Vertices Capital

About Vertices Capital

A podcast for new Limited Partners in Venture Capital. Vertices Capital specializes as an "Outsourced Chief Investment Officer" (a.ka. OCIO) specialized in Venture Capital. We partner with boutique family offices, independent asset managers, and regulated banks. We help them understand the Venture Capital landscape, build bespoke investment strategies, and execute them with precision. verticescapital.substack.com (https://verticescapital.substack.com?utm_medium=podcast)

Publisher

Vertices Capital

Category

business · technology

Language

en

Explicit

No

First episode

6 May 2025

Latest episode

15 Oct 2026

Latest episodes

48 episodes in the feed.

1. 

   15 Oct 2026

   48. The other side of venture capital

   Today we’re tackling a question that almost every new Limited Partner asks when reviewing recent venture capital vintages: How do you make sense of today’s disorienting venture landscape? Right now, the private venture market is sharply bifurcated. On one side, you have a small, highly visible cohort of AI infrastructure, foundation model, and chip companies raising massive funding rounds every three to six months at staggering valuations. You see companies scaling top-line revenue at historical speeds, accompanied by eye-watering multi-billion-dollar price tags. For a new LP, this creates an intense Fear Of Missing Out (FOMO). But to understand what is actually happening, you have to look at fund size math. Mega-platform funds managing $5 billion to $10 billion or more operate under strict structural constraints. To return a $10 billion fund, generating $1 billion exits isn’t enough; they require $5 billion to $10 billion net proceeds from single positions, forcing them into potential trillion-dollar outcome bets regardless of entry price. This dynamic fuels herd mentality, where momentum investors play with “house money” from earlier markups while others pay premium valuations just to signal AI participation to their LPs. But while consensus capital chases these hyper-crowded AI mega-rounds, a massive, highly lucrative segment of the venture ecosystem is being quietly overlooked. Anatomy of the overlooked opportunities. So, what is this “other side” of venture-backed companies that the AI spectacle is obscuring? It consists of high-performing, fundamental-driven businesses, both in traditional software and applied verticals, that are compounding at steady, healthy growth rates with durable economics. During periods of intense market hype, private capital frequently rewards raw top-line expansion without scrutinizing quality. In today’s hyper-hyped AI market, many fast-growing darlings suffer from single-digit gross margins, heavy token-reselling costs, and inflated growth masking customer churn. Contrast that with the overlooked category: companies growing at 2x to 3x annually at scale, scaling, for example, from $20 million to $60 million to $150 million in revenue, while maintaining high gross margins, capital efficiency, and clear paths to profitability. Let’s look at the LP math: A company with healthy unit economics that doubles its revenue every year for five years compounds by 32x. While consensus VCs turn up their noses at 2x or 3x growth because it doesn’t fit the hyper-growth narrative, veteran investors like Oren Zeev point out a crucial reality for LPs: a significantly higher percentage of these fundamental-driven companies will deliver top-tier, realized cash returns than speculative hyper-growth mega-rounds. If a company is growing 3x sustainably with healthy unit economics and no competitor is outpacing them 10x, it represents a prime venture risk-reward opportunity. Yet because they aren’t labeled as foundation models, they trade at far more rational entry valuations. The application layer, and real competitive moats. A common concern we hear from new LPs is: “If a company isn’t building core AI models, won’t foundation model providers like OpenAI simply absorb their software?” This narrative, popularized during peak market panic as the “SaaS apocalypse”, assumes that application-layer software is merely a thin wrapper with no defensible moat. But this fundamental misunderstanding ignores how enterprise software creates long-term value. In reality, underlying code alone is rarely the sole moat. The true moats in software and applied vertical AI stem from four key pillars: * Domain expertise and workflows: deep operational integration into specialized enterprise processes. * Proprietary data and context: unique, non-public customer data assets that generic base models cannot replicate. * Regulatory trust and precision: in fields like legal, finance, tax, and accounting, software cannot be right 99% of the time, it must be 100% accurate. Generic LLMs that hallucinate cannot replace compliance-grade, trusted application harnesses. * Customer distribution and relationships: established go-to-market channels and embedded organizational trust. Furthermore, every existing software business faces a binary reality in the AI era: they are either a beneficiary or a victim of AI. Founder-led application leaders willing to discard legacy assumptions are using AI as a massive tailwind to compress operating costs and expand customer value. Take corporate spend and travel platform Navan (formerly TripActions): as an AI-enabled application leader with a dominant market position, AI serves as an accelerator for margin expansion rather than a disruption risk. Fund maths and strategy for new allocators. Now let’s connect this directly to your asset allocation strategy as an LP. How should you structure your venture portfolio in response to these market dynamics? First, pay close attention to fund size discipline. Smaller, focused early-stage funds, typically in the $200 million range, possess a structural advantage over multi-billion-dollar mega-funds when investing in overlooked, high-fundamental companies. A $200 million fund does not require a $100 billion outlier to deliver a 3x or 4x net return to its LPs. It can generate outstanding cash-on-cash DPI through disciplined entry valuations in $1 billion to $3 billion market leaders. Conversely, mega-funds buying late-stage AI positions at 50x or 100x revenues face severe multiple compression risks when public market realities set in. Second, learn from historical tech supercycles. Drawing parallels to the 1999–2000 internet boom, the core technology transformation, then the internet, now AI, was 100% real and revolutionary. However, private market enthusiasm created a massive disconnect between private valuations and public market realities. When the cycle eventually normalizes, funds that bought high-margin, fundamental-driven compounders will hold durable assets, while funds that paid top-of-market multiples on thin-margin revenue will face difficult write-downs. Actionable LP diligence framework. To wrap up today’s episode, here is a 3-point diligence checklist for new LPs evaluating prospective General Partners (GPs): * Question growth quality, not just rate: ask managers whether their portfolio companies are building high-gross-margin, sustainable businesses or simply buying top-line growth at the expense of unit economics. * Evaluate the moat beyond the model: ensure the GP is investing in application leaders with proprietary data, deep workflow integration, and domain trust, rather than thin model wrappers. * Align fund size with strategy: verify that the GP’s fund size allows them to generate top-tier LP returns without depending on hyper-inflated mega-valuations. Market disorientation and divergence are not things to fear, they are where superior risk-adjusted returns are made. By seeing past the AI FOMO, sophisticated LPs can back managers who capture the massive upside of fundamental compounders sitting right in plain sight. Stay tuned for our next episode, and meanwhile, you can reach out to us, Vertices Capital, on our website: vertices.vc (http://vertices.vc/). Thank you for listening. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit verticescapital.substack.com (https://verticescapital.substack.com?utm_medium=podcast&utm_campaign=CTA_1)

