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💍 Oura is going public

Oura started as a niche sleep tracker and has become one of the breakout consumer health products of the decade.

It still looks like a hardware company. But the S-1 tells a more interesting story.

Revenue surged 74% Y/Y to $1.2 billion in the first nine months of FY26, which ends in September. The company is profitable, and 5 million members now pay for the software layer attached to the ring.

The main question is whether Oura remains a hit hardware vendor or successfully scales into an enduring consumer health platform.

I condensed 300+ pages of the S-1 into a clean breakdown, supported by our signature visuals. By the end, you'll have a clear view of the Oura investment case.

Today at a glance:

1. Overview

2. Business Model

3. Financial highlights

4. Risks & Challenges

5. Management

6. Use of Proceeds

7. Future Outlook

8. Personal Take

1. Overview

Oura was founded in Finland in 2013 around a simple idea: the finger is a particularly good place to measure the body.

Compared with the wrist, Oura says the finger can provide a much stronger photoplethysmography signal, helping improve measurements such as heart rate and heart rate variability. The ring form factor also encourages continuous wear.

The basics

• Headquarters: San Francisco, California

• Ticker: OURA (Nasdaq)

• Mission: Empower people to live healthier, longer

• Latest product: Oura Ring 5, launched June 2026

Oura has evolved from a sleep-and-recovery tracker into a broader health wearable covering more than 50 health and wellness metrics, including activity, stress, heart health, metabolic health, and women’s health.

That expansion has helped turn smart rings from a niche product into a meaningful wearable category.

Still small in wearables

Oura sold 3.6 million rings in the 12 months through June 2026, compared with approximately 212 million wearable devices shipped globally.

That’s only around 2% of global wearable shipments.

Who wears Oura?

I don’t own an Oura Ring myself. I lift weights regularly, and having to take a ring off during strength training undermines some of the appeal of an always-on fitness tracker for me. But living in San Francisco, it sometimes feels like every woman around me does. And the S-1 actually backs that up:

• 72% are women

• 73% are 45 or younger

• 63% report household income above $100,000

• More than half report at least one chronic condition

What’s particularly interesting is that Oura isn’t replacing smartwatches.

For many users, the ring is creating a new slot on the body rather than fighting directly for the wrist. Many members either had no previous wearable or continue wearing another alongside it.

Takeaway: Oura has already built meaningful scale, but it still represents only a small fraction of global wearables. Oura’s runway depends less on stealing smartwatch share than on making smart rings a much larger category.

2. Business Model

Oura makes money in two ways:

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Today at a glance:

1. 📈 Broadcom: AI Target Jumps

2. 💻 Dell: Margins Catch Up

3. 📡 HPE: Juniper Starts Paying Off

4. 🌱 MongoDB: Enterprise Advanced Roars Back

5. ☁️ Zscaler: Usage Revenue Takes Off

6. 🌐 Samsara: Large Deals Accelerate

7. 🧘🏻 Lululemon: Leggings Lose Ground

8. ✍️ DocuSign: IAM Hits 15% of ARR

9. ⚡️ NIO: Margins Hold Up

10. 🤖 UiPath: AI Reaches 18 of Top 20 Deals

11. 🛠️ GitLab: Bookings Break Out

12. 📝 Asana: AI Hits 25% of New ARR

1. 📈 Broadcom: AI Target Jumps

Broadcom Q3 revenue (July quarter) surged 86% Y/Y to $29.6 billion ($160 million beat), with non-GAAP EPS of $3.32 ($0.08 beat).

• Semiconductor solutions as a whole grew 127% to $20.8 billion, driven by AI semiconductor revenue, which jumped 221% Y/Y and 54% Q/Q to $16.7 billion, exceeding the $16 billion outlook from last quarter.

• Infrastructure software also accelerated to 29% growth at $8.8 billion.

The bigger news was the forward reset for next year. Broadcom now expects $115 billion of AI semiconductor revenue in FY27, up from the $100 billion target that disappointed investors in Q2, followed by an extraordinary $230 billion in FY28. Q4 AI revenue is expected to reach $21.7 billion, up 236% Y/Y, another acceleration.

The customer mix includes the usual suspects. Anthropic is expected to become Broadcom’s largest custom XPU customer in FY27, with OpenAI potentially second, while Google remains a multi-tens-of-billions annual business. Meta is also ramping across multiple chip generations. Management says demand from its four largest AI customers continues to exceed what Broadcom can physically supply.

That bottleneck is prompting more vertical integration. Broadcom is bringing substrate production online in Singapore in FY27 while scaling networking alongside custom compute, including its new 200 Tbps Tomahawk 7 Ethernet switch.

Bottom Line: Q2 left investors wondering whether management was sandbagging with its $100 billion FY27 AI target. Now we know, with a $15 billion raise after just one quarter. The $230 billion FY28 outlook implies AI semiconductor revenue nearly quadrupling from FY26 in just two years. Now it’s all about how quickly Broadcom can secure enough capacity to satisfy that demand.

2. 💻 Dell: Margins Catch Up

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Software Strikes Back: Part Deux

For the past two years, software investors have worried that AI would eat into seats, pricing, and eventually the software model itself.

This week, Palo Alto Networks and Snowflake showed the other side of that trade.

Palo Alto is seeing AI create more identities, traffic, and attack surfaces to secure. Snowflake is seeing AI workloads drive more consumption across the data platform.

In both cases, AI is driving more usage across the software stack.

Today at a glance:

1. ☁️ Palo Alto: AI Security Comes Together

2. ❄️ Snowflake: AI Fuels Consumption

1. ☁️ Palo Alto: AI Security Comes Together

Palo Alto closed Q4 FY26 (ending in July) with revenue up 34% Y/Y to $3.4 billion ($60 million beat), while non-GAAP EPS reached $1.02 ($0.04 beat).

Acquisitions still make the headline growth rate messy, but the underlying demand indicators were strong. Palo Alto added a record $970 million of net new Next-Gen Security ARR, while landing roughly 220 net new platformizations, up 44% and twice the Q3 pace. If you recall, platformization is the fancy word for multi-product adoption.

Palo Alto finished FY26 with a 38% adjusted free cash flow margin, essentially preserving its high-30s profitability while absorbing two major acquisitions (CyberArk and Chronosphere).

The GAAP numbers weren’t as pretty. Palo Alto swung to a $282 million net loss, but this was mostly accounting noise driven by one-off acquisition adjustments. The quarter notably included a $524 million mark-to-market charge related to CyberArk convertible notes, along with $281 million of acquired intangible amortization and $487 million of stock-based compensation.

FY27 revenue guidance of $14.1–$14.2 billion implies 23%–24% growth and came in above consensus, while management expects NGS ARR to grow 22%–23% to reach ~$11.1 billion and maintained its 38% adjusted FCF margin target.

Management also reaffirmed its 40%+ adjusted free cash flow margin target for FY28 and $20 billion NGS ARR target for FY30.

The central question for investors is whether this M&A spree creates genuine platform synergies. Early cross-sell data suggests it is.

Platformization Accelerates

Next-Gen Security ARR reached $9.1 billion, up 63% Y/Y, while remaining performance obligations climbed 34% to a record $21.2 billion. Those growth rates still benefit heavily from CyberArk and Chronosphere, so they shouldn’t be read as organic growth.

But Palo Alto provided another useful lens for FY26:

• Network & AI Security revenue: +17% Y/Y.

• Cortex revenue: +25%.

• Idira (CyberArk rebranding) revenue: +21% on a pro forma basis.

In other words, each major platform is growing at a healthy double-digit rate.

More importantly, customers are consolidating more spending with Palo Alto. Net retention among platformized customers remained above 120%. More than 65% of NGS ARR now comes from platformized customers.

Palo Alto’s customers spending more than $5 million in NGS ARR rose 45% Y/Y to 223, while customers above $10 million increased 50% to 78. One Q4 telecom deal alone was worth $126 million and combined firewalls, SASE, Idira, and Cortex XSIAM.

AI security stack comes together

AI agents generate machine-to-machine traffic, access credentials, query internal data, and increasingly take actions autonomously. Palo Alto says agentic traffic across SASE has increased more than 9x in nine months. That makes AI both a new attack surface and a catalyst for upgrading legacy security infrastructure.

Palo Alto is building around three main layers:

• Prisma AIRS: Secure the AI. ARR reached roughly $120 million only one year after launch, making it Palo Alto’s fastest-scaling product. Customers jumped from more than 300 in Q3 to more than 800 in Q4. AIRS now spans runtime security, agent identities, red teaming, observability, and agent gateways.

• Cortex: Detect and respond. XSIAM ARR surpassed $700 million, up roughly 70% Y/Y, with close to 1,000 customers. Chronosphere’s observability ARR also crossed $500 million, more than 2.5x its level just two quarters ago. Half of Chronosphere’s Q4 net-new logos included an XSIAM cross-sell, showing Palo Alto is already plugging the acquisition into the broader platform.

• Idira: Control identity and access. The $25 billion CyberArk acquisition gives Palo Alto control over the credentials and permissions used by humans, machines, and AI agents. Early cross-selling is encouraging: CyberArk ACV grew 27% Y/Y, Palo Alto generated more than 200 CyberArk new-logo wins from its existing installed base, and shared leads between the two sales organizations have increased by roughly 50% since May.

That creates a fairly simple architecture: AIRS secures AI applications and agents, Cortex detects and responds when something goes wrong, and Idira controls what they can access.

But wait! There’s one more layer: autonomous action. Alongside earnings, Palo Alto announced the acquisition of Console, an AI-native platform that lets users build agentic workflows using natural language. The goal is to move Cortex beyond surfacing security issues toward agents that can investigate and remediate them automatically.

In CEO Nikesh Arora’s words, this is the shift toward “software-as-an-agent.”

Takeaway: Palo Alto is starting to show that its acquisition spree is creating something bigger than the individual parts. Platformization is accelerating, AIRS is scaling rapidly, and CyberArk and Chronosphere are already cross-selling into the broader platform. AI is becoming both a demand catalyst and a real revenue stream. The main challenge ahead is justifying a much richer valuation. The stock has roughly doubled since we last added to our PANW position in App Economy Portfolio in March.

2. ❄️ Snowflake: AI Fuels Consumption

Snowflake’s growth acceleration is no longer looking like a one-quarter blip.

Product revenue surged 37% Y/Y to $1.49 billion, up from +34% Y/Y last quarter and +30% two quarters ago. Total revenue rose +35% Y/Y to $1.55 billion ($70 million beat), while non-GAAP EPS was $0.62 ($0.17 beat).

Management also raised FY27 product revenue guidance by $230 million to $6.07 billion, lifting expected Y/Y growth to 36%.

So if we zoom out, the FY27 product revenue growth outlook has moved from 27% to 31% to 36% in the past six months. And there might be more acceleration ahead. Q3 guidance calls for 37%–38% product revenue growth, slightly faster than Q2.

CEO Sridhar Ramaswamy revealed on the call that AI products directly explain roughly half of Snowflake’s recent growth acceleration. But AI’s true impact may be larger because it is also accelerating migrations and increasing consumption across the core data platform.

The quarter in numbers

• Net revenue retention: 126% (+1pp Y/Y).

• $1M+ customers: 828 (+27% Y/Y).

• Remaining performance obligations: $9.0 billion (+30% Y/Y).

• Non-GAAP operating margin: 15% (+4pp Y/Y).

• GAAP operating margin: -17% (+13pp Y/Y).

