You're listening to TIP.
This past year has been a predictably unusual one for me in the markets.
Between the tariff tantrum and the AI scare, many of the companies that I own have really been put through the wringer.
But after spending hours each day researching investing, I've learned a lot and taken the time to reflect on which of those lessons have really helped me evolve the most in 2025.
This episode, like all my previous episodes, won't bother at all guessing with what will happen in 2026.
It's about what I've learned that has directly impacted how I think and how I strategize.
Now, when reflecting on some of the biggest mistakes I've ever made in my investing career, I realized that two of them didn't really stem from poor analysis.
They came from fairly simple psychological errors.
It's easy to learn about investing and assume that we'll all act rationally, but the reality is far from it.
This episode was an excellent exercise for forcing me to confront where my thinking was too rigid, too emotional or even too optimistic.
One of my biggest thinking shifts was realizing that being confident and being flexible can actually coexist.
A more uncomfortable realization was the biggest threat to my portfolio isn't interest rates, geopolitical unrest or AI, but me and my imperfect thinking.
I also share my thoughts on fragility of compounding and the steps that I've taken to protect myself so the compounding engine can just continue working.
This episode is packed with how I've turned this thinking into usable tools to help me improve as an investor.
And the reason I think these tools work is that nearly all of them have been cloned from the legendary investors.
I get the privilege of studying daily.
I'll walk you through updates to my strategy around things like position sizing, how I wait for investments to play out and how I say no.
So if you've ever felt the urge to act when nothing needed to be done, or felt extreme confidence right before proven wrong, this episode is just for you, because I feel your pain.
This episode will help you learn from my mistakes and give you a few ways to think differently about your own investing.
Let's jump right in to what I learned in 2025.
We've studied the financial markets and read the books that influence self-made billionaires the most.
We keep you informed and prepared for the unexpected.
Now for your host, Kyle Grieve.
Welcome to the Investors Podcast.
I'm your host, Kyle Grieve, and today I'm happy to discuss my nine biggest learnings from my last year, specifically from this podcast.
So the podcast game is just super interesting for me because it's a job where I get to share these incredible lessons with you every episode, but then I can also pick and choose which of these strategies and mental models that I personally learned from that the world's greatest investors or minds are using on a regular basis.
So today I'm going to go over some of the strategic shifts that I've learned from spending thousands of hours researching the world's greatest investors, companies and fascinating books that I've shared with you in 2025.
So let's jump right in and discuss the concept of flexible conviction.
So, on the face of it, flexible and conviction are two words that seem very, very strange to put next to each other, don't you think?
Flexible means being able to bend, adapt, or change easily without breaking.
And conviction refers to a firmly held belief or strong confidence in an idea, principle or decision.
But here's the thing.
Conviction works very well under specific circumstances, such as things like position sizing.
But it can also lead to many errors in my thinking.
If I have too much conviction in an idea, it makes me do things such as size positions too large.
Maintain conviction in an idea where maybe the thesis is deteriorating or exposing myself to increased risk.
And these three things add up to me losing money or having reduced returns, which is an area of investing that I'd obviously love to protect myself as much as possible.
But don't get me wrong, conviction 100% matters, and it matters a lot.
But what I really learned this year, especially from someone like Anthony Bolton, was that conviction must be re-earned at very regular intervals.
So what I this framework.
I'd get an idea in my head, I'd gain conviction, and then I didn't think that I allowed myself to be very flexible until unfortunately, it was just too late.
While I thought that Alibaba was a great business, it was taking an approach to growth that just wasn't optimal for creating shareholder value, in my view.
I could have come to that conclusion a lot earlier had I allowed myself to adjust my conviction levels rather than stubbornly holding onto them, as I did with Alibaba.
Now Anthony Bolton warns us that beliefs can really calcify when new uncertainties appear.
And this directly explains what I think happened to me with my Alibaba investment.
The calcification of beliefs and conviction is a very perilous thing.
And if you allow thoughts in your heads to calcify just too much, you rapidly increase the risk of making bad decisions because you become blinded by new facts that counter your existing beliefs.
But this year, I came across a quote that profoundly changed just how I view conviction.
And that was simply, strong convictions, weakly held.
This is use what I call conviction ranking.