2. 

   8 Oct 2026

   47. USV’s $900M set of new funds, and the new math of early-stage venture

   When Benchmark broke its 20-year pattern of keeping funds at $425 million or below to raise $2 billion across two new vehicles, it signaled that even the most discipline-first franchises were finding the market too expensive for the traditional early-stage playbook. USV raised $900 million across two new funds: a $500 million early-stage fund and a $400 million opportunity fund. The firm’s previous comparable vehicles were $275 million and $350 million, respectively, so this raise is by far the largest in the firm’s history, and echoes this exact structural shift. Examining both moves together reveals why top-tier early-stage firms are evolving their capital strategies, as well as the key differences in how they execute that evolution. First, the shared thesis: the market has evolved. Both Benchmark and USV are famously thesis-driven, concentrated early-stage investors that historically avoided bloated fund sizes to maintain tight ownership and high return multiples. Their strategy shifts reflect three shared market realities: Escalating check sizes. Benchmark created a $1.25 billion growth fund alongside its $750 million early-stage fund to handle larger, multi-stage funding rounds. Similarly, USV noted that typical Series A checks, which used to sit around $3 million, now start between $10 million and $30 million. To maintain target ownership percentages across a portfolio of roughly 30–40 core bets without diluting deal math, fund sizes naturally had to expand. Capital intensity in new tech cycles. While building an initial software prototype is cheaper than ever, scaling a breakout company now requires substantial capital. USV highlights that capital is heavily absorbed by subsidizing compute and inference costs to drive user adoption, cutting through market noise, and funding capital-heavy categories like energy, physical AI, and full-stack robotics. Bigger outcomes and competition: Both firms recognize that startup funding rounds are larger, faster, and more competitive, while potential market outcomes have expanded significantly. Second, the strategic divergence: multi-stage expansion vs. bottom-up discipline. While both firms scaled up, their fund architectures highlight two distinct approaches to managing style drift: Benchmark’s stage expansion. Benchmark broadened its scope by launching its first dedicated growth fund ($1.25B) alongside its core early-stage vehicle ($750M). For LPs, this represents a transition toward a multi-stage platform model, raising questions about team stability, decision rights, and whether later-stage investing might dilute their core early-stage edge. USV’s bottom-up fund sizing. USV explicitly chose not to raise a $1B+ “unicorn fund” or create a separate growth franchise as a vanity metric. Instead, they constructed the $900 million vehicle bottom-up based strictly on check sizes, target ownership, and portfolio reserves. About preserving outlier math. USV emphasizes that keeping their fund at $900 million, still relatively compact compared to mega-funds, ensures their return math does not depend on rare $100 billion mega-unicorns. Exits in the single-digit or $10 billion range can still return the fund multiple times and keep incentives aligned around carry rather than management fees. Finally, the LP evaluation framework. For Limited Partners analyzing this “great unfreezing” across legacy VC franchises, these two examples offer a clear framework for evaluating manager evolution: Strategy fit vs. AuM gathering. Is the larger fund size a bottom-up requirement driven by entry check size and ownership targets, or a top-down move to capture management fees and market share? Ownership discipline. Can the firm continue to win lead positions and secure meaningful equity ownership in higher-priced rounds without overpaying? Incentive alignment. Does the expanded capital base preserve partner focus on core portfolio execution, or does it introduce friction and team turnover? When premier firms like Benchmark and USV scale their funds, it is less about abandoning discipline and more about re-underwriting fund math to match the cost structures and deal mechanics of the AI era. Stay tuned for our next episode, and meanwhile, you can reach out to us, Vertices Capital, on our website: vertices.vc (http://vertices.vc/). Thank you for listening. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit verticescapital.substack.com (https://verticescapital.substack.com?utm_medium=podcast&utm_campaign=CTA_1)

