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Hello, Reader.

There is a common pattern in new technology cycles, and it goes like this: 

The innovation itself appears. Then, a bottleneck emerges. Next, capital floods in to solve the problem. Finally, the regime changes.  

We saw this “regime change,” or complete reorganization of stock market winners and losers, in the dot-com bust phase. 

Capital rotated out of the high-profile names and into a variety of other sectors, including base metals, precious metals, energy insurance, and utilities. Those sectors delivered solid double-digit or triple-digit returns over the early part of the 2000s, even while the Amazons, Intels, and Ciscos of the world fell 80% or more. 

Another regime change is happening now.  

Since the early AI revolution, the Magnificent Seven companies have been sitting securely on the throne. The group includes Alphabet Inc. (GOOGL), Amazon.com Inc. (AMZN), Apple Inc. (AAPL), Meta Platforms Inc. (META),Microsoft Corp. (MSFT), Nvidia Corp. (NVDA), and Tesla Inc. (TSLA).  

But their seat is soon to be usurped. We are starting to see a rotation out of some of the highest profile, high beta tech stocks and into more real-world, asset-backed sectors. 

I’ll share the name of one such company below. But first, let’s take a look at what we covered here at Smart Money last week.

Smart Money Roundup

September 16, 2026

If the Race for Smarter AI Slows, This May Be the Next Wave of Profits

In my colleague Luke Lango’s view, even if frontier AI development slows – following an Anthropic researcher’s resignation and calls from Amodei, Altman, and Musk to pace the industry – the bigger opportunity lies in applying today’s AI. He also highlights a young, private food-service robotics startup and explains how investors can back such private companies before an acquisition or IPO.

September 17, 2026

The AI Race Is Getting Harder to Predict, and That’s the Opportunity

Though the industry warns AI may be uncontrollable, investors are floating a $2 trillion valuation for Anthropic’s IPO. In other words, nobody knows which future is coming. That’s why I favor “AI Survivors” – companies that thrive whether AI accelerates, stalls, turns dangerous, or proves a bubble. Thursday’s piece shows how to invest in AI without predicting the outcome.

September 19, 2026

Not All AI Stocks Will Survive — Here’s How to Tell Which Are Likely to Fail

Two Spokane gas stations that slashed prices to 59 cents a gallon, losing thousands, offer a vivid example of what Tom Yeung calls a “bad business model,” in which selling identical products destroys profits. He argues the same commoditization is squeezing AI, pointing to GPU-rental “neoclouds” alongside interchangeable model makers and power producers. Read more about the winners with real pricing power who could survive the squeeze.

September 20, 2026

How an AI Slowdown Could Spark a Robotics Boom

Fresh from the All-In Summit – where he heard from Nadella, Huang, Musk, and President Trump – Luke Lango came away more bullish on AI. After witnessing no signs of slowing infrastructure, he argues robotics could be a major beneficiary, using Agility Robotics’ safety-focused Digit 5 to illustrate what turns an impressive machine into a repeat customer. The private company he’s backing could open a far bigger opportunity – see why before the deadline at midnight.

The AI-Powered Copper Play

Freeport-McMoRan Inc. (FCX), a metals mining company with a focus on copper, is maximizing this regime-change opportunity by boosting copper production in every way possible. For example, the company has developed cost-effective methods for extracting commercial quantities of copper from waste rock through advanced leaching techniques. 

Freeport uses AI to optimize ore sequencing, mill throughput, equipment uptime, and geological modeling across massive copper operations. Algorithms improve recovery rates, reduce energy consumption, and minimize downtime. 

Because mining is capital intensive and operationally complex, small efficiency gains can scale into enormous dollar impact. AI helps Freeport decide which rock to move, how fast to process it, and when to service machinery. 

The company also applies machine learning to geological data, improving reserve estimates and guiding long-term mine planning. 

This is applied intelligence in its purest form: more output from the same ore body, with fewer people and lower costs. 

I believe “asset-heavy” companies, like Freeport, will rise in rank as Big Tech household names continue to fall.

Regards,

Eric Fry