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

AI spending isn't slowing down.

But the AI investment story may be changing.

Global AI spending is still accelerating, Nvidia is reporting extraordinary growth, and hyperscalers continue committing hundreds of billions of dollars to data centers, GPUs, networking and power.

So why are we hearing more about an "AI slowdown"?

Because there are several very different things that could be slowing — model development, infrastructure spending, AI revenue growth, or simply investor expectations.

And those distinctions matter.

In this episode, we break down what is actually happening beneath the AI boom, why massive infrastructure spending is creating a new focus on returns, and what happens when investors start asking whether AI growth is fast enough to justify the capital being deployed.

⭐ Sponsored by Podcast10x - Podcasting agency for VCs - https://podcast10x.com

Key topics we explore:

— Why AI spending and infrastructure demand remain extraordinarily strong
— What Nvidia's latest numbers reveal about AI demand
— Why hundreds of billions in AI infrastructure investment changes the investment equation
— The growing importance of capital efficiency, margins and infrastructure utilization
— Why highly leveraged AI infrastructure companies could face different pressures than hyperscalers
— How frontier AI development could slow without AI adoption slowing
— Why inference, AI agents and enterprise automation may become increasingly important
— The difference between slowing AI growth and slowing AI expectations
— Why the next phase of the AI boom could be defined by returns rather than spending

The bigger question:

Can AI generate enough economic value to justify the enormous amount of capital being invested into the technology?

AI doesn't have to stop growing for the AI trade to slow down.

It simply has to grow more slowly than the expectations already priced into the market.

For investors, that distinction could become increasingly important as the AI ecosystem moves from a period of aggressive capital deployment toward a period where revenue, margins, utilization and return on invested capital matter much more.

The question is no longer simply:

"How big can AI become?"

It's:

"Show me the returns."

LINKS

Prashant Choubey - https://www.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

Sponsorship queries: prashantchoubey3@gmail.com

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

Subscribe for weekly data-driven breakdowns of the forces reshaping capital markets.

#VC10X #AI #ArtificialIntelligence #Nvidia #AIInvesting #AIInfrastructure #AIBubble #DataCenters #AIAgents #VentureCapital #Investing #TechInvesting

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Morgan Flager is Managing Partner at Silverton Partners, the longest-running and most active early-stage venture firm in Texas. He joined Silverton in 2006 and has spent two decades backing seed and Series A companies out of Austin, with outcomes including SailPoint, Ping Identity, Vacasa, AlertMedia, Black Locus and TrendKite. Silverton closed Fund VII at $248M, the largest in the firm's history, and is currently in market with Fund VIII. Before Silverton, Morgan invested at FTV Capital and held operating roles at Kintana and Ingrian Networks. He holds a BS from Stanford.

Morgan is at least doubling Silverton's allocation to hard tech, and he explains why part of that rotation is real conviction and part of it is the venture industry running from a broken toy.

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

Key topics we cover:
- Why Silverton's hard tech allocation is moving to 30-40% of the fund across defense, AI infrastructure, manufacturing and energy
- What still makes a software company defensible when features are commoditized and wrappers are worse than features
- Why he's writing more seed checks instead of holding deeper reserves as the power law sharpens
- The valuation math that makes him walk away: a $300M seed entry needs a $5B outcome, and only ~30 companies have crossed $10B in 20 years
- How LP conversations changed between Fund VII and Fund VIII, and why liquidity is now the first question

Chapters:

(00:00) - Preview

(00:52) - Introduction to Morgan Flager & Silverton Partners

(02:19) - Silverton's Evolving Deployment Strategy (2022-2026)

