WAYT? 2-10-2026

Episode Overview

• This episode introduces the "HALO" investing framework (Heavy Assets, Low Obsolescence), arguing that the market is rotating away from asset-light software companies toward physical businesses that AI cannot replicate or disrupt.
• The hosts analyze the "Post-AI Litmus Test," a critical new method for evaluating stocks by asking whether a Large Language Model (LLM) can perform the company's core function, suggesting that software stocks face a structural threat similar to newspapers in the early 2000s.
• Key discussions include the "Gell-Mann Amnesia Effect" in financial media, the dilemma surrounding AI capital expenditures (CapEx), and how retail brokerages like Robinhood are pivoting their business models toward net interest income rather than just trading fees.
• The narrative connects broad market trends—from the saturation of the attention economy to the specific risks of "catastrophic decline" in individual stock picking—helping investors understand why broad indices are hitting highs while many popular pandemic-era stocks remain crushed.

Key Concepts

• The HALO Investing Theme: Standing for "Heavy Assets, Low Obsolescence," this concept inverts the last 15 years of market wisdom. Investors are fleeing "asset-light" businesses (SaaS/Software) in favor of companies with tangible physical assets (Energy, Industrials, Materials). The thesis is that physical products and logistics cannot be replicated by AI code, providing a defensive moat.

• The Post-AI Litmus Test: A new filter for stock selection involves asking: "Can an LLM replicate what this company makes or sells?" If the answer is yes (e.g., customer service, middle-man aggregators, basic coding), the stock is vulnerable to a permanent downward re-rating. If no (e.g., digging materials, moving freight, serving food), the stock is considered "safe."

• The "Newspaper" Trap for Software: The hosts draw a parallel between current software stocks and newspaper stocks from the early 2000s. A low P/E ratio does not make a stock "cheap" if its business model is being structurally destroyed. Just as the internet demonetized news, AI may demonetize "seat license" software models, turning them into value traps.

• The Gell-Mann Amnesia Effect in Finance: This concept explains market volatility caused by generalist panic. It occurs when experts spot errors in reporting on their own industry but blindly trust reporting on other industries. In finance, this creates opportunities when the broad market panic-sells a stock based on headlines that industry insiders know are irrelevant.

• The AI CapEx "Goldilocks" Dilemma: The market is currently struggling to price AI infrastructure spending. "Too little" spending signals a lack of innovation or fear of ROI, while "too much" spending signals margin compression and a potential data center bubble. This uncertainty is causing volatility in Mega Cap tech stocks.

• Asymmetric Risk in Stock Picking: Citing JPMorgan data, the episode highlights that 40% of individual stocks in the Russell 3000 suffer a "catastrophic decline" (70% drop) and never recover. This explains why many retail portfolios from 2021 remain underwater despite the S&P 500 hitting all-time highs; the index automatically filters out losers, while individual stock pickers remain exposed to permanent capital destruction.

• Brand vs. Aggregator Moats: In the age of AI, owning the customer relationship (e.g., Marriott/Hilton loyalty programs) is a strong defense, while being a search aggregator (e.g., Expedia) is a vulnerability. AI chatbots can replace the function of searching and aggregating, but they cannot replace the proprietary rewards systems and physical experiences offered by strong brands.

Quotes

• At 0:04:47 - "I am calling it HALO... Heavy Assets, Low Obsolescence... Just at first blush, does that pass your sniff test? Does that seem to be an accurate reflection of the stocks that are going up versus the stocks that aren't?" - Josh Brown introducing the core framework for the current market environment.

• At 0:06:42 - "Ask yourself the following... Can an LLM replicate what this company makes or sells, or can it not? ... We spent 15 years celebrating these asset-light businesses... Asset-light is what everybody wanted. High margin businesses." - Josh Brown highlighting the reversal of the "asset-light" preference that dominated the 2010s.

• At 0:11:19 - "Claude [AI] cannot give you a Diet Pepsi or a bag of Fritos." - Josh Brown providing a concrete example of "Low Obsolescence"—physical consumption cannot be digitized.

