Afford Anything - Why AI Misleads Investors and How to Fix It

Episode Date: November 25, 2025

#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 How a single prompt can transform AI from a loose generalist into a sharp, reliable research assistant.
 The surprising way optimism bias shows up in AI tools, and how to flip it to your advantage.
 Why limiting your data sources can make your analysis dramatically stronger.
 The role-play trick that helps you see a company the way a short seller, value investor, or even Warren Buffett might.
 A simple reframing that turns AI from a stock picker into something far more powerful for decision-making.
 The moment in the demo that revealed a blind spot even seasoned investors often miss. Resources and Links Get Brian’s free business-analysis prompt at longtermmindset.co/ai Check out Brian’s YouTube channel: Long-Term Mindset @BrianFeroldiYT 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 Share this episode with a friend, colleagues, and your family around the Thanksgiving table: https://affordanything.com/episode663 Learn more about your ad choices. Visit podcastchoices.com/adchoices

Do you remember that pretty famous story about chat GPT telling a lawyer that a bunch of fake court cases were real? So if you haven't heard about this, chat GPT basically hallucinated a bunch of fake court cases and the lawyer presented it at court. And, well, that did not end well. Given the AI tends to hallucinate, why would anyone trust AI to analyze their investments? Well, that's a rhetorical question. And my guest today has some answers because my guest today has figured out how to turn chat GPT and other types of AI from a highly imperfect machine that hallucinates into a legitimate junior financial analyst that only uses SEC filings. Today's conversation is going to center around how to use AI responsibly when you analyze

your investments. Today's guest is Brian Feroli. He is a financial educator and author. He's written over 3,000 articles for the Motley Fool. He is the author of the book, Why Does the Stock Market Go Up? He runs the YouTube channel Long-Term Mindset, which has about a quarter million followers, and he has more than 600,000 followers on Twitter where he teaches investors about how to analyze businesses. So he talks about how to read income statements, balance sheets, cash flow statements. And today he joins us to talk about how to use AI as your junior analyst. Welcome to the Afford Anything podcast, the show that knows you can afford anything, not everything. This show covers five pillars, financial psychology, increasing your

income, investing, real estate and entrepreneurship. It's double I fire. And today's episode is all about that first letter I, investing. Most of you, including myself, are index fund investors, which is amazing. So if you're thinking to yourself, hey, if I'm an index fund investor, why should I care about analyzing individual stocks? Well, a couple of reasons. Number one, even if you're 95% in index funds, many of us have a little bit of fund money in individual stocks, like some Apple shares that you bought back in 2015.

So that's one reason. The other is that learning how to actually evaluate whether or not a company is worth your investment, that is a skill set that has tremendous value because if you know how to evaluate businesses, then you, as a business owner, as an entrepreneur, as a person who works at a company, you understand how business is run,

you understand what makes businesses profitable, and that makes you more valuable to your company, either as an employee or to the company that you might one day start and run. Learning business valuation, learning company analysis is a highly adaptable and transferable skill set. And today Brian talks about,

how AI can be your partner in that. So with that said, here he is, Brian Faroldy. Brian, welcome. Thanks for having me, Paul. Awesome to be here. Thanks for being here. Can you tell us about the pros and cons of using AI to choose stocks? I am a fundamental investor. I have been researching stocks the traditional hard way for two decades now. And to me, that means reading SEC filings, reading earnings reports, listening to conference calls, reading analyst reports, all that kind of thing. When AI kind of exploded onto the scene, I guess we're in year three now. Initially, I was a little put off by it because it seems so new. But over the last year, I've really tried to adopt AI in my everyday life.

And what AI is so good at, it's taking huge amounts of data, huge amount of quantities of data. and compressing it and explaining it to you in an easy-to-understand way. I think if the listeners here have used AI, and I'm guessing 100% of them have at this point, they're kind of familiar with the pros and cons of AI themselves. On the pros, it's really good about giving information fast and digesting it.

On the cons, if you've used it for any amount of time, you know that it tells you incorrect information and it has an optimism bias built into it. So from a pro perspective, I think that AI can be an invaluable, tool for fundamental focus investors like me to help them analyze companies and analyze stocks, but you have to put in strong guardrails in place because of that bias that's built into chat TBT to be so positive and to essentially make up stuff. So as long as you use chat

GPT the right way or AI the right way, I think it can be in a wonderful tool. All right, I've got some follow-up questions, both about hallucination and about the optimism bias. But before we get there, I'd first like to establish you are largely an index fund investment. master, yes? Yes. I have a good chunk of my net worth. All of my retirement funds are an index funds. The bulk of my net worth, about 70% of my net worth, is in individual stocks. Oh, really? 70%. Why is it that you're comfortable with such a major proportion of your portfolio in individual stocks? From an overall asset allocation perspective, all the studies that I've shown and all the data, the long-term data is clear. Equities is the place you want to

be in the long-term. So I just believe that in my core. The reason that I have gone the individual stock route is because I'm the type of person that likes to dive into the details. And when I first learned of investing 20 plus years ago, I thought that picking stocks was the way to go. And I just, for whatever reason, the idea of analyzing companies and becoming a stock picker really fascinated me and really took hold in me. And I recognize that that is not for everybody. I'm the type of person that would read SEC filings for fun. Like to me, that would be more fun to analyze a company that I'd never heard of than to watch a Marvel movie. So I'm not up to date on the latest Netflix shows or anything like that, but I just really like the details of investing. And the reason it's become such a

large portion of my portfolio isn't because I set out to do that. It's because my investments have done so well over the last 20 years that the individual stocks that I have honed as a group have come to dominate my net worth. Oh, okay. So in terms of a cost basis, how did it originally start from a cost basis point of view. Yep. So I tried to do it as tax efficiently as possible. So I've always tried to max out all of my tax advantage accounts, my 401K, my Roth IRA, et cetera for both me and my wife. Anybody that has a 401K, which is a majority of way that most people invest into the markets, knows that one of the downsides to a 401k is you're very restricted on what you can do.