RPO remains the softer metric, dipping sequentially from $9.2 billion to $9.0 billion despite 30% Y/Y growth. Some of that reflects Q2 renewal seasonality and faster burn-down as customers consume ahead of contractual schedules. In a consumption model, actual platform usage and product revenue remain cleaner indicators of business health.

The gap between GAAP and adjusted margins remains enormous because Snowflake still relies heavily on stock-based compensation, which accounted for 27% of revenue. Still, that ratio is down 12 percentage points Y/Y. The absolute level remains high, but the direction is clearly improving.

AI fuels the core business

Cortex Code (CoCo) surpassed 9,100 accounts, adding more than 2,000 during the quarter, while CoWork expanded to 5,800 accounts.

These products enable direct AI consumption, but the bigger opportunity lies in the second-order effect.

Customers need more governed data available to their AI applications. More users can interact with that data through conversational interfaces. Agents can increasingly retrieve information, analyze it, and take actions. Each additional workload increases Snowflake consumption.

AI is also helping Snowflake bring workloads onto the platform faster. Coding models can automate parts of legacy migrations that historically required large teams and months or years of manual rewriting.

So AI creates new workloads, but also makes it easier to move onto Snowflake in the first place. That helps explain why the core business is accelerating alongside the AI portfolio rather than being cannibalized by it.

The customer data supports the same story. Snowflake added 692 net new customers, up 32% Y/Y, indicating strong momentum.

A total of 65 customers now generate more than $10 million in trailing annual product revenue, up from 45 a year ago. In a consumption model, that expansion matters. Snowflake needs customers to keep discovering new ways to use their data. AI is giving them just that.

The gross margin tradeoff

Snowflake lowered its FY27 non-GAAP product gross-margin outlook from 75% to 74%, partly because AI products carry additional model and inference costs. But operating-margin guidance moved in the opposite direction, rising from 13.5% to 14.5%. This confirms continued operating leverage alongside accelerating top-line growth.

In other words, Snowflake is choosing to absorb some near-term AI costs while the broader platform scales.

Takeaway: Snowflake’s AI thesis is moving from defense to offense. This quarter showed that AI can make that governed data layer more valuable. Product growth has accelerated from 30% to 37% in two quarters, and operating margins are expanding at the same time. So far, Snowflake looks increasingly like one of the software companies where AI expands consumption rather than cannibalizing it.

That’s it for today!

Happy investing!

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Disclosure: I own PANW and CRWD in App Economy Portfolio. I share my ratings (BUY, SELL, or HOLD) with App Economy Portfolio members.

Author's Note (Bertrand here 👋🏼): The views and opinions expressed in this newsletter are solely my own and should not be considered financial advice or any other organization's views.

Over 300,000 subscribers turn to us for business and investment insights.

🔥 The August report is here, with over 100 businesses visualized!

All the key earnings from the past month in one report.

• ✔️ Cut through the noise with clear, concise financial snapshots.

• ✔️ See revenue trends, profit margins, and key takeaways instantly.

Download the full report below or log in to your account.

Here’s a sneak peek. 👀

What to expect in our monthly report?

🤖 Big Tech & AI

• New IPOs: SpaceX, Cerebras

• Hardware: Sandisk, HP, Lenovo

• Chip Design: NVIDIA, AMD, ARM

• Infrastructure: Arista, Cisco, CoreWeave, Nebius

💳 Fintech & Commerce

• Gig Economy: Uber, DoorDash, Grab, Instacart

• Digital Banking & Lending: Nu, Klarna, Affirm, Chime

• Merchant Software & Payments: Intuit, PayPal, Block, Toast

• Global Commerce: MercadoLibre, Alibaba, PDD, Sea, Shopify

🧠 Enterprise & Data Intelligence

• Data & AI: Palantir, Datadog, Elastic

• Productivity: HubSpot, Veeva, Zoom, Monday

• Software Stack: Salesforce, Workday, Atlassian, Figma

• Cybersecurity: CrowdStrike, Cloudflare, SentinelOne, Rubrik

🍿 Media & Entertainment

• Streaming: Disney, Warner Bros., Paramount, FOX, Spotify

• Gaming: Tencent, NetEase, Nintendo, Sony, Take-Two

• Social & Ads: Snap, Pinterest, Match, AppLovin

• Sports betting: DraftKings, Flutter

🛍️ Consumer Brands

• Retail: Walmart, Target, Best Buy, Home Depot, Lowe’s

• Big Pharma: Lilly, Novo Nordisk, Pfizer, Merck, Amgen

• Travel: Booking, Airbnb, Expedia, Marriott, Tripadvisor

• Restaurants: McDonald’s, RBI

Download the full report👇

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• 💻 CrowdStrike, Salesforce

• 💰 Wall Street’s Top Stocks in Q2

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PRO members get everything PLUS:

• 📩 Saturday PRO reports: Timely insights on the latest earnings.

Today at a glance:

1. 📶 Marvell: Custom Silicon Breakout

2. 📦 PDD: Growth Slows Again

3. ✅ Intuit: DIY Price Reset

4. 🧠 Synopsys: EDA Reaccelerates

5. 🏗️ Autodesk: MaintainX Lands Cleanly

6. 👔 Workday: AI Mix Jumps

7. 🧑‍⚕️ Veeva: Falcon Lands Early Adopters

8. 🖥️ Zoom: Enterprise Momentum Returns

9. 🌈 Affirm: Growth Meets Leverage

10. 🔐 Okta: Agent Deals Arrive

11. 🔷 Rubrik: ARR Picks Up

12. 🛒 Best Buy: PC Prices Do The Work

13. ☁️ Nutanix: Hardware Workarounds Scale

14. 🔍 Elastic: AI Penetration Jumps

15. 🏥 HealthEquity: Margins Keep Climbing

1. 📶 Marvell: Custom Silicon Breakout

Marvell Q2 FY27 revenue (ending August 1st) rose 37% Y/Y to a record $2.74 billion ($30 million beat), with non-GAAP EPS of $0.94 ($0.01 beat).

Data Center revenue jumped 46% to $2.17 billion, representing 79% of total sales, as demand for AI infrastructure remained exceptionally strong.

Custom silicon should bring the next leg of growth. Management expects a significant acceleration beginning in H2 FY27, followed by custom silicon revenue more than doubling in FY28 as hyperscalers increasingly design their own AI chips. Marvell also expanded its partnership with Google across AI accelerators, storage, networking, and near-memory compute, backed by a six-year warrant agreement.

Connectivity remains a major driver. Demand for optical interconnects is accelerating as AI clusters require more bandwidth, while Marvell called its CXL memory-expansion business a “home run” with deployments across multiple hyperscalers.

Marvell now expects FY27 revenue of roughly $12 billion (up from $11.5 billion previously) and raised its FY28 target to $18 billion (up from $16.5 billion). Q3 revenue guidance of $3.15 billion was also well ahead of consensus and implies another ~15% sequential jump.

Bottom Line: Marvell’s AI story is broadening from connectivity into custom compute. With custom silicon set to accelerate sharply, management is raising expectations faster than the current quarter alone would suggest. But expectations are already enormous: the stock trades over 50x forward earnings, and much of the Google opportunity through FY28 was already embedded in guidance. That helps explain why shares fell despite Marvell raising both FY27 and FY28 outlooks.

2. 📦 PDD: Growth Slows Again

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NVIDIA keeps outrunning the law of large numbers

The company just crossed $96 billion in quarterly revenue, with growth accelerating above 100%. Management now expects revenue to grow another 70% next year, adding more than $200 billion in annual revenue. At this scale, that should sound almost implausible. Yet even that outlook is supply-constrained.

But the story is also getting more complicated. NVIDIA is helping finance the infrastructure its customers need, while some of those same customers are developing competing chips of their own.

So the debate now comes down to two questions:

• How long can the AI infrastructure boom keep compounding?

• How much of it can NVIDIA continue to capture?

Today at a glance:

1. NVIDIA’s Q2 FY27

2. Business highlights

3. Key quotes from the call

4. What to watch moving forward

1. NVIDIA Q2 FY27

NVIDIA’s fiscal year ends in January, so the July quarter was Q2 FY27.

Data Center revenue remains off the charts, as illustrated below.

Income statement:

• Revenue accelerated 106% Y/Y to $96.2 billion ($4.1 billion beat).

  • Data Center +117% Y/Y to $89.0 billion.

  • Edge Computing +27% Y/Y to $7.2 billion.

• Gross margin was 75% (+3pp Y/Y).

• Operating margin was 66% (+5pp Y/Y).

• Non-GAAP EPS was $2.22 ($0.13 beat).

Cash flow:

• Operating cash flow +57% Y/Y to $24.1 billion.

• Free cash flow +59% Y/Y to $21.3 billion.

Balance sheet:

• Cash and marketable securities: $99.4 billion.

• Debt: $33.4 billion.

Q3 FY27 Guidance:

• Revenue +12% Q/Q and +89% Y/Y to $108.0 billion ($3.4 billion beat).

• Gross margin 74% (-1pp Q/Q).

• Guidance assumes no Data Center compute revenue from China.

So, what to make of all this?

• 🚀 Growth accelerated again: Revenue growth jumped from 85% in Q1 to 106% in Q2, while Data Center accelerated from 92% to 117%. NVIDIA added nearly $15 billion of revenue sequentially, and Q3 guidance calls for another $12 billion.

• ☁️ Demand is broadening: Hyperscale revenue reached $48.7 billion, while AI Clouds, Industrial, and Enterprise grew even faster to $40.3 billion. NVIDIA is increasingly benefiting from neoclouds, enterprises, and sovereign AI alongside Big Tech.

• 🔄 Rubin is arriving without a digestion pause: Blackwell Ultra is still ramping, yet Rubin shipments have already started. So far, each new architecture is layering onto the previous one rather than creating an air pocket.

• 📉 Margins are finally bending: Gross margin is expected to fall from 75% in Q2 to 74% in Q3 and roughly 71%-72% in Q4, largely because of higher memory costs. The pressure appears supply-driven rather than a sign of weaker demand or pricing.

• 🧱 NVIDIA is locking up supply: Supply and capacity commitments jumped from $119 billion to $279 billion in three months, largely to secure memory. That's a huge vote of confidence in future demand—and a much larger commitment if the cycle eventually slows.

• 🔮 The outlook remains extraordinary: NVIDIA expects roughly 70% revenue growth in FY28, far above prior Wall Street expectations. If that holds, the AI infrastructure cycle is still expanding rapidly despite NVIDIA already operating at enormous scale.

Big picture: Growth accelerated, demand broadened, and Rubin is arriving before Blackwell has slowed. The main new wrinkle is that sustaining this pace is becoming more expensive, with memory costs pressuring margins and supply commitments rising rapidly.

2. Business highlights

⚡ Rubin raises the value of a gigawatt

NVIDIA is capturing more revenue from every AI factory generation.

Management estimates its revenue opportunity per gigawatt keeps increasing:

• ~$18 billion per gigawatt with Hopper.

• ~$25 billion per gigawatt with Blackwell.

• And now ~$40 billion per gigawatt with Vera Rubin.

Rubin combines GPUs, CPUs, networking, and software to deliver 30x higher throughput per megawatt and 35x lower token costs than Grace Blackwell Ultra.

Production shipments have already started, with purchase orders from every major hyperscaler, AI cloud, and system OEM.

