#663: We’re living through the first era in which an investor can ask a machine to read a decade of SEC filings in seconds. That sounds powerful, but also a little terrifying. Can we trust it? And how do we use it without falling for hallucinations or built-in optimism?

In this episode, we dig into the practical, real-world ways AI can strengthen our investing process while avoiding its biggest pitfalls. If you’ve ever wondered how to blend old-school fundamentals with new-school tools, this conversation will open up an entirely new mental model.

Our guest is Brian Feroldi, an investor who has spent more than twenty years doing classic, deep-dive fundamental research. He reads SEC filings for fun, and he’s embraced AI not as a stock picker, but as a force multiplier that can turn days of research into minutes.

We talk about the specific guardrails that make AI useful for fundamental investors, including restricting sources to trusted filings, designing step-by-step instructions, and assigning the AI a role so it knows how to “think.” We also explore how to stress-test optimism bias, how to analyze companies like a forensic accountant or a short seller, and how to build prompts that match your own investing personality.

Whether you’re an index-fund loyalist with a little “fun money” or a hands-on analyst, this conversation will expand the way you evaluate businesses and make decisions.

Key Takeaways

Resources and Links

Chapters

Note: Timestamps are approximate and may vary greatly across listening platforms due to dynamically inserted ads.

(03:02) Pros and cons of using AI for stock research


(4:55) Why Brian invests heavily in individual stocks


(12:52) Guardrails for reducing AI hallucinations


(17:22) How to write step-by-step prompts


(24:02) Using roles to shape AI’s output


(35:57) Running Brian’s prompt on Kava


(46:22) Understanding pricing power and recession behavior


(01:00:02) Evaluating management teams


(01:06:02) Using AI to reflect your investing personality

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