You are very restricted to the options that the company that you are working for give you. So I tried to invest in as low cost away as I could through those vehicles, so I put them into index funds whenever that was an option for me. And just as a broad category decision to make my life as easy as possible, I made the decision all of my retirement funds are going to be in index funds. Done, easy, simple, no thinking, dollar cost averaging, wonderful way to invest for the long term. But with the quote unquote active portion of my portfolio, with the capital that wanted to put into the market that was beyond the limits of 401k and Roth IRA, that I chose to be more tactical with and to go the individual stock route. That was my broad capital allocation decision

making. Let's come back to then AI. We know that AI hallucinates. Sometimes it can hallucinate over even the most basic of details. Given that reality, is it really prudent to turn to AI for any investment decision generally, much less individual stock picking. Yeah, your first instinct is totally correct. You should be skeptical. After all, this is your money on the line, right? This is your hard-earned money that you're putting at risk. I don't like to put my capital at risk unless I'm absolutely convinced in the fundamentals of the investment that I'm making. Given that AI hallucinates, this is one reason why I was super skeptical for years about using AI to help me make these decisions, simply because I did not want to be making investment decisions

based on faulty information, right? You'd be building a skyscraper on a foundation built on quicksand. That would not be a good strategy. However, as I've studied AI and I've talked to some people that are way better at AI than I am, I think that there are some simple rules that you can adopt that will dramatically increase the quality of the information that you get back from AI, so much so that if you follow the structure that we're going to talk about, I now have full confidence in the information that I'm getting back from AI. Okay. Let's talk about some of those. How is it that you put those

guardrails in place? Yep. Rule number one to me is to insist that whenever chat GPT or any AI gives you information back, that you force it to use original sources that you trust. So as an investor, one original source that I trust is the SEC, the Securities and Exchange commissions. So one of the rules that I put into the prompts that I built is you are only allowed to source information from the Securities and Exchange Commission, or you're only allowed to source information from sources that I personally trust. Very few sources. So for me, that's the SEC, that's company filings, and then there's a few third-party sites such as like Morningstar.com when I'm analyzing a company's competitive advantage. But if you just first and foremost insist on the sources

that the prompt use, that alone will dramatically increase the quality of information that you get back. Would another way of doing that be to find certain sources? So, for example, to download the SEC filing, PDF it, upload it, and say, do not use any information from the web, only use information that comes from this PDF that I have uploaded here. Yep, absolutely. Anything that you can do to restrict the information that AI is pulling from to a source that you trust, again, will dramatically increase it. In fact, we're going to go through this prompt later. But one of the things that I insist on on the prompts is whenever you present with a number, you also have to simultaneously give me the link to the information that you got that number from. So when I'm reading

through the prompt and when I'm actually referencing a number that's pulling up, I can click over to that original source and if I want to double check where the number came from right in the prompt itself. So if I'm like, okay, it's saying this company did 50 million in revenue, if I click over the SEC filing and I scroll down, I can verify that the SEC filing gave me that number. When you see that, then it's like, okay, I trust this information. Do you go through and methodically check each one, or do you randomly spot check? So it depends on the information that I'm looking for and the quality of the information that I'm going for. So I primarily use Chad GPT as my AI, and I use this mostly for high-level overview of stock.

So if I'm analyzing a company for the first time or I'm analyzing an earnings report on a company that I own, it's wonderful for turning over rocks, if you will, for like, is this a good company? this is a filter to use because it can do that so, so quickly. If I was going to actually buy it, there's deeper analysis that I would want to do and with different sources. One source that I use is called fiscal.a. And that's a website that pulls directly from SEC filings and helps me chart and graph all kinds of numbers and stuff like that. So I think AI is a wonderful source for a first pass and getting to know a company.

But if I'm going to go deeper on it, there's other sources that I use. All right. Tell me more about the prompts. So you've talked so far about restricting the source. material that AI uses. Beyond that, what else do you do within the prompts to reduce the risk of hallucination? Another thing that I do is I give the prompt exact step-by-step instructions that I wanted to do. So, for example, let's say I was researching Apple's stock. I wouldn't type in the chat GPT. Is Apple a buy? Right? Like, that is such a broad statement, and that is, that gives

chat GPT or NIA way too much freedom to interpret that. I think a good mental model to get in your mind is you have to think of AI like a junior analyst or a junior intern that is eager to do whatever you tell it to, the instant that you tell it to. If you were hiring an intern to come in and you said something like go research this guest and that was the only information to give them, they would go off and comply and come back with information. And it might be in a format that is completely incoherent to you. If you gave that same intern the instructions for, I want you to start by going to this person's LinkedIn bio.

Then I want you to write down where they went to school. And then I want you to go up and pull up an interview they just did. I want you to write down the questions that they had. And you gave them step-by-step instructions for how to do the thing. Obviously, the information that you're going to get back would be so much better because it's in a format that you want and it's following the exact instructions that you are giving it. Chat TPT and AI works the same way. So in the prompts that I built, I say, step one, use these sources.

step two, go to this part of the 10K and look up this information. Step three, answer this question. Step four, answer this question. Step five, after all this is done, give it to me back in this format and in this order. So by insisting on it follows a step-by-step function that I created, the information that I get back is exactly in the order that I want it to be in. You know, the comparison to a junior analyst makes a lot of sense or a junior or an intern because so much of the time, you know, the challenge of hiring and training is being able, you know, ideally you hire and train because you're busy and you need to offload work, but it gets worse before it gets better because you have to do so much work up front in terms of preparing a clear set of instructions for any juniors.

Yeah, if you've ever hired an assistant or anything like that, I like to think of it as like 108010 as the broad framework. 10% of the work is just creating the instructions for what you want to do. That is on you to do that, you the employer or you the boss. You have to do that first 10% to say, here's what we want to do and here's the instructions to do it. The 80% is the actual going through and executing on the instructions, right? That's what AI is designed to do. If you give it a good framework, it will go out and do that hard work for you and come

back with information. Your job is then to take that information, do the final 10%, which is interpret the results that you're seeing. So AI can be wonderful with handling the middle 80%, the same way a virtual assistant would be good with handling the middle 80%. But you have to give them good instructions, and then you have to check their work. That's still on you. Right. And then part of that final 10% would also be iterating on the first 10, right, based on, you know, giving feedback and iterating on that first 10% based on how well they've done in that middle 80.

