VC10X - Investing, Venture Capital, Asset Management, Family Office, Wealth Management

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Note: Not investment advice. The episode was recorded on 26 Oct ‘26, several of the companies discussed have shared their earnings and guidance in the past few days after the date of recording. DYOR.

Rob Li is Managing Partner at Amont Partners and the second generation at his family's single family office. He began his career in private equity at Morgan Stanley and now runs a concentrated, Buffett-style equity portfolio across tech, consumer and industrials, with outside LPs alongside family capital and roughly a third of the book invested outside the US.

Rob explains why more machines and passive money are making markets less efficient, not more, and where human judgment still finds alpha.

⭐ This episode is brought to you by Podcast10x - https://podcast10x.com

Key topics we cover:

• Why Micron is still Amont's biggest position, and how high bandwidth memory changed the memory cycle
• Data deserts and data icebergs: where machines and AI miss mispricing
• The edge of investing across regions, from Nordic betting software to Shopify's logistics bet
• Why debt funding for AI CapEx is a bridge, not a solution
• The three M filter of moat, management and mispricing, and what private equity teaches public investors

Connect with Rob Li:https://www.linkedin.com/in/zl79/

Connect with Prashant Choubey:https://linkedin.com/in/choubeysahab

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VC10X website - https://vc10x.com

Timestamps:

(00:00) - Preview

(00:28) - Host introduction and sponsor message

(01:40) - Family office allocation and investment horizon

(02:05) - Investment philosophy, circle of competence, and outside LPs

(05:05) - Holding forever: intent versus quasi-permanent capital

(07:39) - Cyclical memory stocks and Micron drawdowns

(08:58) - Nike short, product cycles, and memory cycles

(17:16) - Micron's US base and cross-region advantage

(24:02) - Data deserts, data icebergs, and Qualcomm and Intel examples

(33:06) - Whether AI erodes the edge and siloed cross-region arbitrage

(37:59) - Debt-funded AI capex and corporate ROI

(45:29) - Using AI in own work and the value of human conversation

(47:01) - Patience, thesis changes, and the uniform rental exit

(48:34) - Moat, management, and mispricing filters; disruption risk

(54:30) - Private equity discipline, free cash flow, and sportswear insights

(60:02) - Closing and contact details

#VC10X #FamilyOffice #Investing #PublicMarkets #Micron #AI #HedgeFunds #ValueInvesting #Alpha #Podcast

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Aoifinn Devitt is Managing Director of Global Wealth at Moneta, a wealth management firm with $50.54 billion in assets under management. She previously served as Chief Investment Officer of Moneta and London CIV, ran her own investment consulting firm, and holds a PhD in psychological safety in investment management from King's College London. She also hosts the Fifty Faces podcast and the weekly Markets Happy Hour.

In this episode, Aoifinn explains how wealthy families approach alternatives, why risk tolerance is really tested in drawdowns, and why she blames advisors for the liquidity mismatch in private market funds.

⭐ This episode is brought to you by Podcast10x - https://podcast10x.com

Key topics we cover:

• How US and UK high-net-worth families differ on alternatives and risk
• Bringing institutional governance into private wealth and family offices
• What neuroscience reveals about investor behavior and active management's existential crisis
• Rebalancing in a concentrated market and staying cautious on the AI cycle
• Venture access for RIAs and who is to blame for the liquidity mismatch

Connect with Aoifinn Devitt:
LinkedIn - https://www.linkedin.com/in/aoifinndevitt/
Fifty Faces - https://www.fiftyfaceshub.com/
Moneta - https://monetagroup.com

Connect with Prashant Choubey:
LinkedIn - https://linkedin.com/in/choubeysahab

Subscribe to VC10X newsletter - https://vc10x.beehiiv.com
Subscribe on YouTube - https://youtube.com/@VC10X
Subscribe on Apple Podcasts - https://podcasts.apple.com/us/podcast/vc10x-investing-venture-capital-asset-management-private/id1632806986
Subscribe on Spotify - https://open.spotify.com/show/7F7KEhXNhTx1bKTBFgzv3k?si=WgQ4ozMiQJ-6nowj6wBgqQ
VC10X website - https://vc10x.com

Timestamps:

