Warren Pies of 3Fourteen Research joins Excess Returns to break down the AI bull market, the macro risks investors should watch, and why the data still supports continued strength in semiconductors and equities. We discuss GPU demand, token usage, open source AI, Fed policy, housing weakness, oil, earnings growth, market valuations and the biggest risks to the current cycle.

Warren Pies on X
https://x.com/WarrenPies

3Fourteen Research
https://www.3fourteenresearch.com/

Caliban
https://www.3fourteenresearch.com/caliban

Main topics covered

• Which bearish AI arguments actually matter for investors

• Why regulatory risk may be the biggest long-term AI concern

• How data center spending is crowding out housing investment

• Why the Fed may struggle to cool AI-driven investment without hurting the labor market

• What GPU availability says about real-time AI compute demand

• Why open source AI is not yet replacing frontier models

• How token pricing and OpenRouter data help measure AI usage

• Why semiconductor stocks may still be in the middle of a major cycle

• How semis are being valued differently than traditional cyclicals

• Why Fed policy, earnings growth and market multiples are key to the second half of 2026

• What oil positioning and refined product inventories say about macro risk

• Why 3Fourteen remains constructive on equities despite rising overheating risk

Timestamps

00:00 Intro
01:04 Which bearish AI arguments have teeth?
04:00 Why AI regulation is the biggest long-term risk
07:03 Technology spending versus housing investment
11:03 How AI CapEx is showing up in inflation data
13:04 Why the labor market is more fragile than headline jobs data suggests
16:24 Why GPU availability is a cleaner signal than CapEx announcements
21:00 What token pricing and OpenRouter data reveal about AI demand
27:36 How 3Fourteen benchmarks frontier models against open source AI
30:00 Why the semiconductor selloff looked like a buyable dip
34:02 Are semiconductors still cyclical businesses?
38:08 Why Fed tightening could be the thing that ends the bull market
42:15 What the oil shock means now
45:47 Refined product inventories, crack spreads and energy stocks
47:18 Are earnings estimates becoming too optimistic?
50:49 Why the debasement regime still supports equities
54:05 Where to find Warren Pies and 3Fourteen Research

Ritavan joins Excess Returns to explain The System Gambit, a new framework for understanding competitive advantage, business strategy, AI disruption and long-term compounding. We discuss why traditional moat checklists can miss the real source of value, how companies can build systems competitors cannot copy, and what investors should look for when AI changes the game.

The System Gambit
https://amzn.to/4b0J32I

Main topics covered

• Why the traditional moat checklist can fail investors

• The three requirements for a true System Gambit

• How investors can evaluate business strategy from the outside

• Why code is not always the moat in the age of AI

• What history can teach investors about asymmetry and leverage

• Why AI adoption is not the same as AI value creation

• The difference between moving fast and understanding the game

• Lessons from Nokia, ASML, Amazon and Walmart

• How intangible investment and J curves can hide long-term value

• Why the best companies build compounding systems competitors cannot copy

• How investors can identify companies changing the game rather than optimizing the old one

Timestamps

00:00 Opening preview and introduction

04:00 The three ingredients of a System Gambit

08:49 Why code is not the moat in AI software

13:00 Skanderbeg and changing the rules of the game

17:00 Good moats, good narratives and asymmetric advantage

22:31 Microscope vs telescope as a lesson for AI

28:35 AI winners, losers and high dispersion markets

32:08 Signal quality, bottlenecks and why AI adoption is not enough

36:00 Nokia, agility and the failure to build a causal model

40:15 Why understanding the game beats speed

44:00 Intangible investment, the J curve and ASML's hidden edge

49:54 The contrarian AI thesis behind The System Gambit

54:00 How to recognize a real System Gambit

58:27 Amazon, Walmart and multi-paradigm compounding

1:03:00 Prime, FBA and platform leverage

1:07:00 Walmart's answer to Amazon

1:11:06 Closing thoughts and where to find Ritavan

On this episode of the 100 Year Thinkers, Chris Mayer and Matt Zeigler discuss long-term investing, 100-baggers, AI stocks, SpaceX valuation, founder-led companies, and why the best investments often come with brutal drawdowns. We also cover his new book The Investor's Odyssey, the danger of letting labels like AI do too much work, how to think about TAM and capital allocation, and why patience may be the biggest edge for investors trying to own great businesses for decades.

