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Mamoon Hamid: AI - Where Value Accrues, Startups vs Incumbents & Scaling Laws | E1217

Mamoon Hamid is a General Partner @ Kleiner Perkins and one of the greatest venture investors of our time. In the past, Mamoon has led rounds in Figma, Slack, Rippling, Intercom, Glean and Box. Prior to joining Kleiner Perkins, Mamoon was a Co-Founder of Social Capital, and prior to that a Partner at U.S. Venture Partners (USVP). ----------------------------------------------- Timestamps: (00:00) Intro (03:01) Where Will AI's Value Accrue, and Where Should Capital Focus? (05:28) Is AI Investing Different from Traditional SaaS Investing? (07:49) Sustainable Growth vs. Sugar High Revenue (14:18) Will Foundation Models Subsume Application Layer Companies? (20:50) Where Does Kleiner Perkins Fit: Boutique or Capital Accumulator? (22:07) Lessons in Reserves Management & Capital Concentration (26:53) Why Do Breakout Companies Plateau? (30:19) What’s Mamoon’s Best Performing Investment (38:55) What’s Mammon’s Founder Type? (43:14) Should Founders Maximize Fundraising and Valuation Only? (46:10) What VCs Do Today That They Shouldn’t (47:53) Thoughts on Voting Structures in Decision-Making (51:21) Mamoon’s The Most Contentious Deal (54:24) Mamoon’s Biggest Loss (57:33) How Do the Best CEOs Run a Board? (59:11) Quick-Fire Round ----------------------------------------------- In Today’s Episode with Mamoon Hamid We Discuss: 1. The Greatest Venture Deal of All Time: Figma or Slack: What is Mamoon’s highest returning deal? What did Mamoon see in Dylan and Figma when they had no revenue and very little user data? What compelled Mamoon to write Stewart the check with Slack? What did he not see with Slack that he should have seen? 2. Taking Control of the Great Brand in Venture: Kleiner Perkins: Is it true that Kleiner approached Mamoon and gave him the keys to the Kleiner kingdom? How did it go down? Will Kleiner go back to having multiple products, large growth funds, international funds? What does Mamoon want Kleiner to be in 5 years? What was the hardest element of the transition into Kleiner? What did Mamoon not know that he wishes he had known? 3. Becoming a Generational Defining Investor: Market, founder, product, how does Mamoon rank them 1-3? How has Mamoon changed most significantly as an investor? What does he know now that he wishes he had known when he became a VC 19 years ago? What is his biggest loss? How did it shape his mindset and go forward investing approach? 4. AI Supercycle: The Greatest Time to Invest Where does Mamoon believe the value will accrue in this wave of AI? Where are many investors spending a lot of time but Mamoon believes is not worthy of that time? Will scaling laws continue? Have we ever seen an incumbent set spend like this incumbent class? How does that change the game for VCs? ----------------------------------------------- Subscribe on Spotify: https://open.spotify.com/show/3j2KMcZTtgTNBKwtZBMHvl?si=85bc9196860e4466 Subscribe on Apple Podcasts: https://podcasts.apple.com/us/podcast/the-twenty-minute-vc-20vc-venture-capital-startup/id958230465 Follow Harry Stebbings on Twitter: https://twitter.com/HarryStebbings Follow Mamoon Hamid on Twitter: https://twitter.com/mamoonha Follow 20VC on Instagram: https://www.instagram.com/20vchq Follow 20VC on TikTok: https://www.tiktok.com/@20vc_tok Visit our Website: https://www.20vc.com Subscribe to our Newsletter: https://www.thetwentyminutevc.com/contact ----------------------------------------------- #20vc #harrystebbings #mamoonhamid #kleinerperkins #partner #venturecapital #investor #figma #slack #ai #founder #rippling

Mamoon HamidguestHarry Stebbingshost
Oct 20, 20241h 3mWatch on YouTube ↗

At a glance

WHAT IT’S REALLY ABOUT

Mamoon Hamid on AI’s boom, venture discipline, and market creation

  1. Mamoon Hamid argues we’re in a once-in-a-lifetime AI supercycle where value will accrue largely at the application layer, especially in software that amplifies scarce, high-value workers like doctors, lawyers, and developers.
  2. He maintains that early-stage AI investing is fundamentally the same craft as classic SaaS: back exceptional, deeply technical, product-obsessed founders in big or category-creating markets, while staying disciplined on ownership and pricing despite hype.
  3. Hamid is skeptical of overinvestment in AI middleware and pure LLM providers in the near term, but believes massive CapEx will be justified as AI shifts spend from software licenses to labor substitution and productivity, unlocking trillions in tech value.
  4. On venture practice, he stresses concentration, thoughtful reserves, non-formulaic deployment, reputation-driven access, and founder selection over data platforms or voting structures, while candidly discussing mistakes in reserves, lending bets, and over-believing for too long.

IDEAS WORTH REMEMBERING

5 ideas

AI value will concentrate in vertical, application-layer products that augment scarce talent.

Hamid focuses on tools for doctors, lawyers, and developers, arguing AI that directly multiplies expensive human labor (e.g., co-pilots like Harvey, Ambience, Codium) supports dramatically higher price points and faster revenue scaling than traditional seat-based SaaS.

Founders and product quality still matter more than model access in AI startups.

He sees differentiation coming from deeply technical founders paired with domain experts, and from tuning models for near-perfect output in critical domains (e.g., 99%+ accuracy in medical transcription), not from simply wiring into a popular LLM.

Venture investors must stay price-disciplined, using “YOLO” bets sparingly.

Hamid acknowledges massive pre-product rounds at extreme valuations but insists these should be rare exceptions; the core business still requires buying 15–20% ownership at sane prices and reserving 40% of capital for follow-ons, or the fund math breaks.

Much AI middleware and tooling may be overfunded and fleeting in value.

He believes the “middle layer” (vector DBs, fine-tuning infrastructure, orchestration) is seeing heavy investment, but rapid technical change and potential commoditization mean much of the value there may not endure compared to focused applications.

LLM platforms will likely become good businesses, but not quickly or easily.

While today’s LLM providers have weak margins and intense price competition, Hamid draws an analogy to AWS and cloud: as GPU performance improves and scale grows, selling “electricity and compute” can become highly profitable over time, even if token prices keep collapsing.

WORDS WORTH SAVING

5 quotes

We’re in the midst of a supercycle like none we’ve seen before… this time feels like the rise of the internet multiplied by 10.

— Mamoon Hamid

We took the top 20 jobs in the US and who makes the most? It’s doctors, lawyers, and developers. How do we help supercharge these people?

— Mamoon Hamid

I love products that create markets. They get to create the playing field, they play on the playing field, and they win the game.

— Mamoon Hamid

A lot of firms think that information is knowledge and knowledge is arbitrage. But when everyone has the same knowledge, it’s no longer arbitrage.

— Mamoon Hamid

Venture is a grind. It’s glamorous… except it’s not glamorous.

— Mamoon Hamid

AI supercycle, scaling laws, and where value will accrueStartups vs. incumbents in frontier models and application layersPricing discipline, round dynamics, and reserves management in ventureMarket creation vs. competition: Slack, Figma, Glean, RipplingLLM economics, infrastructure vs. application-layer business qualityExit dynamics: M&A slowdown, IPO windows, and when to sellVenture firm strategy: boutique vs. capital accumulator, decision-making, and founder selection

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