Uncapped with Jack AltmanThe Next Generation of Software | Mamoon Hamid, Partner at Kleiner Perkins | Ep. 16
Jack Altman and Mamoon Hamid on mamoon Hamid on AI investing, VC cycles, and Kleiner’s revival.
In this episode of Uncapped with Jack Altman, featuring Mamoon Hamid and Jack Altman, The Next Generation of Software | Mamoon Hamid, Partner at Kleiner Perkins | Ep. 16 explores mamoon Hamid on AI investing, VC cycles, and Kleiner’s revival Hamid recounts entering Silicon Valley during the dot-com boom, learning how hype can detach from fundamentals, and how the best investors keep an open mind while being rigorous about timing. He then walks through the emergence of Web 2.0, cloud/SaaS adoption (which took longer than people remember), and mobile’s maturation from wrappers to native apps driven by games and killer apps.
At a glance
WHAT IT’S REALLY ABOUT
Mamoon Hamid on AI investing, VC cycles, and Kleiner’s revival
- Hamid recounts entering Silicon Valley during the dot-com boom, learning how hype can detach from fundamentals, and how the best investors keep an open mind while being rigorous about timing. He then walks through the emergence of Web 2.0, cloud/SaaS adoption (which took longer than people remember), and mobile’s maturation from wrappers to native apps driven by games and killer apps.
- He argues AI is a “super cycle” with a potential $60T labor opportunity, shifting value toward AI-levered companies and creating space for generational startups. Kleiner’s AI investing framework focuses on applications that map to real jobs—starting with copilots for highly skilled professions, moving to autonomous agents for mid-skilled roles, and eventually robotics for physical labor (but later due to cost/complexity).
- On firm-building, he describes joining Kleiner in 2017 as a “refounding moment,” returning to a small-table early-stage model, defining a mission (“first call for founders who want to make history”), and measuring partner performance through a disciplined funnel: see, pick, win, and work. He closes with how family and faith shape his leadership style and how he tries to treat founders with respect and empathy during high-stakes fundraising moments.
IDEAS WORTH REMEMBERING
5 ideasTiming beats pattern-matching past bubbles.
Hamid emphasizes staying optimistic and open-minded rather than dismissing new ideas because earlier versions failed (e.g., Webvan vs Instacart). The question is less “did it fail before?” and more “why now—are adoption and enabling tech finally ready?”},{
Cloud/SaaS wasn’t immediate consensus—even in VC.
He notes that in 2007–2009 many investors still centered on hardware/networking, and even obvious cloud apps struggled to get funded. Broad SaaS enthusiasm only flipped in the early 2010s after infrastructure matured and success stories accumulated.
AI is framed as a $60T ‘jobs-to-be-done’ market, not just a feature wave.
Hamid ties AI’s magnitude to labor’s ~60% share of GDP, arguing AI will increasingly do work, not merely assist. This reframes investing from “cool models” to “which real economic activities get automated or radically accelerated?”
Start with copilots for scarce, high-skill roles—then progress to autonomy.
Kleiner’s early AI approach targeted doctors, lawyers, and engineers with copilots (e.g., Ambient for clinical scribing, Harvey for legal, Windsurf for engineers). The premise: nuanced domains need humans in the loop first, with autonomy increasing as reliability improves.
Autonomous agents shine where persistence and scale are impossible for humans.
In roles like nursing call workflows (Hippocratic), AI agents can operate at the right times, at massive parallelism, and with infinite follow-up—unlocking protocol adherence and better outcomes that are currently limited by staffing and time windows.
WORDS WORTH SAVING
5 quotesAI is, to us, the super cycle of all super cycles.
— Mamoon Hamid
If you have that mentality, you're gonna miss everything.
— Mamoon Hamid
A lot of the stuff that happened in the dot-com boom, the timing was just off.
— Mamoon Hamid
If we want to invest in a company, we have to win it.
— Mamoon Hamid
Small N, high engagement, is a really good signal to invest in a company.
— Mamoon Hamid
QUESTIONS ANSWERED IN THIS EPISODE
5 questionsIn your ‘job pyramid’ framework, what’s the clearest signal that a copilot should graduate into a fully autonomous agent (reliability thresholds, regulation, workflow design, liability)?
Hamid recounts entering Silicon Valley during the dot-com boom, learning how hype can detach from fundamentals, and how the best investors keep an open mind while being rigorous about timing. He then walks through the emergence of Web 2.0, cloud/SaaS adoption (which took longer than people remember), and mobile’s maturation from wrappers to native apps driven by games and killer apps.
You cite a $60T labor opportunity—how do you avoid overestimating what’s economically automatable versus what’s technically possible but not cost-effective?
He argues AI is a “super cycle” with a potential $60T labor opportunity, shifting value toward AI-levered companies and creating space for generational startups. Kleiner’s AI investing framework focuses on applications that map to real jobs—starting with copilots for highly skilled professions, moving to autonomous agents for mid-skilled roles, and eventually robotics for physical labor (but later due to cost/complexity).