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The Investor's Odyssey: Resisting the Sirens and Playing the Long Game⁠

https://amzn.to/44BMXeJ⁠

Main topics covered

• Why SpaceX, AI and trillion-dollar IPOs are testing investor discipline

• How Chris Mayer thinks about valuation after watching Google become a huge winner

• Why great businesses can still be terrible investments at the wrong price

• The danger of letting labels like AI, quality and TAM replace real analysis

• Why many AI features may not create real customer value

• What the dot-com bubble can teach investors about AI adoption and shakeouts

• Why investors do not need to be early if a company is truly exceptional

• How to separate AI anecdotes from real financial impact

• Why capital allocation and return on invested capital matter more as companies scale

• How to evaluate founder control, governance, incentives and trust

• Why the best long-term stocks can still fall 50 percent or more along the way

• What rational exuberance might look like for long-term investors

Timestamps

00:00 Intro: Chris Mayer on AI, SpaceX and long-term investing

04:00 SpaceX valuation vs Google and the risk of paying too much

08:01 Why labels like AI and quality can do too much work

12:05 The AI pause, the dot-com analogy and where real value may emerge

16:06 Why investors do not need to be early when a business is real

21:00 Becoming a great company versus already being mature

25:10 Thinking about TAM, market share and realistic growth expectations

29:43 Corporate governance, free float and shareholder rights

34:27 How to judge founder trust, incentives and compensation

38:57 Employee ownership, culture and building enduring companies

43:02 Investor frustration in a lopsided AI-driven market

47:02 Why even a perfect stock picker would face brutal drawdowns

52:17 The rise of trillion-dollar IPOs and the question of rational exuberance

56:29 The Investor's Odyssey and playing the long game

Ben Inker of GMO joins Excess Returns to break down whether the AI boom is an investment bubble, how it compares to 2000, 2007 and 2021, and why today’s risk may be more about earnings than valuations. We also discuss AI capital spending, market supply from IPOs, GMO’s seven-year asset class forecasts, international stocks, benchmark-free allocation and what private equity investors may be missing.

7 YEAR ASSET CLASS FORECAST

https://www.gmo.com/americas/research-library/gmo-7-year-asset-class-forecast-may-2026_gmo7yearassetclassforecast/

WHAT BARBARIANS LIKE TO TAKE PRIVATE

https://www.gmo.com/americas/research-library/part-1-what-barbarians-like-to-take-private_gmoquarterlyletter/

THE CASE FOR LIQUID ALTERNATIVES

https://www.gmo.com/americas/research-library/the-case-for-liquid-alternatives-in-todays-environment_insights/

Main topics covered

• Why GMO sees the AI boom as a bubble investors may be able to navigate

• The difference between easy bubbles and hard bubbles in portfolio construction

• Lessons from the internet bubble, the global financial crisis and the 2021 duration bubble

• Why today’s market may be an earnings bubble, not just a valuation bubble

• How AI data center spending affects corporate profits before depreciation shows up

• Why transformational technologies do not always reward the companies building them

• The risk of circular financing, debt-funded AI spending and increasingly creative deal structures

• How IPOs, share issuance and market supply can pressure stock returns

• GMO’s seven-year asset class forecasts and why international stocks look more attractive than U.S. stocks

• Why private equity portfolios may contain large hidden bets on small, lower-quality companies

Timestamps

00:00 AI, earnings bubbles and market supply
00:58 Why Ben Inker thinks the AI bubble may be easier to navigate
02:43 What makes a bubble easy or hard for investors
08:12 Comparing risk and return in 2000, 2007, 2021 and today
14:42 Why optimizers and real clients see risk differently
17:02 What GMO learned from managing through past bubbles
19:08 How today compares to the 2000 internet bubble
20:00 Why this may be an earnings bubble
23:34 Semiconductors, memory makers and the capital cycle
25:00 How AI CapEx compares to railroads, electricity and fiber optics
29:33 Debt, circular financing and strange AI deals
34:32 Why massive stock issuance could challenge the market
40:00 How GMO builds seven-year asset class return forecasts
41:40 Why interest rates change fair value for stocks and bonds
45:32 Why international, value and small-cap stocks look more attractive
49:06 The case for a benchmark-free portfolio
55:21 What 700 leveraged buyouts reveal about private equity
01:02:00 How public portfolios can offset private equity risks
01:03:37 Why investors need to understand what they are paid for
01:08:27 Closing thoughts

Ian Smith, portfolio manager at William Blair, joins Excess Returns to break down emerging markets, global diversification, and why EM may offer a very different opportunity set than US stocks. We discuss AI capex, the role of Korea, Taiwan, China and India, the impact of the dollar, quality investing, valuation, and how active investors can think about opportunity in a world shaped by AI disruption and geopolitical change.