Yeah, absolutely. And I know that you've hired people before. And so you know the quality of the information that you give them or the standard operating procedures that you, you tell them to follow, the more clear you can be with that, the less errors there are, the less communication there needs to be back and forth, and the happier you are with the output of the work. Right, exactly. All right, let's continue going through some of the prompts. Let's see the process for how you shape these instructions. So one key prompting technique, and this works for anything, not just for researching our

companies. AI works really well when you start out by assigning that AI to have a role. So, for example, if you're going to be an investor, one thing that you can tell the AI to do, is if you're a value investor, say, act as Warren Buffett. Or if you're a growth investor, you can say, act as David Gardner, recent guests on your podcast. Or if you're going to be a short seller or diving deep into the financials, you can say, act as a forensic accounting or act as a financial analyst. Just by giving it that instruction up front to put it in the framework,

suddenly the information that it will pull from in its database is going to be restricted to that role that it has. So again, if I say to the AI, act as Warren Buffett, it's going to instantly know what the word moat means. It's going to know to emphasize things like competitive advantage and return on equity and a strong balance sheet and long duration of compounding. And it's going to reference all of the data that's out there on Warren Buffett and his investing style. So just by giving it that simple prompt upfront to assigning it a specific role that will restrict the data that it can use and it will dramatically increase the quality of the output that you get. Now, what I see here is an inherent conflict in asking it to be Warren Buffett while simultaneously not necessarily wanting it to

pull from any source online, including garbage sources. So what's going through my mind is maybe uploading a bio of Warren Buffett as part of that PDF and saying, act as Warren Buffett based only on the information that's in this PDF, do not use any outside sources besides this PDF. Would that be a way to do it, or would you trust it to have at it to interpret who Warren Buffett is and what his philosophy entails. Yep. If you wanted to take the next step and kind of prompt it with a role and a really specific role and put that in as the very first prompt that you do, that can be one way to do it. From what I've found, just putting into the prompt itself, just giving it a role up front and saying, act as Warren Buffett or act as a financial anus, to me, that does the job.

But if you want to go to the next step and give it a more detailed profile so that it's using that, that more power to you. Okay. So assigned it a character role. What else? So step two is like we said before, ground everything with trusted sources. So come up with the list of trusted sources for it to pull data from. I don't think it could go wrong with just saying the Securities and Exchange Commission or company filings or company earnings reports. That will dramatically cut down on hallucinations. And you can also, if you want to go to the extra level, put an extra step there for it to verify the information that it's getting. I've done things before like, say something like pull up the most recent 10Q. 10Q is a quarterly report that comes

out that companies issue three times per year when they're reporting earnings. And sometimes it pulls up a 10Q, but it's not the most recent 10Q. So just by saying things like, the first thing is to start with what year is it or what day is it? And then say, pull up the most recent one. Sometimes as a chat TPT can get a little bit tripped up unless you give it literally that specific of instructions. But assign it a roll and give it the sources to pull from. That's a great foundation. Okay. Assign it a roll. Give it the sources to pull from. Be incredibly specific and clear in your questions and your instructions. That's step one and step two. Yep. And then step three is to give it a step wise structure to go through. So a step one, a step two, a step three,

and break it down in specific sequence that you wanted to do as if you were explaining it again to an intern, someone that had never done this before. So for me, that would be things like Step one, acquire the data using these steps. Step two, verify that the data sources are accurate. Step three, now that we have that established, go through these specific questions in order, and step four, report them back to me in this formatting. So one, two, three, four, the clearer you can be with the instructions you want it to follow, the better the information you will get back. How do you know, so I'm thinking about some of the people who are listening to this, who are primarily indexed fund investors, because we have many people who listen to

this are, myself included, are predominantly index fund investors. Many of us are not super acquainted with stock analysis to begin with, even absent AI. So if that is your situation, how do you know enough to know the steps that you want and the formatting that you want? Yeah, great question. My analysis shows that there is about 60 million Americans that own individual stocks. So even if you're the type of person that has primarily put all of your assets into index funds, which I think is a fabulous strategy and should be the default strategy for 99% of people. Even in my own friend group, people that do that, they often also own invidia, or they also own Apple, or they even own, like our friend Brad Barrett, died in the world index investor,

yet he also owns Berkshire Hathaway, and he also owns Markell. So even him, who has been a huge proponent of index funds, still owns individual stocks. Now, as long as it's a small part of your portfolio and you're not risking your retirement on it, That's a perfectly fine thing to do. Some people call that fund money, some people call that play money, or they just want to learn about it. But if you're the type of person that's going to be investing in individual stocks, which many people do through stock-based compensation, through the company that they work for, I think it behooves you to always start by educating yourself, learn about the fundamentals of the company, learn the basics of reading financial statements, learn how to tell what makes for a good company. You don't have to go as deep as, say, Warren Buffett does, or as deep as I do, as deep as professional investors, but if you can just give yourself a grounding education in the basics of

business, how does the company make money, what are its key products or service, what are its growth prospects, what the heck is valuation, what risks do I think of? The more you can understand those basics, the more confidence you can have that owning that individual stock is a good choice. You know, and it's true. many people have some proportion, you know, a fund money fund where they can buy individual stocks. But I think a lot of people are vibes investors. They heard about something at the proverbial water cooler and on a lark threw some money at it and it either worked out or it didn't.

And if it worked out, then people can develop overconfidence and that can later, of course, come back to bite them. So I think many people get, you know, without the grounding in how to conduct fundamental analysis on a stock, I think a lot of people can start as vibes investors, either it fails or it succeeds, which is sometimes worse. That success leads to a confidence, which leads to an even bigger failure, ultimately, and then ultimately people just sort of get burned. Yep. And to me, if you're the type of person that bought a stock because a friend told you about it

and you did zero research on it, that's not investing. Right. That is just pure gambling. And if you look at the stock market, most people associate the stock market with gambling because they don't understand the absolute basics about what stocks are, what they represent, why their value changes over time, how the market moves in cycles, and what is it that causes stocks to appreciate or depreciate over time? To me, those are fundamental things. So I don't consider just knowing the name of a ticker, buying it, and then hoping it goes up to be investing. To me, that is just pure

gambling. Now, there's nothing wrong with that if that's what you want to do. do as long as you know that what you're actually doing is you're gambling. You're not investing. To me, investing is buying shares in a company that you have researched, approaching that company with a ownership mindset, with a long-term mindset, tracking the results of that company to make sure that the thesis, the reasons you bought it, are intact in the first place and owning it as long as those reasons are still in place. To me, that is investing. Right. So that then goes back to the construction of the prompt. Do you have sample prompts that people can use. Step three is create steps. And I think a lot of the people who are listening

are like, I don't know enough to know what steps to create. I have a prompt. If you go to long-term mindset.com, which is my website, backslash AI, I do have a free prompt that people can download. It's about 2,000 words long. So it's a pretty meaty prompt. And what it'll do is, and we can certainly go through this, it's a prompt that follows all of the techniques that we've laid out. And what it's designed to do is to go into any business that you name that's publicly traded, and it will answer seven questions that I think are foundational questions about the business, such as what does the company do? What are its main products and services? What countries does it operate in? How frequently do customers purchase that product? What happens

in a recession and can the company raise prices? Questions like that, which are things that I want to know as just foundational information before I would do any analysis on top of that. So yeah, if your listeners want to get a free copy of that prompt, just go to link. I'm hopefully in the description or something. Perfect. With regard to those foundational questions, one thing that strikes me is, okay, let's say I know what, I ask those foundational questions, and I learn what countries that company operates in. How do I contextualize that information? So let's just use a hypothetical company, and we'll say it operates in North America, Malaysia, Singapore, poor Indonesia, and its basis of operations are those two regions. What do I do with that