🏦 NVIDIA becomes an AI financier

NVIDIA has invested nearly $50 billion in frontier AI labs and partnered with major financial institutions to help raise more than $500 billion of third-party capital for AI infrastructure.

It is also using credit support and take-or-pay commitments to help AI labs and neoclouds finance capacity. Critics call this circular financing. NVIDIA argues it is simply removing a capital bottleneck for customers whose demand is growing faster than their balance sheets.

Either way, NVIDIA is moving beyond selling infrastructure to helping make that infrastructure possible. There may also be a strategic benefit: financing infrastructure today can help lock in NVIDIA deployments before competing silicon reaches scale.

🤗 NVIDIA agrees to buy Hugging Face

According to The Information, NVIDIA has agreed to acquire Hugging Face for $12.9 billion, nearly triple its 2023 valuation.

Hugging Face is one of the main hubs for developers to discover, share, and deploy open AI models, often dubbed the “GitHub of AI.” With only about $150 million in annual revenue, NVIDIA is clearly buying strategic positioning rather than near-term profits.

The logic ties directly to Jensen’s argument on the call: NVIDIA benefits whenever AI models proliferate. Open models are particularly attractive because startups and enterprises generally don’t build custom chips and overwhelmingly rely on existing compute infrastructure.

Owning Hugging Face would move NVIDIA one layer closer to developers and tighten the link between open-model adoption and its broader computing platform. The risk is that NVIDIA ownership could weaken the neutrality that helped make Hugging Face so valuable in the first place.

3. Key quotes from the earnings call

Check out the earnings call transcript on Fiscal.ai here.

CEO Jensen Huang:

On custom chips:

“Whereas many of these XPUs are inference-specific chips for one cloud or one service, NVIDIA is a platform, an entire AI factory platform that spans the entire AI life cycle that you can use in any cloud. It’s in every cloud. You can run anywhere. [...] I have 100% confidence that our technology will continue to be extraordinary for them and that the economics of using our technology, whether it’s from data processing to training, to post-training, to agentic processing, our technology’s going to be extraordinary for them.”

This is Jensen’s answer to OpenAI’s Jalapeño and the broader custom-silicon threat. His argument isn’t that customers won’t build their own chips. It’s that those chips tend to optimize specific workloads, while NVIDIA’s advantage is a fungible platform spanning training, inference, networking, CPUs, and multiple clouds. The question is whether that breadth remains valuable enough to justify NVIDIA’s premium economics.

On what happens when AI becomes agentic:

“When the world goes to agentic, fully agentic systems, you are going to have agents running all the time, working with other agents running all the time. [...] I think the most important thing that matters for the industry is that, one, AI is now doing productive and useful work. Two, AI is generating profitable tokens. Three, if we had more compute, we could generate more profitable tokens, which results in more profit for all of the services. This is the exact phase where we are at, which is the reason why everybody is leaning in.”

Today’s AI is still largely triggered by humans. Jensen believes the next phase involves millions of agents operating continuously and interacting with other agents. If that happens, inference demand stops being directly tied to human usage, and the amount of compute required could increase dramatically.

4. What to watch next

NVDA is up roughly 20% YTD, still outperforming the S&P 500.

Even after the post-earnings jump, the stock trades at only about 20x forward earnings, well below the multiple it commanded earlier in the AI boom and below the rest of US Big Tech.

The latest 13F filings for Q2 2026 showed that hedge funds are not accumulating NVDA as much as they used to. The stock remains one of the most widely held names, although many funds are still underexposed relative to its 8% weight in the S&P 500.

At that valuation, the debate is less about whether NVIDIA looks cheap today and more about how durable these extraordinary earnings can be.

In semiconductors, a low P/E can sometimes signal peak earnings rather than a bargain. The multiple may be compressed precisely because the market is questioning whether today’s profitability is sustainable. So far, that skepticism has been repeatedly proven wrong.

Here’s what I’m watching:

• Custom silicon: OpenAI just published the first results for Jalapeño, its custom inference chip. The company says it delivered 1.5x-1.9x more throughput per watt and materially lower latency than the NVIDIA systems tested across several models. OpenAI still plans to use NVIDIA broadly, but Jalapeño shows that NVIDIA’s largest customers have a growing incentive to move specialized inference workloads onto their own silicon.

• Circular financing: NVIDIA says AI labs receiving some form of balance-sheet support could account for roughly one-quarter of its business next year. Financing customers does not make the underlying demand fake, but it increases NVIDIA’s exposure if AI labs eventually struggle to monetize the infrastructure they are building.

• Margins and supply: Memory scarcity is expected to push gross margin down before price increases help it recover next year. The question is whether NVIDIA can continue securing sufficient supply to meet extraordinary demand without sacrificing too much of its economics.

📉 The bear case is that AI infrastructure spending eventually outruns the profits it can generate, while custom silicon takes a growing share of inference.

📈 The bull case is that agentic AI keeps expanding compute demand faster than efficiency gains and competition can reduce it.

So far, NVIDIA is still winning that race.

That’s it for today!

Happy investing!

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Thanks to Fiscal.ai for being our official data partner. Create your own charts and pull key metrics from 50,000+ companies directly on Fiscal.ai. Save 15% with this link.

Disclosure: I own AAPL, AMD, AMZN, GOOG, META, MSFT, and NVDA in App Economy Portfolio. I share my ratings (BUY, SELL, or HOLD) with App Economy Portfolio members.

Author's Note (Bertrand here 👋🏼): The views and opinions expressed in this newsletter are solely my own and should not be considered financial advice or any other organization's views.

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Software finally had a good night

Investors have spent much of the year questioning whether AI will accelerate software growth or slowly eat into it.

On Wednesday, two of the industry’s biggest names gave them something else to think about.

CrowdStrike delivered record net new ARR and raised its outlook again. Salesforce posted its strongest new business growth in four years and pointed to organic revenue reacceleration ahead. Both stocks surged more than 10% after hours.

But the more interesting part is where the growth is showing up and what the market may have missed by lumping all software into the same basket.

Today at a glance:

• 🦅 CrowdStrike: What Doesn’t Kill It

• ☁️ Salesforce: SaaSpocalypse Pushback

🦅 CrowdStrike: What Doesn’t Kill It

For years, the CrowdStrike investment thesis has been that every new threat makes Threat Graph, the AI brain behind Falcon, smarter. The past two years suggest something similar about the company itself.

In July 2024, a faulty update caused one of the largest IT outages in history and put customer trust under extraordinary pressure. Two years later, CrowdStrike just delivered what CEO George Kurtz called the best quarter in company history.

Revenue grew 26% Y/Y to $1.47 billion ($30 million beat), marking the fifth consecutive quarter of acceleration, while non-GAAP EPS reached $0.31 ($0.02 beat).

Non-GAAP operating income jumped 46% to a record $372 million, a 25% margin, while free cash flow reached a Q2 record $377 million, up 33% Y/Y.

The GAAP picture remains less flattering, with the company still showing an operating loss margin of 2%. The main reason was stock-based compensation, which accounted for roughly 26% of revenue.

The recurring-revenue engine remains the main KPI:

• Ending ARR grew 25% Y/Y to $5.84 billion, continuing a remarkably predictable trajectory.

• Net new ARR reached an all-time record $333 million, up 51% Y/Y, accelerating sharply from +32% last quarter. New-logo net new ARR also hit a record, while both gross and net retention improved, showing that the acceleration extends beyond existing customers buying more modules.

The Flex Flywheel

Ending ARR from Flex customers surged 101% Y/Y to $2.29 billion, already approaching 40% of CrowdStrike’s total ARR. More than 935 accounts adopted Flex during the quarter.

Customers moving to Flex increased ending ARR by roughly 40% on average, while platform adoption continued to deepen.

The appeal of Flex is simple: customers commit a security budget upfront and can deploy it across Falcon modules over time, making it easier for CrowdStrike to consolidate more security workloads onto a single platform.

AI Creates More to Secure

The Mythos moment we discussed last quarter is also becoming clearer in the numbers.

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Today at a glance:

1. 🛒 Walmart: Digital Outruns Stores

2. ⚙️ Analog Devices: Grid-to-Chip Breakout

3. 🎮 NetEase: Evergreen Games Deliver

4. 🎯 Target: Traffic Holds Up

5. ⛷️ Amer Sports: Wilson Joins In

6. 💳 Klarna: GMV Reset

1. 🛒 Walmart: Digital Outruns Stores

Walmart Q2 FY27 revenue rose 6% Y/Y to $187.9 billion ($1.1 billion beat), with adjusted EPS of $0.81 ($0.07 beat). Walmart US comps slowed to 2.6%, the weakest growth in more than six years and below the 3.7% consensus, sending shares sharply lower. Transactions still grew 1.5%.

The headline slowdown is somewhat misleading. New federal drug-pricing rules created a roughly 125 bps drag on US comps. Excluding Health & Wellness, comps grew 3.4%. Walmart also used some of its tariff refunds to cut prices on more than 11,000 items. The company continues gaining share, particularly in grocery and among higher-income households.

Meanwhile, the businesses increasingly driving Walmart’s economics remain much stronger than store sales:

• Global e-commerce grew 23%.

• Advertising surged 38%.

• Membership fee revenue increased 17%.

Walmart US e-commerce has now grown above 20% for 10 consecutive quarters, with profitability improving as stores increasingly function as fulfillment hubs rather than simply physical retail locations.

Fuel remains a challenge, with FY27 incremental fuel costs now expected above $2 billion. Walmart is also expected to continue reinvesting tariff refunds into lower prices, contributing to Q3 adjusted EPS guidance of $0.62–$0.64, which is below consensus.

Despite that reinvestment, Walmart raised FY27 sales growth guidance to 4%–5% (from 3.5%–4.5%) and adjusted operating income growth to 7%–8.5% (from 6%–8%).

Bottom Line: Slower US comp reflects pharmacy pricing rather than lost share. The more important shift continues underneath, with e-commerce, advertising, membership, and marketplace growing far faster than traditional stores. Walmart increasingly looks less like a retailer with digital businesses attached and more like an omnichannel platform funded by retail.

2. ⚙️ Analog Devices: Grid-to-Chip Breakout

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Alibaba’s AI bet is starting to show up in the numbers

Revenue rose 9% Y/Y to $39.6 billion, while Cloud accelerated to 45% growth, its fastest pace in more than five years. AI-related product revenue grew triple digits for the 12th consecutive quarter, and Cloud adjusted EBITA more than doubled as margins expanded.

The trade-off remains expensive (a familiar theme across Big Tech this earnings season). Alibaba spent almost $10 billion on CapEx during the quarter, up 75% Y/Y, while free cash flow was a $6.6 billion outflow. Adjusted EBITA also fell by 30% as the company continued to invest in AI infrastructure, models, and applications.

This quarter offered the clearest glimpse of the potential return on these AI investments, and management put a three-year payback timeline on its compute buildout.

Revenue breakdown:

• 🛒 China E-commerce: $16.3 billion, down 8%.

• 🛵 Quick Commerce: $7.9 billion, up 45%.

• 🌍 International Commerce: $6.1 billion, up 1%.

• ☁️ AI Cloud & Compute: $7.1 billion, up 45%.

• 🤖 AI Apps & Others: $4.9 billion, up 3%.

Alibaba overhauled its reporting segments this quarter. Quick Commerce now stands apart from legacy China e-commerce, while Alibaba Cloud absorbed the T-Head chip division.

The 8% Y/Y decline in China E-commerce reflected weaker marketplace activity and Alibaba’s continued pullback from some direct-sales businesses.