William Blair Investment Management
https://im.williamblair.com/

The Problem With Quality
https://im.williamblair.com/insights/articles/the-problem-with-quality

Topics covered:

• Why emerging markets are not one single trade

• How AI capex is reshaping EM indexes and performance

• Why Korea, Taiwan and China are central to the AI supply chain

• The role of the US dollar in emerging market returns

• Why EM index concentration is higher than many investors realize

• What past innovation cycles can teach us about the AI buildout

• How AI is changing the definition of quality investing

• Why China’s manufacturing strength creates both opportunity and risk

• The long-term case for India despite high valuations

• How William Blair evaluates quality, trajectory and underappreciation

• Why valuation in emerging markets requires more than simple multiples

• The one investing lesson Ian Smith would teach the average investor

Timestamps:

00:00 Intro

04:10 Why emerging markets are not one market

08:37 Why EM is underrepresented in global indexes

13:16 How the dollar impacts emerging market returns

18:37 AI capex, picks and shovels, and EM supply chains

24:17 How William Blair is using AI in the investment process

28:30 Why quality and growth have decoupled in emerging markets

33:19 Why AI disruption creates opportunity for active managers

37:30 China’s overcapacity, competition and global manufacturing edge

42:00 India’s long-term growth drivers and valuation challenge

47:00 Finding underappreciated quality in EM stocks

52:01 Deglobalization, China and the future of global trade

56:09 The one lesson Ian Smith would teach investors

Tobias Carlisle joins Excess Returns to discuss why today’s market may be setting up a major opportunity in value stocks, small caps and micro caps. We cover stretched market valuations, AI capex, SpaceX and other massive IPOs, the risk of speculative growth assumptions, and how Tobias builds systematic deep value portfolios in ZIG and DEEP.

Tobias Carlisle on X
https://x.com/Greenbackd

Acquirers Funds
https://acquirersfunds.com/

Topics covered:

• Why elevated market valuations point to lower forward returns, not necessarily an immediate exit from stocks

• The case for small value, micro-cap value and mid-cap value after a long large-cap growth cycle

• Why equal-weight indexes and small caps may be signaling a market leadership shift

• Whether AI capex will create lasting profits or mostly benefit consumers

• The parallels and differences between AI, the dot-com boom, railroads and fiber optic buildouts

• How AI spending is being financed and why the stock market may be demanding more compute investment

• What the SpaceX IPO, OpenAI and Anthropic could mean for market supply and investor psychology

• Why base rates are being challenged by the growth of major technology platforms

• How disruption can create value traps and why traditional valuation metrics can struggle in disrupted industries

• The energy demand implications of AI data centers and why nuclear and natural gas could matter

• How Tobias combines valuation, quality, financial statements and portfolio construction in ZIG and DEEP

• Why quarterly rebalancing may be a practical balance between timing luck, momentum and trading costs

Timestamps:

00:00 Why AI value may accrue to consumers
04:00 What extreme market valuations say about future returns
08:22 Small caps, equal weight and the Mag Seven reversal
14:15 AI capex and lessons from past technology booms
19:47 Who gets the profits from AI?
23:00 Cash flow, debt and the AI spending race
28:06 SpaceX, giant IPOs and market supply
31:00 OpenAI, Anthropic and Mauboussin’s base rates
35:17 Is buying the S&P 500 more speculative than investors realize?
36:57 Value investing during disruptive technology cycles
41:07 War, energy prices and the broadening trade
45:32 Semiconductor valuations and aggressive growth assumptions
47:30 How Tobias builds the ZIG and DEEP portfolios
54:17 ETF rebalancing, timing luck and systematic value investing

Professor Aswath Damodaran joins Kai Wu on The Intangible Economy to break down how to value SpaceX, AI companies, intangible assets, and the future of value investing.

We discuss why big markets do not automatically create big value, how AI CapEx is changing the character of major technology companies, and why the best investment stories still have to connect to the numbers.