This is a journal entry that I make pretty much every month, in which I determine whether any new information that I've learned is either strengthening or weakening my conviction.
You can really do this however you want.
You can give it a letter grade.
You can have a number, a percent.
I personally use percentages, but it really makes no difference.
The reason this is so effective is that it shows whether you are gaining or losing conviction in your ideas.
In my last entry from November 24th of 2025, I noticed a few highlights.
I had one business where my conviction levels dropped a little more compared to some of my others, and then I had a few positions that gained a few more than others.
Now I'm not going to name either of these positions, but I can tell you that for one of the businesses where my conviction actually decreased a little bit, there were a couple of reasons here that I can share.
So the first is that the last two quarters have been pretty ho-hum.
Had I known the business would probably slow down as much as it has, I would have delayed buying it, since this is kind of one of my inflection point businesses.
But I still actually have enough conviction in the position that a lot of the new spending that's causing this contraction in margins et cetera, is going into money that can probably improve the business over the short to medium term.
So that's money that's going into things like SGA and research and development, which I think will probably end up helping the company.
So my plan here is just to kind of wait and see what happens over the next year or so.
There are some specific contracts to do with this business that are completely outside of their control.
And once they get awarded to their customers, then their customers will begin shopping with businesses that the company I'm discussing sells.
So there are specific contracts that are completely outside of their control that should actually end up helping this company once they're announced.
Now, as for the position where my conviction went up, My conviction simply increased because the business has been going through some of these temporary headwinds.
And this quarter really showed to me that a lot of these tailwinds that the market was very, very fearful of.
And I wasn't very, very fearful.
I held my position and even added to it.
But it was a position where I felt like I wanted to see how they were going to deal with them.
And again, that's kind of a short-term problem, but I felt that they deal with them very, very well.
And now that those problems are mainly behind them, there's probably going to be a reacceleration to its growth and intrinsic value.
And so the next few quarters should further reinforce my conviction that things are moving in the direction that I'm hoping for, which is to continue moving up.
So one key to this test is to ensure that your conviction in an idea is coming from the fundamentals of a business and not from your emotional state about a company's share price movement.
So when I look at where I increase conviction, I see stocks that have actually fallen in price.
For instance, Lumine and Topicus have both decreased substantially in price, but my conviction in them just really hasn't faltered at all.
This helps determine my actions, as I then know that they're very good candidates for me to probably add capital to and increase my position size.
So this conviction ranking really helps me be more decisive, but maybe less delusional.
There's probably a really good chance that I shouldn't be adding to that position, even if there's a corresponding drop in the share price.
Just because a stock's price drops doesn't mean that that's a valid opportunity to invest in it.
You need to look at things like the fundamentals of the business and decide if the market is correct or incorrect on its current perception.
And my conviction ranking helps me make that independent decision that are not tied to the market.
Now, it's essential to never get married to an idea or fall in love with one.
As I've said, conviction is really just a test.
And the businesses that stay in my portfolio will tend to be the ones where my conviction levels are improving over time.
These improvements generally come from very strong fundamentals, such as higher growth metrics, higher margins, greater capital efficiency or maybe even more robust validation of capital allocation decisions.
Now, I know that I've constantly tried to test myself to see where I could be wrong.
And while this can obviously hurt the ego, a degree of humility in investing is much, much more valuable than having a high IQ.
Another way a business can improve its fundamentals is through a less discussed strategy, which is strengthening customer loyalty.
This is another area that I've spent more and more time thinking about after researching my episode on the book Hidden Monopolies.
Instead of focusing purely on traditional competitive advantages that businesses have, such as being a.
But, as I outlined in that episode, there are many, many ways that a business can improve its customer loyalty, and it doesn't have to be explicitly tied to monetary reasons.
My favorite case study from the book showed how a business with very obvious scale economies could still actually end up losing to a competitor who was able to improve customer loyalty.
The story highlighted Nokia, which was once the absolute king of mobile devices.
And it had exceptional scale benefits as well, which seemed to be undisruptable by newcomers such as Apple.
But Apple built more and more customer loyalty over time, which eventually led to Nokia's loss of its mobile device dominance.
Now, the beautiful part about customer loyalty is that it combines fundamentals such as intangibles with if consumers spend a small amount of money on a product, they might not see any reason to switch, as they satisfy the satisficing heuristic.