Overall revenue rose 9% Y/Y, but it came with another step down in profitability. Operating margin fell to 6% from 14% a year ago, while adjusted EBITA declined 30% to $4.0 billion as Alibaba kept investing across AI and commerce.

Alibaba is getting faster growth from the businesses it is funding most aggressively, but the cost of building them remains visible across margins and cash flow. The company is maintaining its 380 billion yuan (~$56 billion) three-year AI investment plan.

☁️ The AI payback

Alibaba Cloud delivered its strongest growth in more than five years, with revenue rising 45% Y/Y to $7.1 billion. AI-related products now account for roughly 35% of external Cloud revenue, up from 30% last quarter.

The acceleration is finally driving operating leverage. Cloud adjusted EBITA jumped 133% Y/Y to $830 million, expanding segment margins to roughly 12%, a notable milestone given how aggressively capacity is scaling.

Management says demand for AI compute still exceeds supply, which explains much of the current spending cycle. This quarter’s $10 billion in CapEx was primarily allocated to adding cloud infrastructure. AI-related revenue was already running at roughly $7.3 billion annually in the June quarter, with management expecting it to approach a $10 billion run rate this quarter.

The key question is how quickly those infrastructure investments can recoup their costs. Alibaba estimates that AI compute assets can currently reach breakeven in roughly three years, comfortably within their expected useful life. Management believes the payback period could eventually fall toward 2.5 years as utilization rises, Cloud margins improve, and more workloads shift toward Alibaba’s own chips.

That framework helps explain why Alibaba is comfortable sacrificing free cash flow today. If Cloud can sustain 40%+ growth while gradually improving margins, the current CapEx ramp can support a much larger recurring revenue base rather than becoming a permanent drag on returns.

🧠 Alibaba wants to own the stack

Alibaba’s advantage is that it does not have to monetize AI through one product.

It owns increasingly large pieces of the stack:

• Silicon: T-Head (in-house Zhenwu chips).

• Compute: Alibaba Cloud.

• Foundation models: Qwen (open-weight ecosystem).

• Applications: QwenWork, enterprise agents, and consumer assistants.

Owning more of that stack should help the economics over time. T-Head’s Zhenwu chips already serve more than 650 external customers across 20+ industries via Alibaba Cloud. As more workloads move onto Alibaba-designed silicon, the company can reduce its reliance on expensive third-party accelerators and potentially capture more of the margin generated by AI demand.

Qwen provides another distribution advantage. The model family has surpassed 3 billion downloads, with more than 300,000 derivative models built on top of it. Alibaba can make the models broadly available while monetizing the resulting usage through inference, storage, and other Cloud services. Its Model-as-a-Service business has already surpassed 16 billion yuan (~$2.4 billion) in ARR.

The play is much bigger than selling chatbot subscriptions. Alibaba distributes Qwen to capture developers, converts that open-source adoption into sticky Cloud compute, and deploys custom silicon to protect gross margins. That creates a flywheel across the stack.

🤖 But AI apps are expensive

Alibaba now breaks out AI Labs & Applications (part of AI Apps and Other in our visual above), giving investors a cleaner view of what model training and front-end apps cost while Cloud scales.

The segment includes Alibaba’s model labs, the consumer Qwen business, and products such as QwenWork.

• AI Labs and Applications Revenue reached $0.5 billion, up 16% Y/Y.

• Adjusted EBITA loss widened to roughly $2.0 billion, more than four times the year-ago level.

The losses reflect heavy spending on model training, product development, and user acquisition. Alibaba is still competing aggressively for consumer and enterprise adoption, even as much of the underlying technology remains free or inexpensive to access.

Management expects losses to narrow as training becomes more efficient and commercialization expands. For now, though, the economics are very different across the stack. Cloud is already showing operating leverage, while AI applications remain firmly in investment mode.

🛵 Quick Commerce becomes the second curve

Quick Commerce revenue surged 45% Y/Y to $7.9 billion, making it larger than Cloud this quarter. The business now includes Taobao Instant Commerce, Freshippo, and Tmall Supermarket’s on-demand operations.

On-demand delivery gives Alibaba a powerful frequency engine. Food delivery drives more frequent usage, while 30-minute delivery for groceries and everyday essentials expands order volume well beyond traditional multi-day marketplace shopping.

The economics are also improving:

• Taobao Instant Commerce improved unit economics Q/Q while maintaining market share.

• Higher average order values and a better mix of non-food orders helped margins.

• Alibaba expects non-food volume to surpass food within the next fiscal year.

• Quick Commerce is targeting overall profitability by FY29.

Management believes Quick Commerce could eventually represent around 30% of platform GMV. If that happens, the current spending would have done more than defend Alibaba against Meituan and JD.com. It would have added a much higher-frequency layer to an e-commerce business whose traditional China revenue is already mature.

Bottom Line

Alibaba’s AI spending is still crushing free cash flow, but this quarter offered tangible evidence that the investment is creating economic value. Management’s roughly three-year payback estimate on AI compute assets is the most revealing metric.

AI Labs remains deeply loss-making, and Quick Commerce still requires substantial investment. Still, if Cloud sustains 40%+ growth with expanding margins, today’s massive CapEx could look like smart capital allocation. It is broadly the same playbook we are seeing from the US hyperscalers.

Next up: Saturday’s PRO edition, with Walmart, Target, Klarna, and more.

That’s it for today!

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Disclosure: I own AMZN, BABA, GOOG, META, MSFT, and SHOP in App Economy Portfolio. I share my ratings (BUY, SELL, or HOLD) with App Economy Portfolio members.

Author's Note (Bertrand here 👋🏼): The views and opinions expressed in this newsletter are solely my own and should not be considered financial advice or any other organization's views.

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It’s 13F season again!

Every quarter, funds managing over $100 million must disclose their portfolios, offering a rare glimpse into the minds of elite investors.

The latest 13F filings capture portfolios as of June 30.

In Q2, the AI trade broadened beyond NVIDIA.

The biggest funds kept their core exposure to hyperscalers and leading chipmakers, but new money increasingly moved toward the rest of the AI supply chain. Taiwan Semiconductor, memory, storage, semiconductor equipment, and newer infrastructure names like Cerebras and Nebius featured prominently among top buys.

The theme also continued to spread into the physical economy. Power, industrials, materials, and infrastructure companies continued to attract capital as investors sought ways to participate in the massive data center buildout beyond GPUs.

Beyond AI, some of the quarter’s most interesting bets came from places few investors would expect.

Against that backdrop, super investors had to choose between doubling down on AI infrastructure, revisiting beaten-down growth stocks, or sticking with durable compounders.

Let’s see where the smart money leaned.

Today at a glance:

1. Hedge funds’ strategies

2. Top buys and top holdings in Q2

3. Fund picks that were not on your bingo card

4. Implications for individual investors

Before we dive into 13Fs, a quick reminder: blindly copying hedge fund trades is a terrible strategy.

Investing is like shooting 3-pointers. Even Steph Curry, the greatest shooter ever, misses more than half the time. There are no guaranteed outcomes, even for the pros.

Your behavior matters more than your portfolio. As Peter Lynch said, “Know what you own and why you own it.”

Conviction is what helps you hold through volatility. And conviction comes from doing your own work, not borrowing someone else’s.

As Ian Cassel puts it:

“You can borrow someone else’s stock ideas but you can’t borrow their conviction. […] Do the work so you know when to sell. Do the work so you can hold. Do the work so you can stand alone.”

Some limitations of 13F filings:

• Omit short positions and cash reserves.

• Offer a partial view, leaving out smaller funds.

• Exclude non-US equities, bonds, and commodities.

• Can be dated, given their submission 45 days after the quarter.

With all this said, let’s see what top funds were buying and holding in Q2.

1. Hedge funds’ strategies

Hedge funds are financial powerhouses known for flexible, aggressive strategies designed to beat the market.

Here’s what typically shapes their moves:

• Market conditions: Long in bull markets, defensive in bear markets.

• Sector trends: Shifts in regulation or consumer behavior steer capital.

• Fundamentals: Strong earnings, free cash flow, and leadership matter.

• Macro factors: Rates, inflation, and geopolitics influence positioning.

• Quant models: Some lean on proprietary algorithms to find an edge.

• Risk management: Diversification, hedging, and position sizing.

• Investor sentiment: Fear and greed create mispriced opportunities.

Still, it doesn’t always work out.

The Global X Guru ETF (GURU), designed to track top hedge fund holdings, has underperformed the S&P 500 since its inception in 2012. And that comparison still leaves out the classic hedge fund fee drag.

And those fees matter. The classic “2 and 20” model (2% of assets + 20% of gains) can significantly reduce returns. It's no wonder that many individual investors are opting for simpler, lower-cost strategies.

2. Top holdings and top buys in Q2

Our partners at Fiscal.ai gather the data on Super Investors and visualize their portfolio for you. Pick your favorite investors and see how their holdings have evolved.

In early 2020, just before the COVID market turmoil, I curated a list of 20 top-performing hedge funds using TipRanks data. The selection focused on alpha relative to the S&P 500, and I also included a few funds frequently featured in my social feeds and podcast rotation. It’s not perfect, but it remains a solid directional filter.

Top 5 holdings end of June 2026:

The 10 stocks below represent nearly half of the top holdings listed:

• 🤖 AI infrastructure: TSM, NVDA, ASML, AMAT, MU.

• ☁️ Mega-cap platforms: AMZN, GOOG, META.

• 🚀 New IPOs: SPCX, CBRS.

Amazon and Taiwan Semiconductor are now tied as the most widely held stocks, appearing among the top five holdings of 9 of the 20 funds. Alphabet follows with eight, while NVIDIA appears in five. Microsoft, once a fixture on this list, appeared only once at the end of June after falling more than 20% YTD.

Apple and Tesla were entirely absent from the top-five holdings.

The holdings themselves don’t change dramatically from quarter to quarter, so let’s turn to the more actionable insights with the new movements in Q2.

Top 5 buys in Q2

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Today at a glance:

1. 🦎 Berkshire: Cash Starts Moving

2. 📱 Tencent: AI Bill Arrives

3. 🌐 Cisco: Networking Supercycle

4. ⚙️ Applied Materials: Tool Bottleneck

5. 🌊 Sea Limited: Shopee Monetizes

6. 🏦 Nubank: Credit Fears Ease

7. 🚚 JD.com: Profit Inflects

8. 💳 Adyen: Platform Broadens

9. 👟 On: Premium Focus

10. 💊 Hims & Hers: GLP-1 Trade-off

11. 🛍️ Global-e: Managed Markets Scales

12. 📆 Monday.com: AI Mix Jumps

13. 🇧🇷 StoneCo: Credit Risk Rises

14. 🌎 DLocal: Volume Eats Take Rate

1. 🦎 Berkshire: Cash Starts Moving

Berkshire Hathaway Q2 revenue rose 10% Y/Y to $101.8 billion, while operating profit before tax reached $14.4 billion.

• Manufacturing was the standout, with revenue up 13% and profit rising 24%.

• Insurance was softer, with underwriting profit down 13% and GEICO underwriting earnings falling 45%.

The bigger story is the capital allocation under new CEO Greg Abel. Berkshire bought $23 billion of stocks while selling just $3 billion, its first quarter as a net buyer of stocks in more than three years. That included roughly $10 billion of Alphabet. Berkshire also repurchased $4.5 billion of its own stock in Q2, followed by an estimated $3.4 billion more in July.

