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Steady Compounding

Warren Buffett Investing Process, Satya Nadella views on AI, Lululemon third-quarter—3-Bullet Sunday

Published 4 months ago • 5 min read

Hey Reader - Thomas here.

Good day to my fellow compounders!

In 3-Bullet Sunday, I share with you the three most interesting pieces of articles, videos, or podcasts I came across for the week on investing and growth philosophies.

Enjoy!

Bought Stocks Recently?

If you've snagged some great businesses during this drawdown, a reminder that the big money is made in the waiting.

Which also means you have to structure your finances, and portfolio to survive both the financial and emotional turbulence that could come your way.

To reap the rewards of compounding, survival is key.

Invest wisely,

Thomas

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I. Warren Buffett Investing Process

Alice Schroeder is Warren Buffett's biographer, and she shared about his decision-making process in 2008 at the Value Investing Conference.

It provided an invaluable peek behind Buffett’s decision-making process when evaluating a new business.

​>> Click here to read the transcript​

Some of my highlights:

If there's a good probability of catastrophe risk, it's an immediate no

The first step in Warren’s investing process is always to say, “What are the odds that this business could be subject to any kind of catastrophe risk that could make it just fail?” If there is any chance that any significant amount of his capital could be subject to catastrophe risk, he just stops thinking. No. And he won’t go there.

Warren doesn't use a model at all, no projected earnings or returns.

Everybody that I know — or knew as an analyst — would have created a model for this company and would have projected out its earnings and would have looked at its return on investment in the future. Warren didn’t do that. In fact, in going through hundreds of his files, I’ve never seen anything that resembled a model.

Here's what he did instead—identify the handful of factors that could make or break the thesis.

He figured out the one or two factors that could make the horse succeed or fail — and, in this case, it was sales growth and making the cost advantage continue to work. Then, he took all of the historical data, quarter by quarter for every single plant, he got the similar information as best he could from every competitor they had, and he filled pages with little hen scratches of all this information and he studied that information.

Buffett's "DCF" model—15% returns from day one

He looked at them in great detail — just like a horse handicapper studying the tip sheet — and then he said to himself, “I want a 15% return on $2 million of sales.” And then he said, “Yeah, I can get that.” And he came in as an investor.
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So what he did is he incorporated his whole earnings model and compounding discounted cash flow into that one sentence. “I want 15% on $2 million of sales.”
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Why 15%? Because Warren is not greedy. He always wants a mere 15% day one return on an investment and then it compounds from there. That’s all he has ever wanted. He’s happy with that. It’s a very simple thing. There’s nothing fancy about it.
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I think that’s another important lesson because he’s a very simple guy. He doesn’t do any kind of discounted cash flow models or anything like that. For decades, he just says, “I want a 15% day one return on my investment and I want it to grow from there.” Ta da!

II. Satya Nadella | BG2 w/ Bill Gurley & Brad Gerstner

video preview​

Some good insights into AI and how its reshaping the tech world.

Some of my highlights:

AI Arms Race

  • Competitive Landscape: Nadella acknowledged the competitive landscape of the AI industry, with major players like Google, Amazon, Meta, and now Elon Musk's xAI entering the fray. He emphasized that, unlike previous tech shifts, all the major players are now actively participating in the AI revolution
  • Not Winner-Take-All: Nadella believes that the AI industry won't be winner-take-all. He anticipates multiple winners at different layers of the AI stack, including infrastructure, models, and applications.

Legacy Search (Google) and Consumer AI

  • Changing User Habits: Nadella discussed how consumer habits are changing with the rise of AI. He noted that younger generations prefer direct answers from AI agents like ChatGPT over traditional search engines.
  • Bing's Role: Nadella emphasized the importance of Bing and the broader search business, even in the age of AI. He highlighted Microsoft's efforts to integrate AI into Bing and develop new AI-powered consumer products.
  • Distribution Challenges: Nadella recognized Google's distribution advantages in the search market, particularly on mobile devices. He stressed the need for Microsoft to innovate and leverage its strengths, such as the Windows operating system, to compete effectively.

The Future of AI Agents

  • Agentic Interactions: Nadella discussed the rise of "agentic" interactions in enterprise settings, where AI agents can seamlessly interact with various business applications and data sources. He envisioned a future where AI agents would handle scheduling, communication, and data analysis, significantly improving productivity.
  • Permission and Control: Nadella emphasized the importance of user permission and control in the context of AI agents accessing and interacting with applications and data. He highlighted the need for clear guidelines and security protocols to ensure responsible AI implementation.

Leveraging AI within Microsoft

  • AI for Productivity: Nadella discussed how Microsoft is leveraging AI internally to improve productivity and efficiency. He cited examples like using AI for customer service, code development with GitHub Copilot, and streamlining workflows across various departments.

The Cost of Model Scaling and Inference

  • Scaling Laws and Economic Realities: Nadella discussed the balance between the benefits of scaling AI models and the economic realities of training and inference costs. He noted that while scaling laws suggest performance improvements with larger models, practical limits and economic considerations exist.
  • Optimizing Inference: Nadella highlighted the importance of optimizing AI inference to improve efficiency and reduce costs. He discussed techniques like test-time computing and diverse hardware architectures to balance performance and cost.

III. ($) Lululemon: Market is Optimistic About Q4 and Beyond

This week's Insider Stock article is on Lululemon.

Members, login here and read my updated thoughts on Lululemon Q3 results

Not a member yet?

​>> Click here to join and access my entire archive of stock research​

That's all I have for you today!

Till next week.

Thomas

Founder of Steady Compounding

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Steady Compounding

by Thomas Chua

I write about investment concepts, business breakdowns and timeless lessons from super investors. Featured on Business Times, Channel News Asia (CNA) and more. Read by over 10,000 investors.

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