This is an advantage that you generally won't see on a business's public presentations.
But when you dig a little deeper and look at the thought processes that a customer makes in relation to a product, you will see these types of relationships.
And businesses that have these relationships, such as a Netflix, saw substantial increases in their intrinsic value, specifically because customers didn't see a need to jump to a competitor.
Now, as a quick side note here, I actually don't believe Netflix's score in this area is going to increase over time.
It's probably going to decrease over time.
But five to 10 years ago, it was a very, very significant advantage for them.
Now, when you have customer loyalty, you don't need to spend as much time on customer acquisition.
You can simply enrich the customer experience and keep customers happy, who will continue doing business with you.
That saves a ton of money on things such as customer acquisition costs, which can then be diverted elsewhere.
The other bonus of having high scores and customer loyalty is that the business becomes much, much more predictable.
If a business has to fight tooth and nail to get every single new customer, it's going to have to spend a lot of money and you have limited certainty whether those customers will actually stick and stay inside of that business.
If you know a business already has a very sticky customer base, then chances are it'll have the same customers five to 10 years from now with greater certainty.
This is why software businesses with switching modes trade at such high valuations.
Investors tend to have high confidence that these businesses will increase their annual recurring revenue, and those are highly valuable.
So what I like to look for are the hidden monopolies.
This is where businesses have maybe improved their customer relationships, but the market doesn't quite understand how those relationships have improved.
In those cases you can truly get some incredible returns because once the market finds out, there's a great chance that you'll get a re-rating in that business's multiple.
Now, similar to conviction testing, I like to audit my businesses to observe their customer loyalty metrics.
I try to do this now on probably a yearly basis so I can see if there's any large scale changes that I need to focus on.
Additionally, I can look at what other companies are doing and see whether my business is maybe cloning some of their best practices to help improve customer loyalty or if they're just getting miles and miles further ahead in their own abilities to improve customer loyalty.
So one business that I can talk freely about here is Aritzia.
I've done my customer loyalty analysis on the business.
And I concluded that they just don't have a very high customer loyalty grade.
And that's actually okay.
I think most retail businesses will not get the highest grade using this exact framework.
But it was still valuable to really go through each one of these 20 line items to see where Aritzia scored somewhat strongly.
Now, I didn't score it very highly in any one area.
But it had some medium scores and things like satisficing personal relationship, costs and exclusivity.
Now I can see whether these metrics move up or down as the business continues to scale, which will help me determine whether they are improving customer loyalty.
Now, finding customer loyalty is great, especially when you decide to sleuth a business.
I covered sleuthing in a lot more detail and I've already mentioned that hidden monopolies often requires quite a bit of digging just to find the hidden monopoly.
And some of the aspects that I covered regarding sleuthing can become very, very helpful.
So the problem with some businesses that I know I own is that I'm not a personal consumer of that business.
So if I was to analyze a business such as Apple, it's pretty easy.
My house is littered with Apple products.
I'm writing this episode on a MacBook Pro.
I'm listening to podcasts on my iPhone.
I got an Apple TV right next to me when I want to watch a show.
But there are many businesses that are in my portfolio that I have zero ability to put myself in the customer's shoes, simply because they just serve markets or have products that I'm not going to shop for and nor will is so valuable, as well as why getting kind of boots on the ground is so important.
If you have people like family, friends or acquaintances who work in industries that use products of the businesses that you're looking at, that can be a highly, highly important person to talk to.
And in that case you definitely should try and find out more about the relationship between that customer and the company, because you can unveil some incredible insights.
For instance, I don't have a ton of experience with vertical market software businesses.
So I have to go and depend on information from others who do use these types of products.
So, for instance, my stepdad works at a post office in Canada and they recently switched to a new software for processing payment.
And he said it was an absolute pain in the ass to learn.
He had to spend weeks learning the latest software and teaching it to others at his location.
So he didn't decide whether Canada Post would switch.
I think if it had been up to him, he would probably have decided that he did not want to switch because he knew that there would be a lot of time and energy that would be spent in learning this new piece of software.
So this little piece of information really helps me understand the switching costs that are involved with a lot of these vertical market software businesses I own, such as Topicus and Lumine.