As a result, the cash pile fell to $365.5 billion from roughly $397 billion in Q1. That is still enormous, but the direction has changed. Berkshire is also deploying capital through acquisitions, including the $6.8 billion purchase of homebuilder Taylor Morrison.

Bottom Line: The Abel era is starting to look different. Berkshire remains extraordinarily liquid, but buybacks, equity purchases, and acquisitions are finally putting meaningful chunks of its cash pile to work. The question is no longer when Berkshire will deploy capital. It is whether Abel can earn Buffett-like returns on it.

2. 📱 Tencent: AI Bill Arrives

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AI has created a massive capacity gap.

There is more demand for compute than the biggest cloud companies can supply.

That gap has fueled the rise of neoclouds, specialized providers built around AI infrastructure. They focus on securing raw power, specialized data-center capacity, and accelerator clusters rather than replicating the broad software ecosystems of AWS, Azure, or Google Cloud.

Three distinct neocloud models reported this week, offering a clear view into how different strategies tackle this compute bottleneck:

• CoreWeave: Pure-play NVIDIA GPU fleet rental scaling on long-term enterprise commitments.

• Nebius: An AI-focused cloud platform built from scratch on international data-center infrastructure.

• Cerebras: A proprietary chipmaker pivoting into cloud-hosted fast inference.

The economics across all three are counterintuitive. Capacity must be funded and built months before it can generate revenue, driving negative free cash flow. Debt, leases, depreciation, and customer concentration matter almost as much as growth.

Let’s review what we learned.

🧱 CoreWeave is Sold Out

CoreWeave is the purest version of the neocloud model. It buys NVIDIA GPUs, installs them in data centers, and rents the compute to customers such as OpenAI, Microsoft, and Meta.

Most of the business is already spoken for. Committed contracts generated 98% of Q2 revenue, while on-demand usage contributed just 2%.

Revenue jumped 112% Y/Y to $2.6 billion, but gross margin contracted by 8 points to 66% as data-center rent, power, and other ramp costs grew even faster.

CoreWeave posted a $49 million operating loss and a $626 million net loss, heavily weighed down by $640 million in interest expense tied directly to its GPU-collateralized debt facilities.

And the income statement captures only part of the spending. Q2 CapEx reached $9.4 billion, more than three times quarterly revenue.

What to make of all this?

• 📚 Demand keeps outrunning capacity: Backlog reached $104 billion, up 246% Y/Y, before another $25 billion of customer commitments signed in early Q3. Near-term capacity is effectively sold out.

• 💰 Margins are expected to turn: Gross margin contracted as CoreWeave raced to bring new capacity online, but adjusted operating margin improved sequentially from 1% to 5%. New Q2 contracts are expected to carry contribution margins 5 to 10 points above recent deals, even before July’s roughly 25% price increase.

• 🧠 The mix is getting better: Storage, CPU, networking, and software now exceed $400 million of ARR. Managed inference jumped from $1 million to more than $100 million of booked ARR in a single quarter.

• 🏗️ Growth remains extremely expensive: CoreWeave raised its 2026 CapEx outlook to $35 billion to $39 billion as it races toward more than 1.85 GW of active power by year-end.

Bottom line: CoreWeave’s $104 billion backlog sounds almost absurd next to a targeted 2026 exit revenue run rate of $19 billion. But conversion is constrained by physical capacity. The investment case comes down to how quickly it can turn power and GPUs into revenue without letting financing costs overwhelm the margin gains.

☁️ Nebius Finds Pricing Power

Nebius did not start as a typical AI infrastructure startup.

• 🇷🇺 Yandex roots: Nebius emerged from the 2024 breakup of Russian tech giant Yandex. Its Nasdaq-listed Dutch holding company sold the Russian operations for $5.4 billion and kept a smaller group of international businesses that became Nebius.

• ♻️ Public-company reset: The remaining company kept its Nasdaq listing, rebranded as Nebius Group, and put Yandex co-founder Arkady Volozh back in charge.

• ☁️ AI infrastructure pivot: Rather than rebuild the old internet conglomerate, Nebius used its engineering talent, cloud expertise, and capital base to build a purpose-built AI cloud.

AI Cloud generated $575 million, or 98% of Q2 revenue, by renting GPU capacity through its own cloud platform.

Revenue surged 454% Y/Y to $582 million, while gross margin expanded 6 points to 77%. The business also generated $236 million of adjusted EBITDA at a 41% margin.

Nebius posted a $176 million operating loss, but depreciation and amortization alone reached $260 million as billions of dollars of new infrastructure started hitting the income statement.

What to make of all this?

• 💰 Pricing is moving higher: Four new AI cloud deals averaged more than $1 billion of contract value and $20 million to $25 million per megawatt. Shorter-term capacity is now fetching as much as $40 million to $50 million per MW.

• ⏱️ Payback is getting faster: Management estimates the Q2 contracts will repay their associated CapEx and operating costs in about 22 months, down from the previous two-to-three-year range.

• 🏗️ The buildout is enormous: Q2 CapEx reached $5.7 billion, almost 10 times quarterly revenue. Nebius still expects $20 billion to $25 billion for the year.

• 🤝 Customers are helping finance it: Nebius expects more than $9 billion of customer prepayments in 2026, covering roughly 50% to 60% of the associated CapEx.

Bottom line: Nebius is spending at extraordinary scale, but rising prices, faster paybacks, and customer prepayments are making each new megawatt more attractive. That capital efficiency may ultimately matter more than its 454% revenue growth.

🧠 Cerebras Moves to the Cloud

Cerebras is the odd one out among neoclouds. Instead of buying NVIDIA GPUs, it designs its own wafer-scale processor and monetizes it either by selling systems or renting the compute through Cerebras Cloud.

The revenue mix is shifting quickly. Q2 revenue rose 74% Y/Y to $180 million, with Cloud & Other Services surging 281% to $126 million while hardware fell 23% to $54 million.

The company had a brutal $477 million operating loss, but the headline needs context. Cerebras went public in May, triggering substantial stock-based compensation. Its core operating loss was just $34 million, compared with $477 million under GAAP.

Core results exclude stock comp, customer-warrant charges, and certain pass-through items. This stock-based compensation overhang should normalize over upcoming quarters as initial post-IPO equity grants settle.

Reported gross margin was just 14%, but on a core basis it was 41%, up about 9 points Y/Y. That was down from 46.5% in Q1, partly because Cerebras is temporarily paying to rent back systems it previously sold so it can meet cloud demand.

What to make of all this?

• ☁️ Cloud has become the growth engine. Core cloud revenue nearly quadrupled to $128 million and surpassed hardware for the first time.

• 📈 The outlook improved. Cerebras raised FY26 core revenue guidance to $880 million to $890 million, alongside higher gross-margin and operating-margin expectations.

• 🏗️ Capacity is still the bottleneck. More than 600 MW of data-center capacity is now live or contracted through 2027. Core gross margin is expected to bottom in Q3 before new capacity comes online and reduces the need for expensive rented capacity.

• 📚 Demand is far ahead of revenue. Remaining performance obligations reached $25.4 billion. OpenAI remains a major customer, but converting that backlog requires substantially more infrastructure.

Bottom line: Cerebras is evolving from a chip seller into a fast-inference cloud. Stock comp and other accounting adjustments obscure that progress, but the real test is converting its enormous backlog into revenue while rebuilding margins as new capacity comes online.

What to Watch

Across all three neoclouds, the same tension keeps showing up. Demand is outpacing available compute, but serving it requires enormous amounts of capital before revenue arrives.

That same compute shortage is pushing tech giants to build their own capacity. Meta is scaling custom silicon and gigawatts of GPUs, while SpaceX has already started selling access to its Colossus cluster. The longer-term question is whether neoclouds remain essential infrastructure partners or temporary relief valves once mega-cap AI capacity fully comes online.

The next phase comes down to capacity, margins, and funding. Neoclouds need to turn contracted demand into energized infrastructure, improve returns as utilization rises, and fund the next wave of expansion without letting debt or dilution overwhelm the economics.

The demand is locked in. Capital efficiency will separate the winners.

Next up: Saturday’s PRO edition will include the other big earnings of the week, like Berkshire, Tencent, Cisco, Sea Limited, Nu, Adyen, and more.

That’s it for today!

Stay healthy and invest on!

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Disclosure: I am long AMZN, MSFT, GOOG, NVDA, AMD, TSM, and ASML in App Economy Portfolio. I share my ratings (BUY, SELL, or HOLD) with members.

Author's Note (Bertrand here 👋🏼): The views and opinions expressed in this newsletter are solely my own and should not be considered financial advice or any other organization's views.

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📺 Streaming’s coming of age

For years, media companies treated streaming like a land grab. That era is ending.

Streaming is starting to look like a mature business. Disney reached a 13% streaming margin, Paramount hit 15%, and Warner Bros. came in at nearly 17%. Subscriber totals matter less than churn, pricing, engagement, and how much profit each viewer can generate.

Meanwhile, the businesses streaming is replacing keep shrinking. Warner’s Networks revenue fell 17%. Paramount’s TV Media declined 9%. Cord-cutting and weaker advertising continue to eat away at linear TV.

Paramount’s Warner Bros. deal has cleared most international regulators, but a US antitrust fight has pushed the timeline into 2027. The longer it drags, the more expensive the deal becomes.

Can streaming profits grow fast enough to outrun the decline of the old bundle? And how expensive could the merger delay become?

Today at a glance:

• 🏰 Disney: Parks Answer the Doubters

• 🎥 Warner: Box Office Whiplash

• ⛰️ Paramount: Stronger Before the Storm

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🏰 Disney: Parks Answer the Doubters

Disney’s fiscal year ends in September, so the June quarter was Q3 FY26.

• 📸 Big picture: Revenue rose +7% Y/Y to $25.2 billion ($0.2 billion miss), while adjusted EPS jumped +28% to $2.06 ($0.21 beat). Total segment operating income rose +21% to $5.6 billion, ahead of expectations. Disney maintained its FY26 outlook for ~12% adjusted EPS growth and raised its buyback target again to at least $9 billion.

• 📈 Streaming margin expands again: Disney+/Hulu revenue grew +11% to $5.5 billion, while SVOD operating margin reached 13%, extending last quarter’s profitability inflection. Disney remains on track for double-digit streaming margins in FY26, though management says international monetization still has room to improve.

• 🍿 Entertainment gets its hit: Entertainment operating income surged +64% Y/Y, helped by streaming profitability and Toy Story 5, which crossed $1 billion at the global box office. The film also lifted merchandise sales and Disney+ engagement, showing how a successful franchise can reverberate across the company.

• 🏰 Experiences answer the skeptics: Experiences revenue rose +10% to a record $10.0 billion, while operating income jumped +20% to $3.0 billion. Domestic park attendance grew +3%, and per-guest spending rose +4%, with Walt Disney World having a particularly strong quarter. International visitation remains soft, but forward bookings are healthy.

• 🏈 Sports remains the weak spot: Sports revenue reached roughly $4.5 billion, while operating income fell -17% to $858 million, hurt by shorter NBA playoff series and rights timing. ESPN remains the clearest drag on Disney’s otherwise improving profit mix.

• 🤖 Disney+ gets a roadmap: CEO Josh D’Amaro said Disney will begin expanding Disney+ beyond video in spring 2027, adding games, merchandise, and other experiences designed to lower churn and increase lifetime fan value. Disney is also considering free ad-supported offerings as it turns Disney+ into the company’s broader digital hub.