information? Is that good? Is that bad? I don't know. Well, now you know more about the company than you did before. For example, if you were to do this analysis on a company like Domino's, I think most people, when they hear the word Domino's would assume U.S. Pizza Company, and they sell pizza. If you ran this prompt, I think you would be surprised to learn that the majority of Domino's revenue comes from sourcing pizza. So selling pizza supplies to their franchisees in the United States, and they have a very strong presence in international markets. So just by doing this prompt, you would learn more about Domino's the company than you might assume because you're a consumer of that company's product. In fact, many companies that are

in the United States, McDonald's, Starbucks, Nike, in many cases, those companies get more revenue outside the United States than they do inside the United States. And once you understand that, if the U.S. market is not doing well and you're worried that a recession is coming, you can be like, okay, well, I know that this company actually gets the majority of its revenue from China or from Japan or from an international market. And even if our country is doing well, that doesn't mean sales in those other countries aren't doing well. And the company's results will be maybe better or at least buffered from that fact. Or you have to think about, well, if this company gets 80% of its sales from Brazil, then all of a sudden you have to worry about exchange rates, right? This company's results are going to be heavily influenced. by the relationship between the U.S. dollar and I think it's a Brazilian real. Real. Yeah. Okay. That's important information that you should know if you're going to be investing in a company.

So it's not to say that you should act in one way or another, but I think it's just absolutely foundational that you know where companies get their revenue from. That, to me, is essential information to know. You mentioned if you're worried about a recession in the U.S. In an increasingly globally interconnected world, a recession in the U.S. would have spillover effects that could lead to recessions globally or downturns globally at a minimum. I mean, we saw, I think, the ultimate example of that would have been 2008, which was truly a global. I mean, when people call it the global financial crisis, I think part of the reason it has that

name attached to it was because it was the most global crisis of its kind. And it was sort of the crisis that really cemented how very globalized all of our economies are. Yeah, absolutely. And you're right that if the U.S. isn't doing well, that typically does not spell good things for other countries around the world. And the inverse could also be true. The U.S. economy might be doing great, but China might be going through tough economic times or Brazil or Argentina or the U.K. or Europe, right? Different countries have different economies. And while they are largely integrated with each other, they can move in different directions. So again, one of the things that I want to know when I'm researching a company that's built into this prompt is what happens to this business in a recession? Or what happens to this company's revenue during tough times? There are some companies that their revenue and profits drop precipitously when the economy goes downward. Auto sales, for example, if the U.S. is in a recession, people delay buying a new automobile. It's also very highly sensitive to interest rates. So automakers like Tesla, like Ford, like GM, you can expect that those companies' revenues are going to fall dramatically if the economy,

if the U.S. is doing very, very poorly. Other companies like Walmart or Dollar General, for example, those companies actually do better. Their businesses improve when times are tough in the U.S. because consumers are trying to stretch their dollar further trade down and they shop at places like Costco or Walmart or Dollar General. So their sales actually improve. So again, that's kind of foundational information that I want to know what has happened to this company's revenue in past periods of economic stress

so that I know if I'm investing what to expect. You know, when I was a kid, I remember on Christmas morning, I got lots of toys, lots of books, lots of clothes, gifts. The books were always my favorite. I'd spent all of Christmas Day just reading and reading and reading. But, you know, none of those are things that I have anymore. They were wonderful in the moment, but decades later, I have no idea where any of those things went. But by contrast, when you give a gift that brings somebody financial security, that's something that lasts a lifetime. Now, when it comes to financial security, nearly half of American adults,

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With PolicyGenius, real users have gotten 20-year, $2 million policies for just $53 a month. Don't wait until next year. Give your family the gift of security today with PolicyGenius. Head to PolicyGenius.com to compare life insurance quotes from top companies and see how much you could save. That's PolicyGenius.com. All right. We prompt the AI, and that includes these seven foundational questions that really give us a backbone of understanding what this company does, where it operates, how it makes money, how it operates in different economic cycles. What next? What's step four? Well, so step four is run the prompt and analyze it on the company and read and start to interpret the results. And this makes for horrible audio. So I apologize. to everyone that's listening. But perhaps we could run this prompt on a company that you know

or you're interested in and we can kind of talk through the results. Perfect. Okay, let's do it. Great. So I have, for people that are watching on YouTube, here is the prompt I'm going to be reading through. So at the top, it says the identity is acting as a financial expert by doing business model analysis from SEC filings. I gave it a clear mission, which is to prompt the user for the company a name. I gave it clear execution triggers for looking up the SEC filings. in an order. I gave it seven questions that I wanted to go through and answer those questions specifically. And then I gave it the instructions for here's how I want this information to be presented back to me. And I insist that there's sources on all the information and more. So I'm

just going to push enter, run that into a chat TPT. Is there a company that you know fairly well or have, want to analyze? There's a company that I actually know almost nothing about that I'm curious about. And it's Kava. Kava. They are a fast, casual, Mediterranean food eatery. So imagine like a Chipotle of Mediterranean food. Yep, great way of saying that. If anyone was familiar with Zoe's Kitchen. Zoe's Kitchen was a company. Kava actually bought Zoe's Kitchen out and rebranded all their names to Kava. So I know a fair bit about Kava. Many people are calling it, quote, unquote, the next Chipotle. If you don't understand that reference, Chipotle has been a sensational long-term investment since it was spun out of McDonald's in

2005, I think, something like that. But yeah, let's do Kava. Yeah, I don't know anything about it. I've actually never even eaten there. Oh, highly recommend it. I think you love it. Okay. I have long wondered if it's going to be seeing how quickly these locations pop up. Yep. I've long wondered, is this the next Chipotle. And it's been a very hot stock since it came public. So I ran the prompt and chat TPT is saying it understands the prompt and it says what company, name or ticker, I like to include both. Would you like me to analyze? So all I did is type in Kava here and I pushed answer. So chat TPT is going to do this thing and I'll read from the top and we'll and we'll see how it does. So it says using Kava group, so the name of the company is Kava's group, 10K as of December 29th,

2024 and it's 10Q from Q1 and Q2 of 2025. So right at the top here, the information that's going to be using are from SEC filings that are the correct year. So that's a good start. So question number one that I have this prompt answer is, what does this company do? So let's read the results. Kava is a U.S.-based fash casual restaurant train focused on Mediterranean-inspired cuisines, bowls, peter wraps, salads, and related grocery store products. It operates its own restaurants over the Kava brand, and it also sells Mediterranean dips, spreads, and dressing into grocery channels.