(00:00) Opening preview: investor psychology, active management, and liquidity
(00:41) Aoife Devitt and Moneta introduction
(01:50) Moneta’s UK expansion and US–UK wealth differences
(04:13) Centralized investment philosophy and advisor autonomy
(05:32) Esoteric investments and evaluating unusual opportunities
(08:03) Institutional governance in private wealth
(10:23) Capital preservation and client risk tolerance
(13:02) Neuroscience, investor behavior, and psychological safety
(16:03) Manager behavior during market drawdowns
(17:23) Active management’s performance challenge
(18:16) Equity concentration and the search for active alpha
(19:59) Portfolio rebalancing and trimming positions
(21:18) Tax planning for private wealth clients
(23:17) Due diligence on technology and AI investments
(27:09) Bonds, yields, and portfolio risk
(29:20) Venture capital access and manager selection
(30:06) Emerging managers and venture allocation
(32:39) Alternatives, liquidity, and the RIA model
(35:09) Qualitative signals in manager due diligence
(36:47) Cognitive diversity and investment team performance
(39:48) What asset managers offer RIAs
(40:48) Venture capital rapid-fire questions
(41:03) Venture themes and regions
(42:09) Typical venture fund commitments
(42:42) How fund managers can reach Moneta
(43:06) Where to follow Aoife Devitt
(43:43) Closing remarks

#VC10X #WealthManagement #FamilyOffice #Alternatives #PrivateMarkets #RIA #AssetManagement #VentureCapital #BehavioralFinance #InvestorPsychology

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Yash Patel is Managing Partner at Capra Ventures, a fund built around Lean AI: AI native companies that do more with less. Capra takes high conviction bets in seed and Series A companies, primarily at the AI application layer. Its first portfolio company, Higgsfield AI, grew from zero to $200M in ARR in nine months and to $1B in annualized revenue in eighteen months. Yash has previously led investments across vertical software and platforms, including OpenGov and Super.com.

In this episode, Yash breaks down his Lean AI playbook and what tiny, fast-growing AI teams mean for fund math, metrics, moats and the future of venture capital.

⭐ This episode is brought to you by Podcast10x - https://podcast10x.com

Key topics we cover:
• Why Lean AI companies call for more concentrated funds and more capital up front
• Net dollar retention of 300%+ and revenue per employee as the metrics that matter most
• Where the moat lies when every competitor has access to the same frontier models
• What the org chart of a one-person, $10M ARR company tells us about which roles stay human
• Why pricing is moving to outcome-based models and the middle of venture is being hollowed out

Timestamps:

(00:00) - Preview

(02:16) - How lean AI changes fund size, reserves, and growth economics

(07:39) - What founders need from venture partners and flexible capital

(10:20) - Retention, engagement, and the metrics that signal product-market fit

(14:14) - Open models, competition, and defensible AI startup moats

(18:13) - Distinguishing temporary viral spikes from durable AI product habits

(20:52) - Managing inference costs and protecting AI gross margins

(23:07) - Token pricing, model-company discounts, and compute deals

(25:04) - Internal model routers and choosing models by use case

(26:51) - AI-native company roles, automation, and human oversight

(31:23) - Founder skills and product velocity in lean teams

(34:10) - Building resilient organizations without corporate bloat

(37:39) - AI startup independence, acquisitions, and IPO prospects

(40:28) - How AI agents could shift SaaS pricing toward outcomes

(43:36) - Venture capital requirements as software gets cheaper to build

(46:49) - Changing venture milestones and the hollowing out of mid-stage funding

(48:38) - Rapid-fire questions about Capra Ventures

(48:50) - Investment sectors

(49:10) - Geographic focus and distributed talent

(49:58) - Typical investment stage and check size

(50:48) - Leading and co-leading rounds

(51:18) - How founders can contact Yash Patel

(51:44) - Where listeners can follow Yash

(52:22) - Closing remarks

Connect with Yash Patel:https://www.linkedin.com/in/ypatel1/

Connect with Prashant Choubey:https://linkedin.com/in/choubeysahab

Subscribe to VC10X newsletter - https://vc10x.beehiiv.com
Subscribe on YouTube - https://youtube.com/@VC10X
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VC10X website - https://vc10x.com

#VC10X #VentureCapital #LeanAI #AIStartups #StartupFunding #VCPodcast #ArtificialIntelligence #Investing

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Jessie Jia Guo is an Investment Partner at Next Legacy, a venture fund-of-funds that has been investing since 1999 on behalf of philanthropists, nonprofit organizations, and a community of athletes, entertainers and changemakers. One hundred percent of the distributions from Next Legacy's legacy funds go to nonprofit causes chosen by its investors, crossing three billion dollars to date. Jessie began her career on the LP side in Beijing before joining Next Legacy through a cold email to its founder.

Jessie Jia Guo on capital with a soul, how Chinese VCs scale differently, and the new liquidity playbook for GPs.