Bottom Line: Streaming profitability is becoming repeatable, while Experiences just delivered the quarter investors feared it couldn’t. That gives D’Amaro more room to execute his “One Disney” strategy, with Disney+ increasingly positioned as the front door to content, commerce, and experiences.

🎥 Warner Bros: Box Office Whiplash

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• 🚖 Uber, Nintendo, Shopify

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Today at a glance:

1. 💊 Eli Lilly: Volume Crushes Price

2. 🦠 Merck: The Bridge Broadens

3. 🧬 Amgen: Growth Outruns the Cliff

4. 🇩🇰 Novo Nordisk: Pill Holds Up

5. 💉 Pfizer: Pipeline Questions

6. 🌐 Arista Networks: Supply Catches Up

7. 💾 Sandisk: AI Eats NAND

8. ☁️ Cloudflare: Agentic Acceleration

9. 🌊 DigitalOcean: AI Accelerates

10. 🐶 Datadog: AI Concentration Bites

11. ☁️ Atlassian: Enterprise Breakout

12. 📢 HubSpot: Pricing Pivot Bites

13. 🎨 Figma: AI Credits Scale

14. 🏴 Klaviyo: Agents Gain Traction

15. 💬 Twilio: Expansion Returns

16. 💻 Paycom: Margins Do the Work

17. ⚡️ Axon: Dedrone Breaks Out

18. 🤝 MercadoLibre: Brazil Bet Pays Off

19. 🥡 DoorDash: DashPass Takes Over

20. 🇰🇷 Coupang: Customers Return

21. 🥕 Instacart: Customers Come Back

22. 📦 Etsy: Back to Etsy

23. 🍞 Toast: Locations Reaccelerate

24. 🔲 Block: Square Catches Up

25. 💳 Fiserv: Reset Gets Deeper

26. 🪙 Circle: Arc Hits the P&L

27. 🏠 Zillow: Growth Without Traffic

28. 🏝️ Booking: Travel Holds Up

29. 🛖 Airbnb: Hotels Check In

30. 🏨 Marriott: US Momentum Holds

31. ✈️ Expedia: Consumer Catches Up

32. 📱 AppLovin: Model Timing Miss

33. 📺 The Trade Desk: Growth Stalls

34. 📌 Pinterest: Growth Speed Bump

35. 👻 Snap: Reset Starts Working

36. 🎧 Spotify: 300 Million Paid

37. 🔥 Match Group: Tinder Stabilizes

38. 🦉 Duolingo: Streak Revival

39. 🗞️ NYT: Subscriber Growth Slows

40. 🚲 Peloton: Profit Without Growth

41. 🎮 Sony: Beyond PlayStation

42. 🎮 Take-Two: GTA VI Preorders Explode

43. 📺 Fox: World Cup Windfall

44. 🏈 Flutter: FanDuel Needs a Reset

45. 👑 DraftKings: Predictions Get Expensive

46. 🍟 McDonald’s: Value Misfires

47. 🍔 RBI: Burger King Breaks Out

48. 🌭 Kraft Heinz: Green Shoots

49. ⚡️ Celsius: Alani Carries the Portfolio

1. 💊 Eli Lilly: Volume Crushes Price

Lilly’s Q2 revenue jumped 48% Y/Y to $23.0 billion ($2.3 billion beat), while adjusted EPS was $8.38 ($1.80 beat). Revenue growth came from a 60% increase in volume, more than offsetting a 13% decline in realized prices.

Mounjaro surged 91% to $9.9 billion and Zepbound grew 46% to $4.9 billion, bringing combined GLP-1 revenue to nearly $15 billion. International Mounjaro sales more than doubled to $5.2 billion as Lilly expands access globally, despite significant price reductions including China reimbursement.

Foundayo, Lilly’s newly launched oral GLP-1 obesity pill, generated $98 million in its first quarter on the market. The next-generation pipeline also advanced materially: retatrutide (triple-hormone obesity injection targeting GLP-1, GIP, and glucagon) delivered positive results in three additional Phase 3 obesity trials. Lilly plans to file with the FDA in Q1 2027.

Lilly raised FY26 revenue guidance to $85–$87 billion, a $2.5 billion midpoint increase. Underlying EPS guidance was also raised by $2.78 at the midpoint, but $3.03 of acquisition-related R&D charges offset that improvement, leaving reported guidance at $35.50–$36.50.

Bottom Line: The GLP-1 story remains a volume machine. Lilly is deliberately giving up price to expand access, and demand is more than compensating. Foundayo adds a new format today, while retatrutide increasingly looks like the next major leg of the obesity franchise.

2. 🦠 Merck: The Bridge Broadens

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🗓️ The earnings flood continues!

This week, we’re visualizing more than 50 earnings reports across tech, healthcare, commerce, and everything in between.

Today at a glance:

• 🚖 Uber: AV Anxiety

• 🍄 Nintendo: Software Cushion

• 🛍️ Shopify: Deceleration Dodged

🚖 Uber: AV Anxiety

Uber’s Q2 revenue rose 12% Y/Y to $14.2 billion ($70 million miss), though an accounting shift from a merchant to an agency model in UK Mobility reduced reported growth by 8 points.

Gross Bookings grew 24% (or 22% constant currency) to a record $58.0 billion, marking the fourth consecutive quarter above 20%.

Trips rose 18% to 3.9 billion, driven by 16% growth in monthly users. The 2-point slowdown in trip growth came entirely from Brazil, Uber’s highest-volume market, where competition for two-wheel drivers constrained supply. US Mobility actually accelerated as insurance savings funded lower prices, with trip growth strongest in markets like San Francisco and Los Angeles where fares fell the most.

Mobility bookings grew 20%, while Delivery accelerated to 25%. That growth is increasingly flowing through to profits. Adjusted EBITDA rose 33% to $2.8 billion, with margin reaching 4.9% of Gross Bookings. Trailing-12-month free cash flow crossed $10 billion for the first time, giving Uber more room for buybacks, M&A, and AV investment.

Autonomy remains the valuation debate. Uber is now live with AVs in seven cities and still targets 15 by year-end. Management argues its advantage is not building the autonomous driver itself, but aggregating demand, dispatching vehicles, handling fleet operations, insurance, and regulators. In mature AV markets including San Francisco, Los Angeles, and Phoenix, Uber says its overall category share is actually higher than a year ago.'

Yet the valuation already reflects plenty of AV anxiety. At roughly 10x 2027 adjusted EBITDA, Uber trades at a modest multiple for a business still growing bookings above 20%. The market is clearly pricing in some future erosion of Uber’s economics.

Uber guided Q3 Gross Bookings to $58.25–$60.25 billion, implying 18–22% constant-currency growth, while EPS guidance of $0.84–$0.88 was roughly in line.

Bottom Line: Uber’s core business keeps getting stronger and its Delivery Hero acquisition could deepen its flywheel. The market’s question has simply moved further out: how much of today’s economics does Uber retain once robotaxis scale?

🍄 Nintendo: Software Cushion

Nintendo Q1 revenue (June quarter) fell 10% Y/Y to ¥518 billion (~$3.3 billion), but still beat expectations, while operating profit surged 151% to ¥143 billion, nearly double consensus. Net income rose 54% to ¥147 billion. The catch was that roughly $300 million of refunded US tariffs reduced cost of sales, providing a large one-time boost to profitability.

Switch 2 sold 3.8 million consoles, down 34% against last year’s launch quarter but already 23% of Nintendo’s 16.5 million FY27 target. It now has an installed base of 23.7 million units globally. That compares to 17.8 million units sold by the original Switch a year after launch.

The big surprise was that the original Switch software sales jumped 39% to 34 million units, versus just 9.5 million Switch 2 games. Tomodachi Life: Living the Dream sold 7.9 million units and Pokémon Pokopia 1.3 million, showing that backward compatibility is keeping the 150M+ Switch ecosystem economically relevant even as hardware migrates. Digital sales nearly doubled to ¥133 billion and reached 62% of software revenue.

IP-related revenue more than doubled to ¥35 billion, helped by The Super Mario Galaxy Movie, which has already passed $1 billion at the global box office. That higher-margin software and IP mix helped gross margin jump 22 points to 54%, although the tariff refund materially amplified the improvement.

Bottom Line: Nintendo left FY27 guidance unchanged at 16.5 million Switch 2 consoles, 60 million Switch 2 games, ¥2.05 trillion of revenue, and ¥370 billion of operating profit. The real test still starts in September, when a price hike takes the Switch 2 to $500 heading into the holiday season.

🛍️ Shopify: Deceleration Dodged

Shopify’s Q2 revenue jumped 34% Y/Y to $3.6 billion ($140 million beat), while GMV grew 32% to $115.6 billion. Free cash flow reached $654 million at an 18% margin, up from 15% last quarter. Shares surged as the recent deceleration scare proved premature.

Growth remained broad across merchant sizes, geographies, and channels. Shopify Payments penetration reached 68% of GMV (+3pp Y/Y), while Shop Pay has now processed more than $400 billion in GMV since launch.

AI commerce is also becoming more tangible. AI-driven traffic and orders to Shopify stores both tripled Y/Y, with AI-attributed orders converting at roughly twice the rate when agents use Shopify’s structured Catalog rather than scraped web data. Importantly, 75% of AI-attributed orders came from outside Shopify’s top 100 categories, suggesting AI discovery disproportionately benefits smaller merchants.

Shopify guided Q3 revenue growth to the low-30s%, well above the ~27% consensus and implying a sixth consecutive quarter above 30%. Free cash flow margin should also improve to the ‘high teens’ to ‘low 20s.’

Bottom Line: Q1 raised the question of whether Shopify was finally slowing. Q2 answered it decisively. GMV and revenue remain above 30%, margins are expanding, and AI is increasingly looking like a distribution tailwind rather than the disruption risk investors feared.

Next up: Saturday’s massive PRO edition, with over 40 companies visualized, including Eli Lilly, AppLovin, Sony, Airbnb, Spotify, and more.

That’s it for today!

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Disclosure: I am long SHOP and UBER in App Economy Portfolio. I share my ratings (BUY, SELL, or HOLD) with members.

Author's Note (Bertrand here 👋🏼): The views and opinions expressed in this newsletter are solely my own and should not be considered financial advice or any other organization's views.

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🗓️ It’s peak earnings season!

This week, we’ll visualize more than 50 reports ranging from Airbnb to Zillow.

Today’s batch captures the mood of earnings season pretty well, with huge AI ambition, rising capital intensity, and a few quieter stories improving underneath.

Today at a glance:

• 🕵️ Palantir: Sovereign AI

• 🚀 SpaceX: Growth Meets the Bill

• ↗️ AMD: Data Center Takes Over

• 🛵 Grab: The Overhang Shrinks

🕵️ Palantir: Sovereign AI

Palantir Q2 revenue jumped 93% Y/Y to $1.94 billion ($130 million beat), marking the 12th consecutive quarter of acceleration. Adjusted EPS of $0.41 beat by $0.06. The Rule of 40 score climbed again to 155, with adjusted free cash flow reaching $1.22 billion at a 63% margin.

US revenue keeps pulling away.

• 💼 US Commercial: $764 million (+149% Y/Y, +28% Q/Q).

• 🪖 US Government: $809 million (+90% Y/Y, +18% Q/Q).