Now, as part of this prompt, Paul, I can see that there's a link to an SEC filing right next to it. So if I can be like, well, did it just make that up? If I click over to that filing, it actually pulls up the most recent annual report, and this is where it got the information from. And if I want to click down to the business, here's a link to what the business is looking at. So this is where it came from. And I can verify that, yes, that is indeed accurate information. So that's, again, how I have confidence in this.

Right next to that information, it says, here's the SEC filing. I got this info from. And if people want to visually follow along, we're showing us. all of this on our YouTube channel. So YouTube.com slash afford anything for anybody who wants to visually follow along with this. All right. So question number two I like to ask is, how does this company make money? We know that it does something with restaurants.

How does it actually make money? Those two things might be completely different from each other. So chat chip between says revenue comes primarily through its restaurant operations. The grocery retail product line is mentioned, but not separately broken out. And it's public summary, I could locate. And according to last year, restaurant revenue, It says, I cannot give you an exact figure because it isn't broken out in the summary but I found, but the company, it noted it opened up 58 new restaurants, all right?

Digital revenue was 38% of total revenue and the grocery retail business was referenced in an article but not in the 10K summary. So this is actually it's saying I couldn't find this information directly in the SEC filing. So at least we know it's not making up the results. But we do have the end of report here that we can pull up. Oh, it gave me a link directly to Kava Group's first quarter results as of 2025. So if we read through here, we can see that it reported $328 million in revenue in the first quarter, and we can at least get some information on there.

So kudos to chat GPT for not making stuff up. Right. That was not as helpful as I hope it was going to be with listing out what the revenue and sales are, but at least it gave us the sources that we could look at up ourselves. Okay. Question number three I want to know is, who are the customers? And it says, Kava's customers are primarily individual customers purchasing meals at its fast, casual restaurants, walk-in, digital orders, and delivery. And it also has grocery customers for spreads and dips.

That's pretty straightforward. That's pretty straightforward. Like any other fast casual chain, like Moe Southwest Grill, like Chipotle, like any place you'd go get lunch, sweet greens. Yep, for sure. The next question, where does it operate? Kavis operations are U.S.-centric. In Q1 of 2025, they operated in 2025. they operated in 26 states plus DC, and geographic revenue breakdowns are not clearly provided

in the summary. But at least we know it's basically a U.S.-based company, and it's only in half the country as of right now. All right, question number five. This is when I get into some qualitative questions. So now that we know what the company is and what it does, I like to know some detailed questions about the company's business model. So one of the questions that I love to ask is, how often do customers buy? As a general statement, I like to invest in businesses where customers frequently make purchases from the company. So they have a subscription-based revenue or it's a consumable product. And I don't like to invest in companies where you buy one time from the company and then disappear for periods of years. So a chat deputy says, many of Kavis restaurant

transactions are repeat visits by consumers. The company reported same restaurant sales. It was up 10.8% in the most recent quarter, including guest traffic plus 7.5%. It's also expanding via new store openings, which includes one-time customers in that transaction. And in the retail grocery product line, the purchase frequency will depend on the grocery shopping habits. But yeah, so I would say that that's accurate. If you're like most people, you, if you like a restaurant, you tend to not only buy from that company one time, but you do so every couple of weeks or so. Right. Next question I like to ask, can the company raise prices? If you've studied Warren Buffett,

you know that his number one thing that he looks for in a business is pricing power. The ability to pass prices onto consumers. So if your prices increase, you can pass those along. That's called pricing power. Not every business can do this successfully. So I like to know, does ChatGPT think that this company can raise prices? And it says, yes, there is evidence for a Q1 of 2025, same restaurant sales growth was 7.5% increase in traffic and 3.3% from menu price increases. So this is ChatDBD saying in the SEC filings, the company reported 3.3% increase in prices. And traffic still went up. So that's a pretty strong sign that this company can increase prices if it needs to. Right. Can you give an example of companies that might struggle

with pricing power, companies that aren't able to pass their direct costs onto consumers, even when those costs increase? Sure. Anything that's a pure commodity. So any product that you would buy and you do not care about the company behind that product, you only want the lowest cost price for that. Toothpicks? Yeah, toothpicks. Exactly. Or paper plates. I mean, you think about the grocery store anytime you are not specifically brand loyal. So if you don't care what kind of cereal you eat, you just want, say, let's say you like Cheerios or whatever, but you're okay with the generic version of Cheerios. If they can't convince you to pay for the brand name Cheerios, but if you're

happy to buy the generic version of Cheerios, that would be a company that does not have pricing power. Another way of thinking about this is some companies don't control the price that they set at all because it's dictated by the market. For example, if you're an oil company and you produce oil, you don't set the price of the oil. The market sets the price of the oil. Same for gasoline, same for gold or silver. Any commodity producer, they do not have control over their pricing. That's set by the market. Right. Actually, when you first mentioned pricing power, the first thing that came in mind were rental properties. There's a range in which you can price your rental property. You know, you could sort of be at the, depending on your level of finishes, you can be at the

bottom to the top of a reasonable rent range. But you can't really go outside of the top of that range unless you have a very, very specialty property. So for the most part, housing is a little bit of a commodity. Sure. Yeah, it's definitely a commodity. But there are commodity components to but I would imagine, I'm not a real estate investor like you are, but I would imagine location matters tremendously, the finishes matters tremendously, the quality of the building, the exterior siding, the landscaping, all that kind of stuff. I would imagine the nicer that is, the higher quality tenant you attract, and therefore the more pricing you can extract for them. Right, exactly. And that's why I say there is a reasonable rent range for, let's say, a three-bedroom, two-bath house

in the one, two, three, four-five zip code, right? There's a reasonable range that you can be and depending on all of those factors. But oftentimes when you're looking for homes, if you're talking to a real estate agent who's not being a good guide and who's just trying to sell you something in order to close the deal and collect a commission, oftentimes you'll hear agents say things flippantly.

Like, oh, you know what I don't know what the water bill is, but if it's high, just charge them more. That type of statement assumes a great degree of pricing power. landlords simply are restricted in the pricing power that they have. Yeah, that's actually a great point. I know a lot of your audience is real estate investors. And if you're the type of person that's buying an individual property, you're not just looking at the Zill listing and purchasing buy, right?

There's a huge number of details that you're going through before you choose to pull the trigger. What's the quality of the place? What's the location? What have the historic rents been? What's the tax rate? How much leverage do I have to put on this for this to make sense? What kind of upgrades are? Those are all you knowing the details about that property.

before you choose to make an investment. To me, that's exactly how I think smart investors approach individual stock analysis. They don't just know the ticker and the price of one share and say buy or sell. They get into the details and they want to answer questions like this. The more you can know about the investment, the better the quality of the decision you make. Right. All right. So the last question I have here to answer is what happens to this company in a recession?