(03:15) - Increased Allocation to Hard Tech & Emerging Categories

(06:01) - Why VCs are Shifting from Software to Hard Tech

(08:03) - Distinguishing AI Wrappers from Defensible Enterprise Platforms

(12:25) - The Next Era of the Texas Startup Ecosystem

(15:07) - Portfolio Construction: More Shots on Goal vs. Deeper Reserves

(18:20) - How AI Creates More Capital-Efficient Software Companies

(22:26) - Maintaining Valuation Discipline in a Hot Market

(25:55) - How AI Will Change the Healthcare Landscape

(29:40) - The Changing Architecture of a Successful Marketplace

(33:00) - The Risk of Frontier Models (OpenAI, Claude) Competing with Startups

(38:00) - Distinguishing Genuine Founder Obsession from Trend Chasing

(40:38) - The Most Common Scaling Friction for B2B Founders ($1M to $10M ARR)

(43:40) - The Shift in LP Conversations and Priorities for Fund VII

(47:01) - How LP Composition has Shifted Over Time

(49:36) - Navigating Tough Board Conversations About Fundraising

(54:33) - The Core Investing Philosophy Morgan Had to Unlearn

(58:34) - Rapid Fire Round Begins

(58:46) - Sectors and Regions

(59:11) - Stage of Investment

(59:20) - Leading Rounds

(59:30) - Typical Check Size

(59:45) - How Founders Can Get in Touch

(01:00:16) - Where to Follow Morgan Online

Connect with Morgan Flager:
LinkedIn - https://www.linkedin.com/in/mflager/
Silverton Partners - https://www.silvertonpartners.com

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

#VentureCapital #DeepTech #StartupInvesting #SeedFunding #AustinTech

AI researchers are resigning — and some are warning that the technology is getting dangerously good.

The latest is Jacob Coxon, who recently resigned from Anthropic after previously working at OpenAI and publicly shared his reasoning on X.

But this isn't simply a story about one researcher leaving an AI lab.

The bigger issue is the race between frontier AI companies. OpenAI, Anthropic, Google, Meta and others are competing to build increasingly capable models, while some researchers are warning that the safety systems needed to control these models may not be keeping pace.

Even if one lab slows down, its competitors have an incentive to keep moving.

In this episode, we break down why AI researchers are increasingly raising concerns, what the frontier AI race looks like from inside the labs, and why self-improving AI could fundamentally change the risk equation.

⭐ Sponsored by Podcast10x - Podcasting agency for VCs - https://podcast10x.com

Key topics we explore:

— Why Jacob Coxon resigned from Anthropic
— The growing divide between AI capability and AI safety
— Why frontier AI has become a race nobody wants to lose
— What happens when AI becomes capable of doing AI research
— The potential implications of recursive self-improvement
— Why even safety-focused AI labs face enormous competitive pressure
— What the AI arms race means for investors, companies and policymakers

The bigger question:

What happens when every AI lab believes it can't afford to slow down?

For investors, this is more than an AI safety debate. The incentives driving frontier AI development could shape how capital flows into the sector, how companies compete, and ultimately who controls the most powerful technology being built today.

The challenge isn't simply making AI more capable.

It's building an environment where companies can slow down when necessary — without handing the entire advantage to whoever keeps accelerating.

LINKS

Prashant Choubey - https://www.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

Sponsorship queries: prashantchoubey3@gmail.com

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

Subscribe for weekly data-driven breakdowns of the forces reshaping capital markets.

#VC10X #AI #ArtificialIntelligence #Anthropic #OpenAI #AISafety #AIInvesting #VentureCapital #Investing #TechInvesting

Get new episodes in your inbox - https://vc10x.beehiiv.com

Ned Brines is Chief of Investment Strategy at Arnel & Affiliates, a single family office in Southern California, where he runs the portfolios for both the family and its foundation. He spent six years in investment banking and more than two decades as an institutional money manager before moving into the family office world, and he serves as an independent director of a publicly traded apartment REIT.

In this episode, Ned breaks down how a multi-billion dollar family office actually builds a portfolio, and why most of what passes for diversification isn't.