Total US revenue reached $1.57 billion, up 115% Y/Y and now representing 81% of Palantir’s business. International revenue grew a much slower 33% to $363 million, with CEO Alex Karp again dismissive of Europe: “The growth sucks.”

The pipeline behind the print looks even more bullish. Palantir closed 220 deals worth at least $1 million, including 73 above $10 million.

• TCV (Total Contract Value): The total value of contracts signed during the quarter reached a record $2.13 billion in US Commercial, up 153% Y/Y.

• RDV (Remaining Deal Value): Contracted revenue not yet recognized climbed 124% Y/Y (and a staggering 27% Q/Q) to $6.24 billion in US Commercial, giving Palantir an increasingly large backlog behind future growth.

Palantir’s new framing is “sovereign AI.” Management argues customers increasingly want AI without handing proprietary data, workflows, or competitive intelligence to frontier model providers. AIP (Palantir’s AI Platform) sits between companies and the models, letting customers swap LLMs while keeping their data and operational logic under their own control. Karp put it more bluntly: customers should not become “vassal states of the language labs.”

We discussed last quarter that tokens are the new coal. Models and tokens are becoming cheaper commodities. Palantir wants to own the governed operational layer where companies turn them into actual work.

Palantir raised FY26 revenue guidance by roughly $500 million to $8.15–$8.16 billion, implying 82% growth, versus 71% expected just three months ago. US Commercial is now expected to grow at least 134% to more than $3.42 billion. Adjusted free cash flow guidance increased to ~$4.6 billion (from ~$4.3 billion previously).

Bottom Line: The fundamental story somehow keeps getting stronger. Revenue growth accelerated, US Commercial is now 39% of the top line, and free cash flow margins have crossed 60%. The valuation is still extreme at nearly 80x FY26 EBITDA, but Palantir is doing something equally extreme: accelerating above 90% revenue growth at nearly $8 billion of annual revenue while simultaneously expanding margins.

🚀 SpaceX: Growth Meets the Bill

SpaceX’s first earnings report as a public company showed why investors are excited about the business and why the valuation remains difficult to digest.

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🔥 The July report is here!

All the key earnings visuals from the past month in one place.

• ✔️ Cut through the noise with clear, concise financial snapshots.

• ✔️ See revenue trends, profit margins, and key takeaways instantly.

Download the full report below or log in to your account.

Here’s a sneak peek of the 100+ companies included. 👀

• ☁️ Mega-Caps: Apple, Alphabet, Microsoft, Amazon, Meta, Tesla.

• 🧩 Semis: TSMC, ASML, Samsung, SKH, Intel, KLA, Qualcomm.

• 💊 Healthcare: J&J, UnitedHealth, Abbott, Intuitive Surgical.

• 🏦 Banks: JPMorgan, BofA, Wells Fargo, Citigroup, Schwab.

• 🍿 Entertainment: Netflix, Comcast, Roblox, Live Nation.

• 💰 Wealth: Morgan Stanley, Goldman Sachs, BlackRock.

• 💻 Software: IBM, SAP, ServiceNow, Fortinet, AppFolio.

• ☕ Restaurants: Starbucks, Chipotle, Domino’s, YUM!

• ✈️ Airlines: American, Delta, Southwest, United.

• 📡 Telecom: AT&T, T-Mobile, Comcast, Verizon.

• 💳 Payments: Amex, Visa, Mastercard, PayPal.

• 🛡️ Defense: Boeing, Airbus, Lockheed Martin.

• 🇫🇷 Luxury: LVMH, Hermès, Kering, L’Oréal.

• 🧬 Pharma: AbbVie, Sanofi, AstraZeneca.

• 🔬 Equipment: ASML, Lam Research.

• 🥤 Beverages: Coca-Cola, PepsiCo.

• 🚗 Autos: Rivian, GM, Ford, Ferrari.

• 📈 Brokers: SoFi, Robinhood.

• 🏨 Travel: Hilton.

• Plus Reddit, Mondelez, Hershey, UPS, P&G, GE Vernova, Tilray, and more.

Download the full report below!👇

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• ☁️ Amazon: The CapEx Equation

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• 📊 Monthly reports: 200+ companies visualized.

• 📩 Tuesday articles: Exclusive deep dives and insights.

• 📚 Access to our archive: Hundreds of business breakdowns.

PRO members get everything PLUS:

• 📩 Saturday PRO reports: Timely insights on the latest earnings.

Today at a glance:

1. 📱Apple: Ternus Handoff

2. 🕶️ Meta: AI Bill Comes Due

3. 📱 Samsung: Records Meet A Rout

4. 💳 Visa: Volume Accelerates

5. 💳 Mastercard: The Crack Didn't Widen

6. ⏳ AbbVie: Growth Engines Hold

7. 🧠 Lam Research: The Ramp Steepens

8. 🥤 Coca-Cola: Volume Carries The Quarter

9. 🧴 P&G: Iran Cost Bites

10. 📱 Arm: Data Center Offsets Phones

11. 🔬 KLA: 2027 Gets Bigger

12. 🧬 AstraZeneca: Pipeline On Trial

13. 🛩️ Airbus: The Ramp Finally Shows

14. 📲 Qualcomm: Diversification On Trial

15. 🛩️ Boeing: Cash Turns Positive

16. ☕️ Starbucks: Measurable Momentum

17. 🔒 Fortinet: The Surge Extends

18. 📦 UPS: The Reset Lands

19. 💡 Cadence: AI Demand Compounds

20. 🪶 Robinhood: Firing On All Cylinders

21. 🍪 Mondelez: North America Turns

22. 🏨 Hilton: Mid-Scale Rebounds

23. 🏎️ Ferrari: Scarcity Pays

24. 🚙 Ford: Trucks Cover The Damage

25. 💳 PayPal: The $60 Question

26. 📈 Coinbase: Winning a Smaller Market

27. 🎤 Live Nation: World Tour Expands

28. 🌯 Chipotle: Momentum Meets A Wobble

29. 🌮 Yum! Brands: Pizza Hut Heads Out

30. 🍫 Hershey: Price Over Volume

31. 👾 Roblox: Monetization Trade-Off

32. 👽 Reddit: Monetization Outruns Users

33. ⚡ Rivian: R2 Hits the Road

34. 🏦 SoFi: Records Meet A Shrug

35. 🦷 Align: Scanners Down

36. 🩺 Teladoc: The BetterHelp Pivot

1.📱Apple: Ternus Handoff

Apple’s Q3 revenue rose 16% Y/Y to $109.4 billion ($0.5 billion beat), while EPS reached $2.02 ($0.13 beat). Tariff refunds contributed $0.11 to EPS, but underlying results still came in ahead of expectations. These were June quarter records, yet shares fell about 6% after earnings.

• iPhone revenue grew 22% to a record $54.3 billion.

• Mac jumped 29% to a record $10.4 billion.

• China rebounded 22% to $18.8 billion.

• Services slowed to 12% growth, reaching $30.7 billion.

This was Tim Cook’s final earnings call before John Ternus takes over in September. He leaves Apple with a good problem to have: the company cannot make enough devices.

Cook said unexpectedly strong iPhone and Mac demand exhausted Apple’s flexibility to secure more advanced chips. These constraints primarily affected Mac this quarter and will broaden to iPhone, Mac, and iPad in the September quarter. Apple still guided revenue growth to 9%–11%, with iPhone expected to grow in the mid-teens, but the outlook came in below consensus.

Memory is becoming the larger margin problem. Cook described the market as a “hundred-year flood,” with rapidly rising prices already forcing Apple to increase some Mac and iPad prices. Excluding tariff benefits, gross margin declined sequentially, and Apple expects another step down in Q4 as cheaper inventory runs out.

Meanwhile, R&D spending rose 32% Y/Y to $11.7 billion as Apple accelerated its AI investment. Cook also suggested heavy Siri users could eventually be pushed toward more expensive iCloud+ plans, offering an early glimpse of how Apple might monetize its AI overhaul.

Ternus inherits one of Apple’s strongest product cycles in years, but also a supply chain that cannot fully support it and a margin structure increasingly exposed to memory inflation. The next iPhone cycle must prove Apple can manage both pressures while convincing customers that its AI catch-up is finally real.

2. 🕶️ Meta: AI Bill Comes Due

Meta’s Q2 revenue rose 28% Y/Y to $60.8 billion ($0.5 billion beat). GAAP EPS fell 13% to $6.18, but the quarter included $2.4 billion in legal charges related to youth-safety litigation and $1.2 billion in severance costs. Excluding those items, operating income would have risen 9% rather than declined 8%. Despite the underlying beat, shares fell as much as 10%.

The selloff came down to two things:

• Free cash flow nearly disappeared. Meta generated $31.9 billion in operating cash flow but spent $31.1 billion on capex and finance leases, leaving just $784 million in free cash flow, down 91% Y/Y. It also issued $24.9 billion of debt and repurchased no stock. Meta can afford the buildout. But for the first time, AI spending has effectively consumed the quarter’s free cash flow, halted buybacks, and pushed the company into the debt market.

• The CapEx floor moved higher again. Meta narrowed its FY26 outlook to $130–$145 billion from $125–$145 billion, raising the bottom end for the second consecutive quarter. Its new 1 GW El Paso data center venture shows how it plans to fund the next stage: BlackRock will own 80%, while Meta retains 20% and leases the entire campus. The structure reduces the upfront cash burden without reducing Meta’s long-term commitment.

The irony is that AI is already paying off inside the ad business. Advertising revenue grew 27% Y/Y as impressions increased 14% and average price per ad rose 12%. Meta’s latest models generated an 8% increase in ad clicks and a 16% uplift in Facebook conversions, while Advantage+ products surpassed a $75 billion annual revenue run rate. AI is already producing measurable returns inside the existing business.

Family DAP reached 3.60 billion, Instagram crossed two billion daily users, and Threads surpassed 500 million monthly users. WhatsApp paid messaging and subscriptions also pushed Family of Apps ‘other’ revenue above $1 billion for the first time.

Zuck also offered a more concrete return path than last quarter. Beyond improving ads and engagement, Meta may sell paid model access and lease excess computing capacity. He said outside buyers have offered a “meaningful premium” to Meta’s cost, though building a real cloud business will require distribution and software capabilities Meta does not yet have.

Reality Labs lost another $4.6 billion, while revenue rose 16% on stronger AI-glasses sales.

Meta guided Q3 revenue to $61–$64 billion, with the midpoint below consensus, and raised FY26 expenses to $165–$169 billion. Meta is already earning more from ads, and it now has plausible ways to monetize models and excess compute. The problem is that the spending is arriving all at once, while some of the new revenue streams will take time to meaningfully contribute.

3. 📱Samsung: Records Meet A Rout

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Amazon plans to spend $220 billion in CapEx this year, up another $20 billion.

And it still won’t be enough. CEO Andy Jassy explained:

“Even at that amount, we will still not have enough capacity to meet all the demand we have in 2026. […] I believe this dynamic will also be true in 2027, too.”

AWS growth accelerated for the fifth consecutive quarter, backlog reached $496 billion, and margins expanded despite the unprecedented buildout.

Amazon has been building the stack for agentic AI. Now, the bet is moving from architecture to economics. Demand is arriving faster than capacity, and Jassy is increasingly confident the returns will justify the spend.

Now let’s see what stood out this quarter.

Today at a glance:

1. Amazon Q2 FY26.

2. The economics of the AI stack.

3. Key quotes from the call.

4. What to watch moving forward.

1. Amazon Q2 FY26

Income statement:

• Revenue rose +20% Y/Y to $200.6 billion ($4.2 billion beat).