So again, if tough times come, which they are guaranteed to, I like to invest in businesses that I think can grow even during a recession, that's best case scenario, or at the very least, they won't be harmed that much during a recession. Those are the type of investments that I like to make. I do not like to invest in companies with highly cyclical revenue. So chat TBD says, well, as a fast casual restaurant, Kava is exposed to consumer discretionary spending. In Q2 of 2025, management noted that consumer traffic softened amid economic uncertainty. And although same restaurant sales in prior periods were strong, the Q2 results of the most recent result of 2.1% growth and the downward revision to full same store sales guidance from 4% to 6% from 6th case indicates sensitivity to weaker consumer demand. Therefore, in a recession, traffic may drop, which will hurt performance.

I think that that analysis is highly likely to be accurate. Right. And would that same analysis apply to any fast casual chain? Yes. I totally think so. But then I also think about my own personal behavior. I do like to apply that to it. I'm a regular consumer of Chipotle. I like Chipotle's kind of food. And when I think about the various dining options that are out there for family, I have family of five. Chipotle, by comparison to going to a sit-down restaurant is pretty affordable. So if tough times came, I might change my behavior to go to places like Chipotle or Kava more and go to sit-down dining restaurant. restaurants less. So you do have to think about those things, too. But there's no doubt that if there was true tough economic times, many people would skip restaurants altogether and just eat more at home, which is the cheapest thing you can do. Right, right. And what you're describing is substitution. In the case of a recession, there would be a certain class of consumers who will

substitute a sit-down experience with servers for fast casual. There will also be a different class of consumers who substitute fast casual for fast food or for more groceries at home. Yep, absolutely. And some restaurants are more insulated from this than others. For example, as we talked about previously, McDonald's sales tend to increase during periods of economic stress. As people say, I can't afford Chipotle or Kava, but I can't afford a value meal at McDonald's. So there are companies like that, that their sales do go up, even if they are restaurants and stuff like that. But again, if you're going to be an investor, I think it's really important that you think through the exercises, what happens to this business during a recession the

same way I would hope you would think through as a real estate investor. Well, what happens if unemployment increases in this area? Is my place good enough that I can still attract renters? Right. So that is the prompt, and that is one of the first prompts that I do when analyzing any business. And in just a couple of seconds, if I've never heard of a company before, I can get a pretty good gist about what the company does, where it gets revenue from, what happens in a recession, and I think it's a really good starting prompt for analyzing any company. Excellent. All right, so now that we know this about Kava, where do we go from here? Well, so we can decide this is the kind of business that interests me and I want to dig further

into it, or I'm not interested at all, and I would just toss it aside and just go on to the next idea. If I was interested in this business, I have a whole bunch of other prompts that I've built that helps analyze the competitive position of the company, the long-term growth, trajectory of the company, the management of the company, the risks of the company, the valuation of the company, all of which are critical to making an informed investing decision. Again, I have a series of prompts that I've built for myself beyond this, but I think that this is a great prompt to start with because it gives you an overview of the company. Get no frills delivered. Shop the same in-store prices online and enjoy unlimited delivery

with PC Express Pass. Get your first year for $2.50 a month. Learn more at pceexpress.ca.ca. Tell me about the prompts. Specifically, you mentioned, do you have a prompt for analyzing management? So much of management are people, it's characters,

it's the talent and skill of the individuals involved, and that is incredibly difficult to assess. as an employer, it's hard even when you're sitting face-to-face with somebody to assess their skill level. How do you do that from a distance? It can be tricky to do, and you might think, well, you really have to get into the soul of somebody to judge what kind of person that they are. But to me, it's a fairly straightforward process. When analyzing a management team, you might think that's really impossible to do or it's hard to do as an investor.

One of the things that I like to do when I'm analyzing a company from afar is just do a couple of quick checks. I think it was David Garder that came up with this framework, but he called the, It's the O-O-T-S. So O-A-T-S. So O stands for ownership. How much of the company's stock does the manager or the CEO of the company own? As a general statement, I want owner-operators. I want management teams that network is going to be impacted way more than my network is going to be impacted if the stock goes down. So you can set up a prompt that checks for their executive compensation. How much stock do they own? How many millions of dollars of stock do they personally have invested in the company. As a broad statement, I want that number to be very high because if

the stock price goes down, their net worth is going to be impacted way more than mine will be. A stands for allocation. CEOs of companies are making capital allocation decisions. They're choosing to invest in R&D. They're choosing to open up new locations. They're choosing to launch new products and services. And you want to check their historic track record for allocating capital and does that lead to increased revenue growth, increased profitability. Do they have a history of launching new products and new services that drive the company forward, that grow the company over time? The T stands for tenure. This is how long have they been doing the job for? If they were, ideally, the founder of the company, they've been with that company since day one. That, to me,

is best case scenario. And there are still plenty of public companies out there that the founder is still in charge. I love to see that. I don't like it when the CEO is a hired gun, they came from some other company, and they were brought in, and they're likely attracted to the high compensation or the prestige of the job. So the longer they've been at that company, in my view, the better. And the S stands for stewardship. So how well do they treat employees? How well do they treat suppliers? How well do they communicate and treat shareholders? You can actually measure those things by looking at the returns of the stock over time. You can go on places like Glassdoor, Indeed, LinkedIn, and see what kind of reviews

the employees give to the CEO. Another one that I like to do is just execution track record. I want to invest in companies that have as a history of making proclamation saying, we're going to grow 10% or whatever, and then actually growing the company 10% or more. So there are some things that you can look at from an outside observer that can give you a real good sense of who is the person in charge, and are they capable of taking the business forward? The last thing that you said, the proclamations retrospective, I am a huge proponent of that because we see so little of that. I did an episode earlier where I talked about how we see very little of that in the financial media, where people will often make predictions, but they never do the retrospective to evaluate how their predictions went.