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

Key topics we cover:

• Why thirty equity managers is one bet wearing thirty different labels
• What real estate is really there to do in the portfolio, and why he doesn't think it's the inflation hedge everyone claims
• How IRR gets manipulated with subscription lines, and what he does to strip it back out
• Why he caps venture funds at $150M and PE funds at $750M
• Why he holds twelve percent cash, waits for downside volatility, and once waited fourteen years to buy a stock

Links:

Connect with Ned Brines:
LinkedIn - https://www.linkedin.com/in/ned-brines/

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) - Preview

(03:12) - The Biggest Misconception in Portfolio Construction

(04:16) - Building a Portfolio Based on Economic Conditions

(05:43) - The Role of Real Estate in a Family Office Portfolio

(06:25) - Framework for In-sourcing vs. Outsourcing Investments

(08:47) - The Dangers of Illiquid Strategies for Retail Investors

(11:08) - How Rising Interest Rates Challenge Private Equity

(12:11) - Hedging Against Geopolitical and Interest Rate Uncertainty

(14:34) - What Specific Role Does Real Estate Play in a Portfolio?

(16:11) - How Families Without a Real Estate Background Should Invest

(19:30) - Are REITs the Best Way to Invest in Real Estate?

(20:37) - Evaluating Established vs. Emerging Fund Managers

(22:15) - Focusing on MOIC (Multiple on Invested Capital) Over IRR

(24:15) - How to Differentiate Between Two Seemingly Similar Managers

(26:08) - Why High-Conviction, Concentrated Bets Are Preferred

(29:32) - Determining the Right Amount of Cash to Hold for Opportunities

(32:40) - Managing a Single Cash Pool for Family Needs and Investments

(33:55) - Uncovering Hidden Risks in Private Markets

(37:13) - Operational Improvements with the Biggest Impact

(39:10) - Distinguishing Between Genuine Risk and Market Volatility

(41:50) - Thoughts on the AI Stock Thesis and Valuations

(47:31) - An Investment Belief That Has Changed Over the Last Decade

(50:13) - How Serving on a REIT Board Changed His View on Real Estate

(55:53) - The Future Advantages and Disadvantages for Family Offices

(01:00:43) - Start of Rapid Fire Round

(01:00:59) - Sectors and Regions of Investment

(01:03:48) - Typical Commitment Size for VC and PE Funds

(01:05:10) - Sourcing Deals: Inbound vs. Outbound

(01:07:22) - Where Listeners Can Follow Ned

#VentureCapital #FamilyOffice #PrivateEquity #Investing #AssetAllocation

Nvidia just announced its acquisition of Hugging Face for $12.93 billion — one of its biggest moves yet.

But this isn't simply Nvidia buying another AI company.

Hugging Face sits at the developer and model layer of the AI stack, while Nvidia dominates the compute underneath it. The deal could give Nvidia a much deeper position across the AI ecosystem — from chips and infrastructure to models, developers and deployment.

In this episode, we break down what Nvidia is really buying, why open AI matters, and what this could mean for the competitive landscape.

⭐ Sponsored by Podcast10x - Podcasting agency for VCs - https://podcast10x.com

Key topics we explore:

— Why Nvidia is paying nearly $12.92B for Hugging Face
— Hugging Face's role in the open AI ecosystem
— Nvidia's move from chips toward a full-stack AI platform
— The strategic importance of developers, models and inference
— How the deal could strengthen Nvidia against custom AI chips
— The tension between Nvidia ownership and Hugging Face's compute-agnostic model

The bigger question:
Is Nvidia buying Hugging Face for its current business — or to control a much larger part of the AI stack?

For investors, the deal is another signal that the AI value chain is moving beyond GPUs. Nvidia isn't just trying to sell the picks and shovels of AI — it's increasingly positioning itself across the platform where AI gets built.

LINKS

Prashant Choubey - https://www.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

Sponsorship queries: prashantchoubey3@gmail.com

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

Subscribe for weekly data-driven breakdowns of the forces reshaping capital markets.

#VC10X #Nvidia #HuggingFace #AI #ArtificialIntelligence #VentureCapital #Investing #OpenAI #AIInvesting #TechInvesting