• Gross margin was 52% (+0pp Y/Y).

• Operating margin was 14% (+2pp Y/Y).

  • AWS: 39% margin (+6pp Y/Y).

  • North America: 8% margin (+0pp Y/Y).

  • International: 4% margin (+0pp Y/Y).

• Net profit included a $53.4 billion non-operating gain, primarily from the valuation markup of Anthropic. The markup followed Anthropic’s $65 billion Series H round in May at a $965 billion valuation, up from $380 billion in February.

Cash flow:

• Operating cash flow TTM was $161.4 billion (+33% Y/Y).

• Free cash flow TTM fell to negative $7.6 billion as a 64% rise in CapEx to $169.0 billion more than offset the growth in operating cash flow.

Balance sheet:

• Cash, cash equivalents, and marketable securities: $123 billion.

• Long-term debt: $129 billion.

Q3 FY26 Guidance:

• Revenue +9% to 12% Y/Y.

• Operating income of ~$24.5 billion, or +40% Y/Y at the midpoint.

So, what to make of all this?

• ☁️ AWS breaks out: AWS revenue accelerated 37% Y/Y to $42.2 billion, its fastest growth in 18 quarters. AWS operating margin reached 39%. Excluding a $600 million energy-contract accounting gain, it still expanded 520 basis points Y/Y. Meanwhile, Amazon’s AI and custom-chip businesses each surpassed $25 billion annual revenue run rates, both growing triple digits. The chips business was above $20 billion just three months ago. At this scale, accelerating growth and expanding margins at the same time is the quarter’s defining result.

• 💵 The AI bill is getting larger: Free cash flow swung to a $7.6 billion outflow as CapEx reached $169 billion over the past year. Amazon also raised its 2026 CapEx forecast from $200 billion to $220 billion, primarily because of higher memory costs. Capital spending now exceeds the cash Amazon generates from operations.

• 📦 Retail volume remains strong: North America revenue grew 16%, International grew 15%, and worldwide paid units increased 17%. North America margin was flat even with a $600 million tariff refund, as higher fuel and transportation costs offset continued fulfillment efficiencies.

• 📢 Advertising keeps climbing: Revenue grew 26% Y/Y to $19.8 billion, putting the business near an $80 billion annual run rate. Sponsored Products remains the core engine, while Prime Video and live sports are opening new inventory.

• 🔮 Guidance looks softer than the underlying business: Q3 revenue growth is expected to slow to 9%–12%, but the shift of Prime Day into Q2 reduces the reported growth rate by nearly four percentage points, while foreign exchange creates another 80-basis-point headwind. Operating income is still expected to grow roughly 40% at the midpoint, suggesting Amazon’s margin expansion remains intact.

2. The economics of the AI stack

🏗️ The return profile

Jassy finally laid out the math behind Amazon’s massive CapEx ramp.

The spending falls into two different buckets:

• Servers and networking equipment: Purchased only a few months before deployment, when Amazon already has visibility into demand. They typically break even in less than three years, while most AI capacity is contracted for at least five.

• Data centers: Built roughly two years before monetization, but designed to operate for more than 30 years and support five or six generations of servers.

Most of AWS’s 2027 capacity is already reserved, with meaningful commitments extending into 2028.

The near-term free cash flow pressure is unavoidable, but Amazon is not building on speculation. Much of the equipment is backed by long-term contracts, while the data centers can generate revenue long after the first generation of servers is retired.

👔 Moving up the stack

AWS is also expanding beyond infrastructure into the software agents running on top of it. Bedrock customers spent more in Q2 than in all previous quarters combined.

• Bedrock AgentCore added payments, web search, deterministic controls, and a development harness.

• Amazon Quick can now run autonomous workflows across email, calendars, files, and third-party applications.

• Kiro, Amazon’s coding agent, tripled usage sequentially.

• Continuum uses agents to identify, validate, and remediate software vulnerabilities.

AI is also pulling the core cloud business with it, since post-training and agent tool use rely heavily on CPUs. Trainium and Graviton lower the cost underneath, Bedrock sits at the model and agent layer, and applications such as Quick, Kiro, and Continuum move AWS closer to the end user.

3. Key quotes from the earnings call

Check out the earnings call transcript on Fiscal.ai here.

Andy Jassy on AI economics:

“We see the margins and returns in AI tracking what we saw with Core at the same point of evolution, actually a little ahead.”

This directly challenges the assumption that AI workloads will structurally dilute cloud margins. Amazon believes AI economics are developing faster than AWS did in its early years.

On the real inference opportunity:

“In the middle of the barbell is all of the current enterprise production workloads, some of which are using inference in a pervasive way, but most of which aren't. That is going to change very significantly over time. In my opinion, that will be the largest absolute segment […].”

AI demand is currently barbelled between frontier labs and breakout applications on one side, and narrow enterprise use cases on the other. Jassy believes the middle will eventually become the largest segment: AI embedded across existing production workloads.

On Amazon’s frontier model:

“My view of it is that within the next few years, you're going to have at least a half dozen models that are comparably good to each other. [...] They'll all be in Bedrock, one of them will be ours.”

Amazon does not need its model to dominate. Bedrock wins through choice, while an in-house frontier model gives Amazon more control over cost, speed, and product priorities.

4. What to watch moving forward

☁️ AWS market share

Total cloud infrastructure spending surged 43% Y/Y to $143 billion in Q2, the 11th consecutive quarter of accelerating growth and the fastest pace in eight years. The market has doubled over that period, with GenAI-specific cloud services growing 165% Y/Y, according to Synergy Research Group.

AWS maintained its leading 28% market share, compared to 20% for Microsoft Azure and 15% for Google Cloud. The three platforms now control 63% of the overall cloud infrastructure market, and 67% of public IaaS and PaaS spending.

All hyperscalers remain supply-constrained, so small quarter-to-quarter market-share movements should not be overanalyzed. The bigger story is a broad AI-driven reacceleration. Microsoft and Google are still growing faster, but AWS has held its 28% share while accelerating from a much larger revenue base.

🧠 Trainium beyond AWS

Amazon is exploring selling Trainium chips separately to customers operating their own data centers. That could turn Trainium from an AWS-exclusive advantage into a merchant-chip business, expanding Amazon’s addressable market beyond the cloud.

The trade-off is whether selling Trainium more broadly weakens one of AWS’s clearest cost and performance advantages.

🛒 Grocery changes the shopping habit

Amazon now offers same-day perishables in 2,300 US cities. Monthly active perishables customers have increased 50% since the start of the year, while orders containing perishables average three times as many units.

The opportunity extends beyond grocery revenue. Grocery can increase purchase frequency, basket size, delivery density, and advertising inventory at the same time.

🏗️ Big Tech’s cash engine

In Q2 2026, the leading hyperscalers grew their trailing-12-month operating cash flow by 34% to $660 billion.

That cash engine allowed Big Tech to begin the AI buildout without relying heavily on outside capital. But the scale of investment has now caught up: free cash flow has turned negative at Amazon and Google and fallen close to zero at Meta. The next phase is already pulling more debt into the equation. Amazon issued debt this year and says it will continue evaluating its funding options (in Alphabet’s case, that includes equity issuance).

Amazon argues this is a timing mismatch rather than a deterioration in economics. It is spending years ahead of demand, while the resulting infrastructure could generate revenue for decades. If Jassy is right, today’s free-cash-flow collapse is the price of locking in tomorrow’s capacity. If demand, pricing, or utilization disappoints, that operating leverage works in reverse.

Next up: Saturday’s massive PRO edition, with more than 30 companies visualized.

That’s it for today!

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Disclosure: I am long AMZN, GOOG, META, and MSFT in App Economy Portfolio. I share my ratings (BUY, SELL, or HOLD) with members.

Author's Note (Bertrand here 👋🏼): The views and opinions expressed in this newsletter are solely my own and should not be considered financial advice or any other organization's views.

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Jensen Huang used his first-ever X post last week to enter Washington’s fight over open-weight AI. He shared an open letter initially signed by 25 companies, including Microsoft, Meta, and Palantir. The coalition urged policymakers to preserve the development and deployment of open-weight models.

Satya Nadella quickly amplified the message, arguing that openness is essential to a healthy AI ecosystem.

To understand why the industry is clashing over this policy, it helps to distinguish how AI software is delivered:

• Closed models (proprietary): The model’s internal weights remain locked behind an API. Companies such as OpenAI and Anthropic control the security guardrails, computing infrastructure, and pricing.

• Open-weight models: The pre-trained weights can be downloaded and inspected. Businesses can customize and host the software on their own infrastructure without paying every query fee to a single vendor.

The immediate catalyst is model distillation, where developers use outputs from leading closed models to train cheaper alternatives. It is the same concern behind US accusations that Chinese lab Moonshot AI used a leading American model to improve Kimi. Closed-model providers argue that unrestricted distillation amounts to intellectual-property theft. Supporters of open weights see it as part of the competitive process that lowers costs and broadens access.

OpenAI, Anthropic, and Google were initially absent from the letter. OpenAI later joined after Sam Altman said he wanted the US to lead in both open and closed models, while Google’s Sundar Pichai endorsed the effort on the company’s behalf. Anthropic remained the clearest holdout, arguing that it does not want to ban open models but supports stricter chip controls, action against industrial-scale distillation, and mandatory safety testing for all capable systems.

NVIDIA reinforced the campaign this week by launching the Open Secure AI Alliance, a coalition of nearly 40 companies building tools to defend against AI-powered cyberattacks. Microsoft, SpaceX, and IBM are founding members. Anthropic, OpenAI, and Meta are notably absent.

The policy fight matters because Microsoft is hedging both outcomes. It maintains a multibillion-dollar closed-model alliance with OpenAI while positioning Azure as the indispensable platform for open-weight deployment. Microsoft does not need to predict which model architecture wins. It wants to provide the compute, governance, and security layer underneath all of them.

In this Q4 breakdown (June quarter), we analyze how that strategy is playing out.

Today at a glance:

1. Microsoft’s Q4 FY26.

2. The sovereignty play.

3. Earnings call takeaways.

4. What moves the needle?

1. Microsoft’s Q4 FY26

Income Statement:

• Revenue +18% Y/Y to $90.0 billion ($2.4 billion beat).

• Gross margin 67% (-1pp Y/Y).

• Operating margin 45% (flat Y/Y).

• Non-GAAP EPS $4.74 ($0.50 beat).

Core business segments:

• 📊 Productivity and Business Processes grew 14% Y/Y to $37.8 billion, supported by M365 Copilot, E5, and early E7 momentum, alongside stronger M365 commercial products revenue.

• ☁️ Intelligent Cloud grew 32% Y/Y to $39.3 billion, driven by 43% Azure growth as Microsoft improved fleet efficiency and brought new capacity online faster.

• 🎮 More Personal Computing declined by 4% Y/Y to $12.9 billion, as weaker Windows OEM and Xbox revenue outweighed 10% growth in Search advertising.

Key Trends:

The table below compares growth year-over-year in constant currency. Some of the products and services overlap.

Cash flow:

• Operating cash flow grew 30% Y/Y to $55.4 billion.

• Free cash flow declined by 23% Y/Y to $19.6 billion.

Balance sheet:

• Cash, cash equivalents, and investments: $76.8 billion.

• Long-term debt: $31.1 billion.

So what to make of all this?

Read more