And that's why they say, you know, you've called 20 out of the last two recessions. And so the proclamations retrospective, I think, is essential. How do you do that when it comes to a management team, but you want to curtail the sources that you're putting into AI because you don't want the AI to hallucinate? How do you make sure that the AI is mining valid data when it's doing a proclamation's retrospective? Yep, that's fairly straightforward. When it comes to judging public companies, they report numbers every quarter. And the two most important numbers that Wall Street looks at are revenue and earnings per share. Those are like key terms that most companies operate by.

and you simply look at how does the revenue in earnings per share compare to prior periods, and if that management team gave guidance, which some companies do, which is when they say, in the next year we're going to grow 15 percent or in the next year we're going to report $2 in earnings per share, well, analysts track what were the actual numbers that were reported compared to the estimates that analysts teams were putting out. As a broad general statement, management teams that have a track record of consistently exceeding Wall Street's estimates, are rewarded in the market, and management teams that have a history of underperforming Wall Street's estimate have very poor stock performance. So that's actually a fairly easy thing to do and look up

numerically to say, did they beat estimates or did they underperform estimates? Right. Okay, so you're using purely their formal guidance in their filings. Yep. If they do give guidance, you can use guidance or you can use analyst estimates. That information is very easy to look up nowadays. Okay. Now, outside of the management team, you talked also about a, assessing the valuation of the company. Can you describe some of the prompts that you've created in order to do that? Because when you're looking at valuation, you, as an individual capital allocator, you know, you're trying to decide if these $10,000 should go to company to Kava versus Starbucks versus some biotech firm, given the wildly different risk profiles, opportunities.

How, as a capital allocator, do you design prompts that can assess not just what the public valuations of the company are, but that can assess the best use of your dollars given your own set of risk tolerance goals, you know, individual considerations? So I'm going to take those as two separate questions. One question is, how do you tell if the company is a good value, what the valuation is? That to me is the first step. The second step you have to do is, given everything I know about the company, the risks, the business, the growth potential, and the valuation, what should I do with this information as a capital allocator?

So one prompt that I have analyzes the stage of the business's life that it's in. I'm a huge believer that you should not use the same metrics to analyze all companies. One analogy I get to look at is think about businesses have distinct phases in their life. Would you judge a three-year-old, a three-year-old human by its. S-A-T score, that would, of course, be ridiculous because the kid is too young for that kind of metric to be valuable. You have to think the same way when it comes to public companies. A company like Kava, that is rapidly growing and rapidly expanding throughout the U.S., I would not necessarily use the price-to-earnings ratio, which is a very common ratio that

investors use to judge valuation, to analyze a company like Kava, simply because Kava is in growth mode. It is rapidly opening up new stores. And because of that, its financial statements are not fully optimized for profits. So the price to earnings ratio would be a poor metric likely to look at to analyze a company like Kava. If you're talking about a biotech company, for example, many biotech companies lose money for years or even decades because they're investing everything into research and development with the hopes of getting that drug to market. So it's very difficult to value those companies, and I would certainly not use multiple metrics like price to sales ratio or price to earnings to try and value them simply because they're in a different

phase of their lifestyle than in another company. On the flip side, a mature company that is profit optimized like Apple or like meta or like Walmart, those companies you can look at their price to earnings ratio and make a valid decision because they are fully optimized for profits. So one of the things that I have the prompts do is they analyze which phase of the business growth cycle is the company is in, and then depending on which phase it's in, which valuation methods are most appropriate to determining whether that company is overvalued,

fairly valued, or undervalued. And then from there, let's say it comes back and it says, according to this valuation metric, the company is undervalued. That's obviously best case scenario if you're hoping to purchase it. Then you take everything to account

as a capital allocator and say, okay, this is a business that I like, this is growth potential that I like, this is a management team that I like, and it's trading at a low valuation. I'm willing to allocate some capital to it because I think that I'm going to get a higher return on the risk-reward spectrum from making this investment versus another one. Right.

Again, the same way that you would analyze any real estate portfolio, right, you would consider, well, what are prices in, say, Manhattan apartments versus, and what's the rent-to-buy-buy ratio in Manhattan versus, you know, the suburbs of Alabama? I would bet those markets are incredibly different from each other, and the numbers make sense in one, and they wouldn't in another market. So the same way that you allocate capital when you're buying properties, same exact mindset to buying stocks. As you've developed out the series of prompts that you have, and people can download these prompts, yes? The business analysis prompt that we discussed before, yes, that one you can download. Yep.

Okay. If people who are listening want to construct their own versions of these prompts, what advice would you give them? Take the free prompt we just mentioned and just study the structure of it and look at the execution triggers, look at the name I assign up front or the role that I'm assigning up front. look at the stepwise function, and if you want it, you can just copy and paste that and say, help me adapt this to analyze a company's competitive advantage, help me adapt this to analyze the company's valuation, help me adapt this to analyze a management team. Or if you're into prompt engineering and you want to develop them on, you certainly can use that. But I think the structure, the structure is a really important thing here for people to look at. The structure is important to look at, and it sounds to me like the curtailing of sources is critical.

With structure and curtailing of sources, we reduce. the risk of hallucinations, but we still don't fully account for optimism bias, and we know that that is baked into a lot of AI. And where that can be particularly difficult is if we ourselves are also, as individuals, prone to optimism bias, then you've got two entities with optimism bias talking to one another, which can then become this unspoken unknown unknown, right? How do you adjust for that? So I think as long as you give it the stepwise structure and you give it the reporting system that the output that you get is in a format that you want, it's not inherently going to be doing, this is a great idea or this is a terrible idea, because what you're asking

it to do is to go out, find information from valued sources, and report it back to you in a format that is useful. I don't think you should outsource your analysis to AI. I think AI is wonderful for gathering information, for presenting it to you in a format that you think is correct, and then it's up to you, the investor, to do that last bit of analysis, to take that and say, is this a good company or is it a bad company? Is this a good buy or is it a bad buy? Should I put this on my watch list or should I figure about that company? So that's how I combated it. If you want to go the next step, when we're signing a role, you could say take the exact opposite approach. So act as a short seller, right? Do that same thing and say, what would you say about Kava? And that way you're

telling the thing to think negatively about this company. Point out the reasons why you wouldn't invest in it or short selling for those that don't know is when you are betting, you make money when the stock falls. So by prompting it, by giving it the role of, I think, of a short seller, it's going to, by definition, go out and look for everything that it could possibly go wrong. And so fundamentally, you're assigning it the devil's advocate role. Yes. And that as a step in the process makes a lot of sense because you want to stress test

all of your assumptions. Functionally, by assigning it the role of a short seller or a devil's advocate, you are baking into your process. As part of that checklist, let's stress test this. by hearing every counter argument. And that's exactly what good investors do. They think of what is the bull case or what is the upside scenario if everything goes right, what is the bear case or what could happen if things go wrong.

