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Nikhil KamathNikhil Kamath

Inside Silicon Valley’s VC Playbook | WTF is Venture Capital? - 2025 Edition | Ep. 24

In this unfiltered conversation, we discuss bad bets, overhyped markets, and where VCs should actually put their money. I sat down with Deedy Das (Principal, Menlo Ventures), Nikunj Kothari (Partner, FPV Ventures), and Niko Bonatsos (Early-Stage Venture Capitalist) to get their hot takes on industries. Timestamps: 00:00 - Intro 00:58 - Deedy’s journey & the Anthropic story 05:10 - Nikunj’s background 11:32 - Niko’s story 13:31 - Sectors to avoid as an investor 23:17 - Today’s hottest sectors 27:31 - Emerging AI trends 38:37 - Declining birth rates + AI’s role 48:19 - Abundance & capitalism 53:19 - Raising kids in an Instagram world 55:39 - No tech: the next big business? 1:00:55 - The future of dating apps 1:06:52 - Key predictions for the next frontier 1:10:14 - Will urbanisation continue? 1:13:51 - Longevity & wellness industry 1:16:01 - Which sector will boom by 2035? 1:25:59 - Rethinking senior living 1:32:52 - Content vs. product: what builds a brand? 1:43:50 - Individual vs. legacy brands 1:47:30 - EVs & mobility: the road ahead 1:58:03 - Opportunities in beauty & luxury 2:02:17 - Where live events are headed 2:06:14 - Climate tech & its impact 2:11:49 - Data centers: the best bet? 2:15:13 - Vices as an industry 2:24:18 - Wrapping it all together 2:29:02 - Legal AI: opportunities & challenges 2:32:29 - India in the global AI race #NikhilKamath - Investor & Entrepreneur Twitter: [https://x.com/nikhilkamathcio](https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqbm9WZVh3cHVTX3JEeGptVjlOZ1R3cW5rVkZJUXxBQ3Jtc0tuekFjWnRXME9XUUVLcDNCTk9YcHd5OU1MV1NMamE0cWE1T25meGJ4VWRMa21OY3VYLWM2T05iOUJtYTNWbWRSLW5YUXNzTTRHUUpjOGdZSGJzNEYxMkt2Y2hmWVNUeU51Nk5MRFVieVNtSTJwMkFXZw&q=https%3A%2F%2Fx.com%2Fnikhilkamathcio&v=wHQiewz8k9g) LinkedIN: [](https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqbGNsNjlxS2NyU3VxOUNIQU1VUmczaWNobmtJd3xBQ3Jtc0tsVmczaDdwdkpMZWlNaVdISk1mQUFfbmhZNVB2al9OU1hwbF9rYTFoMFJGN2FKRnFreXFEaXZhRGttd2xLRHBpQVhIS19XaW5wQTZ3UjB6bm5vazVmdUkwSEdsU0MxS1lXYmJvVnhlekVRczc0RmdTRQ&q=https%3A%2F%2Fwww.linkedin.com%2Fin%2Fnikhilkamathcio&v=wHQiewz8k9g)https://www.linkedin.com/in/nikhilkamathcio/ Instagram: https://www.instagram.com/nikhilkamathcio/ Facebook: https://www.facebook.com/nikhilkamathcio/ #DeedyDas - Principal, Menlo Ventures Twitter: https://x.com/deedydas LinkedIN: https://www.linkedin.com/in/debarghyadas/ #NikunjKothari - Partner, FPV Ventures Twitter: https://x.com/nikunj LinkedIN: https://www.linkedin.com/in/nikunjk/ #NikoBonatsos - Early-Stage Venture Capitalist Twitter: https://x.com/bonatsos LinkedIN: https://www.linkedin.com/in/bonatsos/

Nikhil KamathhostDeedy DasguestNikunj KothariguestNiko Bonatsosguest
Aug 28, 20252h 52mWatch on YouTube ↗

At a glance

WHAT IT’S REALLY ABOUT

Venture capital playbook: future sectors, AI shifts, and second-order effects

  1. The conversation starts with the guests’ operator-to-investor backgrounds and how early-stage investors think about timing, competition, and “hot” vs. overlooked categories.
  2. They discuss key AI shifts: data scarcity, reinforcement learning and evals, long-horizon reasoning/agents, and the race to capture physical-world data for robotics—plus the geopolitical reality of China’s strong models under constraints.
  3. The panel then explores second-order impacts: declining birth rates, digital addiction, privacy erosion, the return of religion/meaning, and how abundance could reshape work, inequality, and leisure.
  4. Finally, they rate sectors through a 2035 lens (beauty/luxury, vices/speculation, education, longevity/senior living, energy/climate, EVs, data centers, content, live events) and debate India’s strategic position in the global AI stack.

IDEAS WORTH REMEMBERING

5 ideas

Avoid ‘too hot’ categories early—pattern-matching deals are often late.

Bonatsos argues early-stage investors should be wary when dozens of startups pitch near-identical ideas (AI receptionists, app builders, RL environments); differentiation and founder edge matter more than category hype.

AI is turning ‘uninvestable’ legacy industries into buyers.

Kothari notes higher rates + cost pressure made efficiency urgent; factories, agriculture, and other slow-cycle sectors now actively seek AI/automation solutions, reversing historical long sales-cycle apathy.

Model progress is shifting from “more data” to better training regimes and evaluation loops.

Das highlights public data exhaustion and the growing importance of reinforcement learning setups and reward design; Bonatsos adds “evals” as a durable market—capturing expert corner cases to refine systems.

Long-horizon reasoning unlocks real ‘agentic’ workflows.

Kothari points to models running for hours with minimal direction as a step-change vs. the fragile agents of 1–2 years ago, enabling deep research, planning, and multi-step problem solving.

Embodied intelligence will be constrained by physical-world data and manufacturing, not just software.

Bonatsos emphasizes the scarcity of high-quality real-world sensor datasets (AV fleets are rare sources) and argues robotics adoption may lag AGI because producing robots at scale is a supply-chain problem.

WORDS WORTH SAVING

5 quotes

Nine out of ten inbound requests you receive, they all sound the same.

— Niko Bonatsos

We’ve run out of public data.

— Deedy Das

AGI is kind of already here… in a capabilities perspective, it’s already better.

— Nikunj Kothari

We should all assume that we’re living our lives in public now.

— Niko Bonatsos

The tyrant of efficiency. Counts seconds like coins…

— ChatGPT (read aloud by Nikhil Kamath)

VC vs. non-VC sector selectionWhat to avoid: overcrowded ‘hot’ marketsAI trends: data limits, RL, evals, long-horizon agentsEmbodied intelligence and physical-world datasetsDemographics: fertility decline and agingAttention economy: content vs. product qualityOffline resurgence: retreats, live experiences, dating evolutionInequality, UBI, and abundance scenariosEnergy/climate, data centers, and compute geopoliticsIndia’s role: foundation models vs. applications

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