankers and investors actually work from sourcing diligence and modeling to turning analysis into deliverables. For me, three key things differentiate Rogo. First, it connects directly to your system, so it can work with your actual data. Second, it understands your workflows, how work really happens across a deal or an investment. And third, it runs end to end and produces real outputs the way the best people do, auditable spreadsheets, investment memos, diligence materials, and slide decks that match your standards. This all comes from the fact that Rogo is built by finance professionals for finance professionals, and it's already being adopted by some of the most demanding institutions in the world. To learn more, visit rogo.ai/invest. OpenAI, Cursor, Anthropic, Perplexity, and Vercel all have something in common. They all use Work OS. And here's why. To achieve enterprise adoption at scale, you have to deliver on core capabilities like SSO, SCIM, RBAC, and audit logs. That's where Work OS comes in. Instead of spending months building these mission critical capabilities yourself, you can just use WorkOS APIs to gain all of them on day zero. That's why so many of the top AI teams you hear about already run on WorkOS. WorkOS is the fastest way to become enterprise ready and stay focused on what matters most, your product. Visit workos.com to get started. Hello and welcome, everyone. I'm Patrick O'Shaughnessy, and this is Invest Like the Best. This show is an open ended exploration of markets, ideas, stories, and strategies that will help you better invest both your time and your money. If you enjoy these conversations and wanna go deeper, check out Colossus, our quarterly publication with in-depth profiles of the people shaping business and investing. You can find Colossus along with all of our podcasts at colossus.com. Patrick O'Shaughnessy is the CEO of Positive Sum. All opinions expressed by Patrick and podcast guests are solely their own opinions and do not reflect the opinion of Positive Sum. This podcast is for informational purposes only and should not be relied upon as a basis for investment My guest today is Mitchell Green, the founder of LeadEdge Capital. When I think about LeadEdge, I sort of think about this giant money machine that Mitchell and his two …

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  • Mitchell Green, founder of LeadEdge Capital, details the systematic investment machine he built over 15 years with partners Brian and Nima
  • Toast exemplifies this: LeadEdge sold $180M in secondary before IPO at $40–50/share; the stock currently trades near $30, validating the forward-underwriting discipline
  • he deliberately avoids investing in high-profile AI model companies like OpenAI, calling valuations in the billions personally irrational

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