• At 0:14:26 - "One lesson from historical examples of industries facing disruption risk is that share price stability requires stability in the earnings outlook... The share prices of the group declined by an average of 95% between '02 and '09." - Josh Brown reading a note comparing current Software stocks to Newspapers in the early internet era.

• At 0:20:16 - "The thing that can fix this is time... If Adobe continues to print record numbers for another five consecutive quarters... the stock will have been a screaming buy." - Michael Batnick explaining that price drops in quality companies often require time, not just price action, to resolve investor fear.

• At 0:24:04 - "Gell-Mann Amnesia is when you see something in the newspaper that you're an expert on, and you read it and you say... 'This person has no idea what they're talking about,' and then you flip the page... and you erase your memory and you believe what you read on the next page." - Michael Batnick defining a critical concept for media literacy in finance.

• At 0:28:03 - "Those three sectors... have like most of the Halo stocks in them. They have heavy assets on their books that they own [that] cannot be replicated. They're not information businesses." - Josh Brown distinguishing between digital businesses that are vulnerable to AI disruption versus physical businesses that are insulated.

• At 0:36:10 - "A legitimate bear case for US equities is a lack of Goldilocks on hyperscaler capital spending. Meaning: too little and people get concerned that companies are worried about the return on investment. Too much CapEx and it results in an inevitable data center overbuild." - Josh Brown explaining the double-edged sword of AI infrastructure spending.

• At 0:49:59 - "They made $196 million dollars in 90 days on margin interest? ... Stock aside, this is a good business. They are printing money." - Josh Brown analyzing Robinhood's pivot to becoming a lender rather than just a trading platform.

• At 0:56:17 - "40% of all companies in the Russell 3000 had a catastrophic decline from which they never recovered... [defined as] a 70% decline from which no material rebound has ever occurred." - Michael Batnick citing data that proves why picking individual growth stocks is dangerous.

• At 1:04:23 - "People only have two ears and two eyes, and they really can only pay attention to one, maximum two things at once... You just reach a point where there are too many apps... nothing can break through anymore." - Josh Brown explaining the biological "ceiling" of the Attention Economy.

• At 1:09:03 - "Expedia is being easily disintermediated by a chatbot that finds you hotel rooms... [Marriott and Hilton] is the opposite. It's the brands driving people to the properties." - Josh Brown contrasting the high AI risk for travel aggregators vs. the low risk for travel brands.

Takeaways

• Audit your portfolio for "AI Replicability": Apply the litmus test to your holdings—if a company's primary product is code or information aggregation, acknowledge that it carries a higher risk of disruption than companies dealing in physical goods or logistics.

• Don't confuse "Cheap" with "Obsolete": Avoid buying the dip on software stocks solely because their valuations are at historic lows; ensure the business model hasn't been permanently broken by AI, similar to how newspapers were broken by the internet.

• Look for opportunities in "Insider" knowledge: When a stock drops on a headline you know is irrelevant (due to your specific industry expertise), recognize this as a potential buying opportunity created by the "Gell-Mann Amnesia" of the broader market.

• Prioritize "Loyalty" over "Aggregation": In the travel and service sectors, favor companies that own the customer loyalty (brands like Marriott) over middlemen (aggregators like Expedia), as AI chatbots will likely replace the search function of the middleman.

• Accept the math of stock picking: Understand that 40% of individual stocks suffer catastrophic, permanent declines. If you choose to pick individual stocks rather than index, you must accept that some holdings may go to zero and never recover.

• Monitor "Net Interest" for Brokerages: When evaluating financial platforms like Robinhood, look beyond trading volume. Their stability increasingly comes from margin interest and lending, making them sensitive to interest rates in ways typical tech stocks are not.

• Watch the "Broadening" signal: Do not fear a market crash just because the "Magnificent 7" stocks stall; if participation is broadening to Industrials and Financials (HALO stocks), this is historically a sign of a healthy bull market, not a top.