And if you're an investor, you know it's always a good idea to spread your bets and to diversify. I would never put all of my capital into one stock. No matter how positive, one of the things that I insist on in the prompts is whenever you present with a number, you also have to simultaneously give me the link to the information that you got that number from. So when I'm reading through the prompt and when I'm actually referencing a number that it's pulling up, I can click over to that original source, and if I want to double check where the number came from right in the prompt itself. So if I'm like, okay, it's saying this company did 50 million in revenue, if I click over the SEC filing and I scroll down, I can verify

that the SEC filing gave me that number. Right for one personality is not the right thing for another personality. There are 20-year-olds out there that are scared to death of volatility and the idea of their portfolio declining in value would just keep them up at night, right? Like investing through 2008, 2009, or 2020 was not fun. Like, it's not a fun period to watch a huge part of your net worth decline in real time in front of you. And just some people aren't emotionally capable of seeing that and dealing with that. If you're the type of person that if your net worth fell 30% in a matter of weeks because of a recession, perhaps you should really cut back in your stock allocation and put more.

more into less volatile assets such as cash or bonds. And that might not be the optimal thing from a long-term growth of your portfolio, but it might be the right choice given your personality. If I could use my mom for a second, my mom is a type of person that scared the death of volatility. She just is scared the death of it. So she invested in her 401K for a couple of decades and always put it into CDs. Cringing is the right thing to do, right?

But for her, the thing that gave her pleasure from that was in 2008, value of her portfolio went up. And she slept soundly at night knowing that her portfolio was safe. Now, I tried to point out to her, well, do you know what your value would be if you invested it in the stock market versus keeping it safe? And she said, I don't even want to think about it. That's not a fit for my personality. And to me, while that might sound like an abhorrent asset allocation strategy for me or you, that was the right asset allocation strategy for her. So, yeah, I haven't explored that deepy with AI, but AI can be good about teasing that kind of thing out about yourself. Let's say that you have the personality type, like your mom, where your

inclination is to put everything into CDs. You want to play it safe. But you want to feel differently. You want to prompt yourself to take on more risk. Can you design an AI prompt that will help you become more of the investor that you want to be? And I use in this example, you're too conservative and you want to take on more risk. It could also work the other way around. you're a little too reckless and you want to be corralled in. Yeah, that's a great idea and it sounds like you're giving me a good homework assignment here, which is almost to come up with a prompt that takes you through an investor assessment of form where it asks you a series of questions and you fill those out and that can help you to tell you

what type of investor you are and perhaps some asset allocation strategies to think of. There's lots of ways to invest and what's mathematically correct by the academic definition may not be right for you given your personality. There are certainly young people out there that have over-allocation to bonds because they don't want to deal with volatility, and there are certainly 80- and 90-year-olds that are investing in a high-risk long-term 100% stock simply because that's a bit fit for their personality. So that might be a great prompt to build something that helps you to discover what type of investor you are. Okay, if you did want to build a prompt, people listening at home who want to build their own investor assessment prompt, do you have any guidelines around prompt construction best tips? Yep. So I would say give it a role.

if there's an investor that you admire or is there a capital allocator that you admire, you can even just say act as a financial advisor, right? What kind of questions would you want to know from me? And just say, act as a financial advisor. And what kind of questions would you want from a new client for them to figure out their asset allocation? AI is wonderful as a tool for coming up with prompts to prompt AI, right? You just have to ask the right questions. You have to be willing to iterate again and again and again. And sometimes building the prompts, like the prompts that I've built me hours upon hours upon hours of refinement to put in them to get them the way that you want. But I used AI the entire way to help me build those prompts.

So yeah, give it a roll and then ask it to prompt you the user with what type of questions that you think it would ask. That's a great way to start. Thank you for these tips and thank you for spending this time with us. Where can people find you if they want to learn more? If you're on a social platform, just type my name in, Brian Faraldian, I'm likely to be there. And if you want to see these prompts in action, I have several videos on my YouTube channel, which is called the long-term mindset where I go through them in detail.

Thank you, Brian. What are three key takeaways that we got from this conversation? Key takeaway number one. AI can be your junior analyst for stock research, but ultimately, the decision-making does have to be up to you. Brian talks about how to use AI effectively for analyzing investments by treating it like a junior intern who needs extremely. extremely specific instructions. And the key to good use of AI is constraining AI, limiting it, for example, to only using very trusted sources like SEC filings, and then also giving it detailed step-by-step instructions.

Because the thing is you want to make sure that you're preventing hallucinations, and if you don't give it those kinds of constraints, it might hallucinate. I think a good mental model to get in your mind is you have to think of AI like a junior analyst or a junior intern that is eager to do whatever you tell it to, the instant that you tell it to. If you were hiring an intern to come in and you said something like go research this guest, and that was the only information to give them, they would go off and comply and come back with information. And it might be in a format that is completely incoherent to you. that is the first key takeaway number two force AI to show its work every single number that you see the AI needs to show you exactly how it got to that make it provide a clickable link to the exact SEC filing for every single number that it gives you one of the things that I insist on the

prompts is whenever you present with a number you also have to simultaneously give me the link to the information that you got that number from. So when I'm reading through the prompt and when I'm actually referencing a number that's pulling up, I can click over to that original source and if I want to double check where the number came from right in the prompt itself.

So if I'm like, okay, it's saying this company did $50 million in revenue, if I click over to the SEC filing and I scroll down, I can verify that the SEC filing gave me that number. That is the second key takeaway. Finally, key takeaway number three. The quote-unquote best investment might not be the optimal one.

Sometimes the approach that is mathematically rational might not be right for your personality. So Brian shares a story about how his mom kept all of her money in CDs and missed out on a bunch of stock market gains. But she also slept soundly during the 2008 crisis. And that fits her personality. She is very afraid of volatility. She doesn't want to put her money at risk. And it's true, there's a famous quote that more money has been lost in anticipation of recessions

than in recessions itself. And mathematically, we might know that. We might be able to pull data that shows that, but that doesn't change how people feel. Feelings turn into behaviors that become suboptimal. And so you can't rationalize your way into taking on risks that don't suit you. My mom is a type of person that scared the death of volatility. She just scared the death of it. So she invested in her 401K for a couple of decades and always put it into

CDs. Cringing is the right thing to do, right? But for her, the thing that gave her pleasure from that was in 2008, the value of her portfolio went up. And she slept soundly at night knowing that her portfolio was safe. Now, I tried to point out to her, well, do you know what your value would be if you invested it in the stock market versus keeping it safe? and she said, I don't even want to think about it. That's not a fit for my personality. Weigh your own personality, your personality, your risk tolerance, your ability to sleep soundly at night, weigh all of that when you're making your investment choices because that stuff

matters. Those are three key takeaways from this conversation with Brian Faroldy. Thank you so much for being part of the Afford Anything community. If you enjoyed today's episode, please do three things. First, share this with friends, family, neighbors, colleagues. share it around the Thanksgiving table, share it with the people in your life because that is the most important way

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Thank you again for being an afforder. I'm Paula Pant. This is afford anything podcast and i'll meet you in the next episode