3. 

   11 Sept 2026

   46. "Sourcing with Discipline" (ep. 17 of the series "101 VC Core Principles")

   Welcome to episode number seventeen of our series called “101 VENTURE CAPITAL CORE PRINCIPLES FOR NEW LPs, WILLING TO UNDERSTAND HOW VENTURE CAPITAL REALLY WORKS”… Let’s dig in. First, number 65. Investors should avoid “false coverage,” such as attending a demo day without following up with substantive engagement. Avoiding false coverage. Attending a demo day and simply collecting business cards is not real coverage; it’s theater that looks like diligence without creating any actual signal. beforeVC’s analysis of YC’s W26 batch makes this explicit: the angels who consistently win competitive allocation aren’t the ones who show up at demo day cold, but the ones who tracked 3 to 5 companies for weeks beforehand and already had valuation conversations in motion, proving that attendance without prior engagement is functionally worthless. Then, number 66. After a high-volume event like a demo day, the quality input is measured by selecting and pursuing the top five companies identified as promising. The top-five filter. After a high-volume event like a demo day, the real signal of quality investing is not how many companies you met, but how disciplined you were in narrowing to the handful worth real pursuit. TechCrunch’s coverage of YC’s Spring 2026 Demo Day shows this in practice: across an entire batch of hundreds of companies, investors converged on just eleven standout startups worth serious follow-up, filtering aggressively rather than chasing every pitch in the room. Now, number 67. For early-stage sourcing, investors must be in the right networks to meet founders before or immediately after they leave major companies (e.g., OpenAI or Anthropic). Sourcing at the frontier labs. In AI especially, the earliest and most valuable deals often come from founders stepping out of OpenAI or Anthropic, so being embedded in those networks before a public launch is now a critical sourcing edge. This dynamic is now so significant that at least a dozen investors who originally backed OpenAI have also moved to back Anthropic’s rivals and spinouts, and trackers like the “Exodus” AI talent tracker exist specifically to help investors spot the next wave of founders departing frontier labs before they officially launch. Finally, number 68. When a deal is passed on, VCs should document the rationale in a short memo for future retrospective analysis. Memos on the ones you pass. Writing a short rationale memo for every passed deal isn’t bureaucratic overhead; it is how a fund builds institutional memory and learns from its own blind spots over time. Bessemer Venture Partners turned this discipline into a public institution with its famous “anti-portfolio,” documenting the specific reasoning behind passes on companies like Airbnb and PayPal so the firm can study its own misses rather than simply forgetting them. Stay tuned for our next episode, and meanwhile, you can reach out to us, Vertices Capital, on our website: vertices.vc (http://vertices.vc). Thank you for listening. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit verticescapital.substack.com (https://verticescapital.substack.com?utm_medium=podcast&utm_campaign=CTA_1)

Reach and audience

Public platform figures. Ratings count people who left a rating, not total listeners.

Spotify

5.0 / 5

1 ratings

Contact Vertices Capital

Guest appearances

Does not typically book guests

Based on episode analysis; this does not confirm that the show is currently accepting guests.