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Let’s dive into this week’s analysis!
A quick breakdown — in case you don’t have the time.
⭐ $400B is moving from the hyperscalers to everyone else.
⭐ What skills actually make people rich?
⭐ Bank of America’s 2027 P/E multiples for the MAG7 are very encouraging.
⭐ Anthropic is winning the enterprise AI race.
Market Overview
As of Market Open 7/9/26
ETF Winners & Losers
Chart of the Week
$400B is moving from the hyperscalers to everyone else.
For years, hyperscalers like Amazon, Microsoft, Google, Meta, and Oracle generated enormous amounts of free cash flow. Semiconductor companies collected only a fraction of that amount.
Now, those lines are crossing.
Bank of America estimates that semiconductor companies could generate more than $400 billion in forward free cash flow by 2027. Meanwhile, hyperscaler free cash flow is projected to fall below zero as spending on data centers, chips, power, networking, and other AI infrastructure accelerates.
That does not necessarily mean the hyperscalers are becoming bad businesses. It means they are spending heavily today to build the infrastructure they believe will power the next decade of computing. Free cash flow is what remains after those investments.
The companies receiving that money are the semiconductor manufacturers and suppliers providing the GPUs, memory, networking equipment, and custom chips required to make AI work. In other words, cash is moving from the companies building AI platforms to the companies selling them the picks and shovels.
The long-term payoff for Big Tech could still be massive. But in the current phase of the cycle, semiconductor companies are the ones converting the AI boom into cash.
When a major investment cycle begins, follow where the money is actually going. The companies spending billions may eventually win, but the companies getting paid can win first.
We’ve seen this with Nvidia, Advanced Micro Devices, Micron, and countless other AI infrastructure names across the entire supply chain.
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In Case You Missed It…
In this week's Monday-morning episode of the Rich Habits Podcast (linked here) — Austin and Robert break down the four skills that separate people who build wealth from everyone else: sales, distribution, financial literacy, and tenacity.
Here’s what they covered…
Rich People Build Skills, Not Just Résumés — A Fidelity study found that 88% of millionaires are self-made, and the difference usually comes down to a specific skill stack — not a degree, job title, or trust fund. The skills that create wealth are learnable, stackable, and often never taught in school.
Sales Is the First Wealth Skill — Every dollar ever made started with someone convincing someone else that something was worth paying for. Sales is not about being pushy — it’s about listening, understanding someone’s problem, communicating value, and asking for the close.
Distribution Turns Income Into Leverage — Sales is one-to-one, but distribution is one-to-many. Content, personal branding, newsletters, podcasts, relationships, and partnerships allow your value to reach thousands of people without your income being capped by the hours in your day.
Financial Literacy Keeps the Money From Leaking Out — Making money and keeping money are two different skills. Austin and Robert break down the core areas that matter most: compound interest, tax strategy, debt management, asset allocation, cash flow, and the simple order of operations — match, Roth, 401(k), then taxable brokerage.
Tenacity Is the Multiplier — None of the first three skills matter if you’re unwilling to get uncomfortable. Building wealth requires rejection, risk, hard decisions, and the ability to keep going before you feel ready. The framework: ask what the worst realistic outcome is, what the best realistic outcome is, and whether you’ll regret not doing it five years from now.
Wealth is not built from one skill alone. Sales helps you create value, distribution helps you scale it, financial literacy helps you keep and grow it, and tenacity gives you the courage to actually use all three.
Here’s a link to the episode that was posted on Thursday. We switched up our scheduling this week!
You can submit questions for episodes by asking them inside of the Rich Habits Network, replying to this email, or sending us a DM on Instagram.
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Austin’s Callout
Bank of America’s 2027 P/E multiples for the MAG7 are very encouraging.
Amazon: 21.4x
Microsoft: 18.7x
Meta: 16.3x
Nvidia: 15.7x
The S&P 500 trades at 21x forward earnings right now. That means Amazon — growing revenue 10%+ annually with AWS margins expanding and an ad business printing money — trades at the same multiple as the average S&P 500 company. Microsoft, Meta, and Nvidia are all cheaper than the index. Nvidia at 15.7x is trading at a 25% discount to the broader market while delivering 50%+ revenue growth.
Think about what that actually means.
The S&P 500's 21x includes banks growing earnings at 5%, consumer staples at 3%, utilities barely moving the needle. These four companies are projected to grow earnings 15-30% annually through 2027. You're paying less per dollar of future earnings for the fastest-growing, highest-margin businesses on the planet than you are for the index that includes hundreds of mediocre growers dragging the average up.
This is the kind of disconnect that doesn't last. Either the broader market re-rates lower, or these names re-rate higher. History says it's usually the latter — high-quality compounders trading at discounts to the index tend to get bid up once the market realizes the math doesn't add up.
In 2022, people called these stocks overvalued at 30x forward earnings. Now they're at 15-21x with better fundamentals. The valuation compression already happened.
I personally bought more Nvidia earlier this week around $194 / share, and now I’m excited to add more shares of the MAGS ETF to my portfolio. That said, all of this gets thrown out the window if the forward earnings expectations are inflated and Bank of America is wrong in their projections.
Robert’s Callout
Anthropic is winning the enterprise AI race.
OpenAI may still have the most recognizable name in artificial intelligence, but Anthropic is gaining serious ground where it matters most: business customers.
Among eligible businesses measured by Ramp, Anthropic’s adoption reached 42.4% in June, surpassing OpenAI at 39.5%. That is a remarkable shift for a company that barely registered on this chart three years ago.
The speed of the move is what stands out. Anthropic’s adoption has more than doubled since the beginning of the year, while OpenAI’s growth has flattened. Google, xAI, and DeepSeek remain far behind both companies.
This is also based on actual spending, not a survey asking executives which products they plan to use. The Ramp AI Index measures corporate card and invoice-based payments across businesses on its platform. In plain English, these companies are putting money behind their decisions.
Claude has become especially popular with developers, technical teams, and businesses using AI for coding, research, analysis, and other complex work. Those customers are not simply testing a chatbot. They are building AI directly into their daily operations.
That matters because enterprise customers tend to be valuable and sticky. Once a company trains employees, connects internal data, builds workflows, and writes software around a particular model, switching becomes more difficult. The company that wins those relationships early has a chance to compound them for years.
OpenAI proved how powerful consumer attention can be. ChatGPT became the default name in AI almost overnight. But that attention was never guaranteed to last.
Anthropic improved the product, sharpened its marketing, and made Claude feel more useful, more polished, and more exciting. It shifted the broader conversation toward Claude, and business adoption followed.
Consumer attention matters enormously, but it can move faster than most people realize. Anthropic is well on its way to becoming a multi-trillion dollar company.
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