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Topics covered:

• Valuing SpaceX after its IPO and why price matters even for great companies

• How Starlink, space launch, and xAI fit into SpaceX’s valuation story

• Why total addressable market can mislead investors in AI and other disruptive industries

• The problem with AI unit economics, data centers, power, water, and reinvestment needs

• Why growth can destroy value when margins and returns on capital are weak

• How intangible assets, R&D, future growth, and narratives should show up in valuation

• The Big Market Delusion and how overconfidence drives boom and bust cycles

• Why AI CapEx is different from the dot-com boom and could create broader risks

• How AI is changing the character of the Magnificent Seven and semiconductor companies

• Why value investing became rigid, ritualistic, and righteous, and how it can evolve

Timestamps:

00:00 Why great companies can still be bad investments

01:03 Introducing Aswath Damodaran and The Intangible Economy

01:49 SpaceX IPO, Starlink, xAI, and the challenge of valuing uncertainty

05:31 Why Starlink became the core of SpaceX’s current revenue

10:31 How Damodaran valued SpaceX across launch, connectivity, and AI

14:07 Why AI’s huge market may still have difficult unit economics

17:10 The tension between SpaceX competing in AI and renting data centers to competitors

20:00 Why valuation should use distributions instead of false precision

22:39 How stories and numbers work together in valuation

26:45 Why investors confuse promises, potential, and businesses

30:49 The Big Market Delusion and overconfidence in AI investing

33:02 Why the AI CapEx boom is different from the dot-com bubble

35:17 How AI infrastructure is changing the Magnificent Seven

38:36 Nvidia, Micron, semiconductors, and the risk of peak cycle earnings

41:00 Why the biggest AI market stories could be scary for society

43:37 AI disruption, labor markets, and the speed of technological change

46:30 Measuring which jobs and companies are most exposed to AI automation

49:00 Why AI cost structure may look more like Spotify than software

51:13 The unresolved business model questions for LLMs and AI agents

52:29 Why traditional value investing lost its edge

56:03 Passive investing, book value, and the blame game in value investing

58:13 Why rigid value investing is vulnerable to AI disruption

01:00:58 How value investing can adapt to intangible assets and uncertainty

01:02:21 Why any company can be a good investment at the right price

01:04:57 Why investing mistakes and track records are harder to judge than they look

In the third episode of First Principles with Andy Constan, Andy breaks down the changing structure of markets as the IPO window reopens, AI CapEx accelerates, and corporate buybacks shift toward new equity supply. We discuss what the SpaceX IPO says about capital markets, whether AI spending can create disinflationary growth, why the consumer is still holding up, and what could challenge the current market bubble.

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Follow First Principles of Apple Podcasts

Topics covered:

• Why IPOs are central to the purpose of public markets

• How Andy evaluates whether the SpaceX IPO worked

• Why issuers may want IPOs to trade higher after pricing

• The shift from stock buybacks to new equity issuance

• Why AI CapEx is changing the supply and demand for shares

• How hyperscaler spending is being funded through cash, bonds, and stock

• The economic test for whether AI investment pays off

• Disinflationary productivity growth versus labor displacement

• Why the current economy is still supported by consumption

• The role of wealth effects and consumer dissaving

• Why falling oil prices may not eliminate inflation pressure

• What Andy is watching in Fed policy, tariffs, AI CapEx, and equity issuance

• How Kevin Warsh could approach rates, QT, and the Fed balance sheet

Timestamps:
00:00 Intro and key themes
04:18 How Andy reads the SpaceX IPO
08:27 Why underwriters and regulators want IPOs to work
13:00 Why issuers may want IPOs to trade higher
17:05 From stock buybacks to new equity supply
21:06 The 600 to 700 billion dollar shift in share supply
26:42 The economic test for AI tokens
32:09 Can AI create disinflationary productivity growth?
38:10 Is AI CapEx holding up the economy?
41:00 Wealth effects, dissaving, and the consumer
45:52 Oil prices, war, and inflation
49:07 Jalen Brunson, incentives, and long-term value
52:00 Fed policy, tariffs, and what matters this summer
55:36 Kevin Warsh, QT, and the Fed balance sheet
58:42 Closing thoughts

No information on this podcast should be construed as investment advice. Securities discussed in the podcast may be holdings of the firms of the hosts or their clients.