⭐ This episode is brought to you by Podcast10x - https://podcast10x.com

Key topics we cover:

• Why benchmarks are table stakes and how force-ranking managers adds rigor
• Whether capital with a soul makes an LP take more risk or less
• How Chinese VCs scale their companies and the role of geopolitics
• The portfolio construction blind spot experienced GPs have when pitching LPs
• Triaging a portfolio for liquidity and spotting real AI conviction versus hype

Timestamps:

(00:00) - Episode highlights
(01:06) - Introduction to Jessie Jia Guo and Next Legacy
(01:37) - Sponsor: Podcast10x
(02:18) - Landing a role at Next Legacy through a cold email, and how Jessie reads cold pitches today
(06:25) - Bringing force ranking from China to US-style benchmarking
(10:59) - Capital with a soul: how 100% charitable distributions shape risk appetite
(13:33) - Full-spectrum portfolio: emerging managers alongside established firms
(15:12) - Telling generational managers apart from trend-chasers
(18:05) - How Chinese VCs scale companies: USD vs RMB funds, going global and local government support
(20:56) - Exit routes and the impact of geopolitics on US-China venture
(25:30) - Next Legacy's history and early entry into China
(28:05) - A common blind spot when VCs pitch LPs: long-term portfolio construction
(31:28) - The new liquidity playbook: triaging breakouts, M&A candidates and pivots
(36:19) - Spotting real AI and deep tech conviction vs hype
(39:55) - $3 billion in charitable distributions and Jessie's personal legacy
(42:03) - The next frontier: institutional investors reinventing themselves with AI
(43:48) - Rapid fire: themes, check sizes and how to reach Jessie
(45:24) - Closing thoughts

Connect with Jessie Jia Guo: https://www.linkedin.com/in/jessiejiaguo/

Connect with Prashant Choubey:https://linkedin.com/in/choubeysahab

Subscribe to VC10X newsletter - https://vc10x.beehiiv.com
Subscribe on YouTube - https://youtube.com/@VC10X
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VC10X website - https://vc10x.com

#VC10X #VentureCapital #LimitedPartners #FundOfFunds #EmergingManagers #ImpactInvesting #Philanthropy #ChinaVC #Liquidity #AIInvesting #Podcast

Jev by TypeSafe is a different kind of AI model.

It doesn’t write essays, generate images, or try to replace frontier LLMs. Instead, Jev is designed to make fast, structured decisions — which tool to use, which model should handle a task, whether an action is safe, how relevant information is, or whether something should be escalated.

And that could become an important layer in the emerging AI agent stack.

In this episode, we break down what Jev actually does, why TypeSafe built a specialized decision model, and whether this approach can make AI agents faster, cheaper and more reliable.

⭐ Sponsored by Podcast10x - Podcasting agency for VCs - [https://podcast10x.com](https://podcast10x.com)

Key topics we explore:

— What Jev actually does and how it differs from traditional LLMs
— Why not every AI decision requires a frontier model
— How Jev could fit into the AI agent stack
— The economics of fast, structured AI decisions
— Where Jev could improve agent reliability and orchestratio
— The limitations and risks of specialized decision models
— What this could mean for the future architecture of AI

The bigger question:

How many decisions inside the AI economy can be separated from expensive generative models and handled by specialized models instead?

The next phase of AI may not just be about models that generate more. It could be about specialized models that decide what happens next.

LINKS

Prashant Choubey - [https://www.linkedin.com/in/choubeysahab](https://www.linkedin.com/in/choubeysahab)
Subscribe to VC10X newsletter - [https://vc10x.beehiiv.com](https://vc10x.beehiiv.com)
Subscribe on YouTube - [https://youtube.com/@VC10X](https://youtube.com/@VC10X)
Subscribe on Apple Podcasts - [https://podcasts.apple.com/us/podcast/vc10x-investing-venture-capital-asset-management-private/id1632806986](https://podcasts.apple.com/us/podcast/vc10x-investing-venture-capital-asset-management-private/id1632806986)
Subscribe on Spotify - [https://open.spotify.com/show/7F7KEhXNhTx1bKTBFgzv3k?si=WgQ4ozMiQJ-6nowj6wBgqQ](https://open.spotify.com/show/7F7KEhXNhTx1bKTBFgzv3k?si=WgQ4ozMiQJ-6nowj6wBgqQ)
VC10X website - [https://vc10x.com](https://vc10x.com)

Sponsorship queries: [prashantchoubey3@gmail.com](mailto:prashantchoubey3@gmail.com)

This channel is for asset managers, allocators, and investors who want analysis that holds up—not headlines dressed as insight.

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#VC10X #AI #ArtificialIntelligence #Jev #TypeSafe #AIModels #AIAgents #VentureCapital #Investing #AIInvesting #TechInvesting