Now, one of the favorite episodes I did in 2025 was on the psychology of human misjudgment that was outlined by Charlie Munger. examine the psychological biases that I personally have succumbed to in the past.
And if you asked me when I started investing, what's the greatest risk to investing?
I probably would have said things such as leverage, maybe lack of a moat or poor capital allocation.
It would have been something that seemed clean and rational.
But the honest answer to that, which I didn't really start to understand until I gained more and more experience, is probably a lot messier and irrational.
And that's not the biggest risk in investing that I've made from two completely different worlds that I think have helped me understand this at a much deeper level.
So for the first trade, we need to go back to 2017.
So Bitcoin had shot up from 3,000 and 20,000 in just a few months.
And every altcoin with a website seemed to double nearly in a couple of hours.
It was an environment that was really easy to fool yourself into thinking that you were smart.
I quadrupled my capital in months and I felt like I had found something that was truly special and life-changing.
Robert Leonard So I built what many temporary successful people do.
I built my edge.
Looking back, there wasn't much science about it, but it felt scientific to me at the time.
I looked at things like Ichimoku clouds and other indicators that I didn't really understand all that well.
I took screenshots that I focused on trends and specifically on the short term.
But when the market rapidly turned against me, I didn't really adjust or take any time to step back and look a little more closely at what I was doing.
Instead I just doubled down and told myself things would probably go up, but I need to just wait it out.
Much like Isaac Newton, who added to his South Sea Company bet once it popped, I made the mistake of thinking my crypto wouldn't go down for too much longer.
So this mistake showed me that my system was more or less built around a narrative that justified a lot of the emotional biases that I was exhibiting.
And as Spinoza said, emotion makes us pursue the worse while seeing the better.
A few months later, 97% of my crypto net worth completely evaporated.
And that didn't happen because Bitcoin was a scam, but because I fell victim to things such as a loving tendency, reward super response tendency and doubt avoidance.
It was unfortunately the perfect storm of misjudgments, a negative Lollapalooza effect.
The second trade took place recently in the last quarter of 2024.
I'd evolved a lot since my days as a crypto speculator.
I thought I had a much better framework and structures in place to help protect my downside, but the danger of emotional reasoning is always around the corner.
When I first bought a business called Simply Solventless, a Canadian cannabis company, I did quite a bit of work.
I did scuttlebutt, management interviews, due diligence.
I spoke with other investors and people involved in the cannabis industry.
And I liked the industry consolidation story that Simply Solventless was a part of.
And I liked the price.
I liked the upside.
And maybe I liked it a little too much, which was probably the beginning of my mistake.
When you like something too much, it's like putting on beer goggles.
You're looking at an unclear picture, but it appears to you to be in 4K.
When a significant fell through, the stock dropped very sharply.
But looking back, my first instinct wasn't caution, which it maybe should have been.
It was excitement and a view towards opportunity.
I wrote in my journal after buying more shares that, quote, this might be a mistake.
I like the price drop, but there's a lot of uncertainty in the idea because of the unknowns with the material adverse conditions.
Now, after that event came things like accounting changes.
Then there were revenue recognition adjustments.
And these added more and more to the uncertainty with the business.
But then a switch kind of changed in my mind.
What if I've been wrong on this business the entire time and I was simply just allowing my emotions to cloud my judgment?
I promptly sold the whole position at unfortunately, a considerable loss, the largest percentage loss that I've ever had.
Let's take a quick break and hear from today's sponsors.
When you're running a small business, hiring the right person can make all the difference.
The right hire can elevate your team, boost your productivity and take your business to the next level.
But finding that person can feel like a full-time job in itself.
That's where LinkedIn Jobs comes in.
Their new AI assistant takes the guesswork out of hiring by matching you with top candidates who actually fit what you're looking for.
Instead of sifting, based on your criteria and highlights the best matches, saving you hours and helping you move fast when the right person comes along.
The best part is that those great candidates are already on LinkedIn.
In fact, employees hired through LinkedIn are 30 more likely to stick around for at least a year compared to those hired through the leading competitors.
Post your job for free at linkedincom studybill.
Then promote it to use LinkedIn Jobs'.
New AI assistant making it easier and faster to find top candidates.
