Q3 Earnings Call Write Up & Transcript

Please just look and read the earnings calls from Amazon and Google.

You'll see where their money is going: AI, Artificial Intelligence (not Allen Iverson)

Look at how much money they are making from utilizing AI and creating new AI products and services. And look at how much money they are reinvesting back into AI chips, AI infrastructure, and AI agentic cores. These are not startups chasing trends. These are two of the largest and most profitable companies in the world, both committing extraordinary amounts of capital toward the same goal at the same time.

Every quarter, their financials tell the same story. AI is no longer an experiment. It is a core business driver. When you read the earnings calls and 10-K filings, you can see where the future is going by looking at the data itself. This is not about speculation or opinions. It is about the numbers.

That is what matters most to us as investors: following the numbers, not the noise.

HOW TO READ AN EARNINGS CALL

Anyone can skim a headline. Investors read the transcript.

1. Revenue and operating income. What is actually growing? Ignore adjectives and look at the cash.
2. Segments. Separate the divisions: cloud, advertising, subscriptions, and retail. Momentum rarely moves evenly.
3. Backlog and run rate. Backlog shows committed future revenue. Run rate shows current scale. Together they show direction.
4. Capital expenditure. This is where conviction lives. When a company spends tens of billions on power, chips, and data centers, that is not talk. That is action.
5. Product specifics. Listen for product names, user numbers, and features. Those prove execution.
6. Analyst Q&A. This is where tons of great questions get brought in to hit on the bullet points of each call that analysts know will make the stock go up or down (extra massive expenditures, tax events, pop in a segmented revenue etc). It is where management gets tested on adoption, supply, and margins.

AMAZON

Scale and income. Revenue reached $180B for the quarter, up 12% YoY. Operating income was $17.4B even after more than 4 billion dollars in one-time charges. Beneath those charges, profitability is expanding.

AWS reacceleration. AWS revenue grew 20.1% YoY to a $132B annualized run rate. Backlog climbed to roughly 200 billion dollars. These are signed commitments from enterprises running their workloads and AI models on AWS.

AI products and revenue. AWS now monetizes AI at multiple layers. Bedrock for inference, SageMaker for model development, AgentCore and Strands for building secure and scalable AI agents, Kiro and Transform for code automation, and Rufus for AI-driven shopping experiences. AgentCore already has more than one million developer downloads. Amazon Connect, which uses AI to power customer contact centers, surpassed one billion dollars in annual revenue. Rufus, the shopping assistant, is responsible for billions in incremental sales.

Capacity and silicon. In the last twelve months AWS added 3.8 gigawatts of new power capacity. It expects to double that again by 2027. Project Rainier now runs nearly 500,000 Trainium2 chips (WHICH THEY PRODUCE THEMSELVES) powering Anthropic's Claude model, with capacity for one million chips by the end of the year. Trainium2 revenue grew 150 percent from the prior quarter.

Investment commitment. Amazon expects capital expenditures of about 125 billion dollars this year, increasing again in 2026. Most of this is for AI infrastructure. That is what conviction looks like in financial form.

GOOGLE: MONETIZING AND EXPANDING THE AI ECONOMY

A record quarter. Alphabet reported its first $100B revenue quarter, up +16% YoY. Every major business line increased at a double-digit pace.

AI as the central engine. Management stated directly that AI is driving results across the entire company. This shows up in numbers, not narratives.

Google Cloud revenue grew 34% to $15.2B with a 24% operating margin (OH MAMA). The backlog reached $155B, up 46% from the previous quarter. Cloud signed more billion-dollar deals in the first nine months of 2025 than in the previous two years combined.

AI in practice. Gemini models now process billions of tokens per minute and are embedded across Search, YouTube, Android, and Workspace. AI Overviews and AI Mode are lifting both total and commercial query volume. Gemini Enterprise already has millions of paid seats. YouTube continues to expand monetization through AI-driven creation and shoppable video.

Capital intensity. Google increased 2025 capital expenditure guidance to 91 to 93 billion dollars and expects to invest even more in 2026. About 60 percent of that goes to servers and 40 percent to data centers. These are foundational assets built for decades of demand.

Profitability and diversity. Cloud operating income grew 85 percent. YouTube subscriptions are expanding. Advertising remains healthy. The company is growing revenue while investing heavily in infrastructure, which is a rare combination.

WHY WE BELIEVE THIS IS STILL THE BEGINNING

AI is not a cycle that will end in a few years. It is a multi-decade technological shift that will define productivity and profit generation across industries.

Three key realities stand out.

1. Sustained demand. The combined cloud backlog of more than 350 billion dollars between Amazon and Google represents locked-in AI spending for years ahead.
2. Infrastructure acceleration. Both companies are adding chips, power, and data centers faster than they ever have before. They are building for demand that has not yet arrived.
3. Expanding monetization. Each product launch, AI agents, code tools, inference APIs, and advertising systems—creates new recurring revenue streams.

HOW TO TELL A BOOM FROM A BUBBLE

A bubble happens when prices rise before revenue does.

A boom happens when revenue and cash flow rise first, and prices follow later.

Amazon and Google are already earning billions of dollars from AI and using those same profits to fund the next generation of AI chips, data centers, and software. That is not speculative behavior. It is disciplined expansion supported by cash flow.

Our work as investors is to study the data, read the calls, and understand how capital allocation reveals conviction. Short-term sentiment will shift, but capital deployment at this scale signals a lasting opportunity.

READ THE FILINGS

If you want to know whether we are in an AI boom or an AI bubble, the answer is already written in the earnings calls and the 10-Ks.

Read the numbers. See how much Amazon and Google are earning from AI today.

See how much they are reinvesting in the systems that will define tomorrow. Look at the billions being allocated to data centers, chips, and AI platforms.

That is not what the end of a cycle looks like. That is what the beginning of a new industrial era looks like.

Decades from now, investors who took the time to read and understand these filings will be the ones who owned the future. We plan to be among them.

This is informational and not investment advice. Investing involves risk and loss of principal. Past performance does not guarantee future results. We and our clients may hold positions in securities mentioned and may trade without notice. Indices are unmanaged and cannot be invested in directly. Data is believed reliable but not guaranteed. We do not provide tax or legal advice. See our Form ADV for details.