For products like clinical scribes, what are the hardest real-world adoption blockers (EMR integration, compliance, workflow change, physician trust), and how do you diligence them at Series A?
On firm-building, he describes joining Kleiner in 2017 as a “refounding moment,” returning to a small-table early-stage model, defining a mission (“first call for founders who want to make history”), and measuring partner performance through a disciplined funnel: see, pick, win, and work. He closes with how family and faith shape his leadership style and how he tries to treat founders with respect and empathy during high-stakes fundraising moments.
You measure ‘seeing’ 60% of peer Series A deals weekly—what qualifies as truly ‘seeing’ a deal, and what do you do differently when you’re below target?
Your internal goal is a 100% win rate on picks—does that ever create selection bias toward “winnable” deals over the most ambitious ones? How do you counteract that?
Chapter Breakdown
From 1997 engineer to VC curiosity: living inside the first internet boom
Mamoon Hamid recounts arriving in Silicon Valley in 1997 as a young engineer at Xilinx and experiencing the internet’s early momentum firsthand. Seeing iconic products (Netscape, Sun, Amazon, Google) and learning they shared a common Series A backer planted the seed that venture capital could be an impactful career.
The dot-com bubble: when prices detached from reality
The conversation moves into what the dot-com era felt like from the ground—both exciting and increasingly irrational. Mamoon describes day trading culture, companies with no revenue achieving massive valuations, and the growing presence of “non-builders” chasing monetization.
Lessons from cycles: stay optimistic, but obsess over timing
Mamoon explains how living through bubbles changes (and shouldn’t over-harden) an investor’s mindset. The key is balancing openness and optimism with a rigorous “why now” framework—many dot-com ideas were correct but too early for adoption and infrastructure.
2000–2005: the slowdown, immigration constraints, and business school as reset
After the crash, Mamoon describes a quieter Valley where jobs were scarce and mobility was limited, especially for those on visas. He uses the downturn to step away for business school, returning when the next wave begins to form.
Web 2.0 and the emergence of cloud software: the pre-consensus years
Returning in 2005, Mamoon joins venture and shifts focus from semiconductors to web and cloud software—before it became the dominant investing narrative. He highlights how early Web 2.0 products and UI-centric experiences reshaped expectations, while SaaS adoption was still far from a given.
Investing in Box: a product thesis meets an exceptional founder
Mamoon explains his early thesis: if desktop software moves to the browser, file sharing/file exploration would be foundational. Box became his first major investment, supported by both a clear product-category logic and immediate conviction in Aaron Levie’s founder quality.
Mobile’s early days: from HTML5 wrappers to native killer apps
Mamoon places mobile as a wave that overlapped with cloud but took time to mature into native-first experiences. He notes how debates about wrappers vs native ended as gaming and apps like Uber pushed performance and engagement expectations forward.
AI as a supercycle: mapping a $60T labor opportunity
Mamoon frames AI as larger than prior waves because it targets not only software and productivity but labor itself. He uses macroeconomic context (GDP, tech as % of GDP, labor share) to argue AI can reshape value allocation and create trillion-dollar venture outcomes.
Where to invest in AI: application layer first, using a ‘jobs pyramid’
Rather than focusing on foundation models or infrastructure, Mamoon explains Kleiner’s application-centric approach. They organize opportunity by job categories—starting with high-skill professions—initially building “copilots” that evolve toward autonomy.
From copilots to autonomous agents—and why robotics is later
Mamoon describes the next step down the pyramid: roles like nursing, sales, and analysis where agents can perform work end-to-end. He contrasts this with robotics, which faces harder data, cost, and physical-world complexity constraints—making it a longer-timeline bet.
Reigniting Kleiner Perkins: ‘back to the future’ and a refounding mindset
Mamoon explains joining Kleiner in 2017 as both a personal full-circle moment and an institutional reset. The firm focused back on what historically made it great: a small, early-stage, craft-driven partnership centered on serving founders.
Growing vs recruiting talent: building a small partnership with strong culture
He outlines why Kleiner intentionally keeps the partnership small and emphasizes internal development. Culture fit—servant leadership and founder service—matters as much as raw investing skill, and the firm optimizes for deep debate around a single table.
Win-rate discipline and the KP operating system: see, pick, win, work
Mamoon shares how KP evaluates both deals and investors via a four-stage funnel: seeing, picking, winning, and working. They track Series A coverage weekly, aspire to win every deal they choose to pursue, and review losses systematically to improve their playbook.
Pattern recognition in top investments—and the founder qualities that matter
Reflecting on Box, Slack, Figma, Rippling, and Applied Intuition, Mamoon distinguishes between non-competitive early bets and later competitive wins. His recurring signals include small-N but extreme engagement, product-obsessed builders, and founder-executors who can “will the future” into existence.
KP’s fund strategy and personal grounding: doubling down + family and faith
Mamoon explains the two-fund approach: an early-stage fund requiring outlier outcomes and a select/growth vehicle to double down on the best performers (and occasionally re-enter missed deals). He closes with what anchors him outside work—family and faith—and how those values shape how he treats founders and colleagues.
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