That's linkedincom studybill to post your.
Imagine scaling your business with technology that understands your customers literally.
That's the story behind Alexa and AWS AI.
Every day, Alexa processes over 1 billion interactions across 17 languages, all while reducing customer friction by 40.
It's not just about making life easier.
It's also about transforming customer engagement and generating new revenue streams.
Behind the scenes, AWS AI powers more than 70 specialized models working together to create natural conversations, proving how enterprises can deploy AI at scale with confidence and security.
Alexa's AI capabilities were battle-tested across Amazon's massive operations, delivering real, measurable impact at scale.
These same innovations now give other businesses a proven framework to boost efficiency, unlock new revenue streams and gain a lasting market edge.
Discover the Alexa story at AWS.com slash AI slash R dash story.
That's aws.com slash ai slash r dash story.
The more your Bitcoin holdings grow, the more complex your challenges become.
What started as a simple self-custody now involves family legacy planning, sophisticated security decisions and navigating situations where a single mistake could cost generations of wealth.
Standard services weren't built for these high stakes realities.
That's why long-term investors choose Unchained Signature a premium private client service for serious Bitcoin holders who want expert guidance, resilient custody and an enduring partnership.
With Signature, you're paired with your own dedicated account manager, someone who understands your goals and helps you every step of the way.
You get white glove, onboarding same day, emergency support, personalized education, reduced trading fees and priority access to exclusive events and features.
Unchained's collaborative custody model is designed to provide the same security posture as the world's biggest Bitcoin custodians, but for those who prefer to hold their own keys.
Learn more about Unchained signature at unchained.com slash Preston.
Use code Preston10 at checkout to get 10% off your first year.
Bitcoin isn't just for life, it's for generations.
All right, back to the show.
After reflecting on these two investments, I realized something quite profound.
Unmanaged emotions never disappear, they just evolve.
Emotions get smarter, more articulate, and even better at concealing themselves.
After reading more and more on Spinoza, I came to a clear realization regarding emotions.
Humans, myself included, are completely bound by emotions.
And we do not clearly understand our own emotions enough to prevent them from distorting decision making.
Or put simply, we're just wired wrong.
So the lesson here is on risk.
In academia, risk is measured by such factors as volatility, price, and beta.
But in reality, risk is how our emotions play tricks on us, distorting our perception.
The second lesson is on the power of loving or liking bias.
This bias binds you to a more painful reality.
It masks flaws that would have given you pause.
And the more attached you become to a hypothesis, the less likely that new valid data will change your mind.
And third, the market will punish psychological weakness at alarmingly fast rates.
Bad analysis might mean your investment goes nowhere for several years if you buy it with a large enough margin of safety.
But bad psychology can cost you instantly, just like it did on my crypto adventure.
Now, the biggest tool for combating your emotions is to acknowledge that they're there and to see which decisions that you're making now come from rational or emotional thinking.
Only then can you triumph over the adverse effects of emotions.
Now, while emotions will have the biggest impact on our investing, we still need to make sure that we are putting the right businesses inside of our portfolio to at least set us up with the best chance to succeed.
And to do that we need to embrace another concept that I learned from Anthony Bolton.
Now I'd love to share a story here about when I was overwhelmed by another investor's expertise.
So a few years ago, I invested in Micron, a business that manufactures silicon chips.
I remember reading analysis deep into the night from this one guy on Seeking Alpha and I was constantly just in awe at this guy's ability to understand Micron and its industry.
He knew how Micron was doing versus competitors, how far Micron was ahead in terms of microchip size compared to Chinese competitors, the direction of pricing, which customers had, excess inventory and other just mind-boggling factoids that I hadn't even thought were material to my thesis.
I felt a little out of my league.
I thought to myself that I needed to get to this level if I ever wanted to feel like I had an edge.
But the more I researched, the more I realized that that goal was entirely out of reach.
Not only did I not have the time or really inclination to learn as much as this guy, but I also had 10 other positions to understand deeply as well, plus a full-time job and a family.
Now, as I began thinking more and more about it, I realized that it was impossible to make that a goal to strive for, because unless I could spend 40 plus hours per week researching semiconductors, chances are that I would never become as knowledgeable as this guy.
Now, let's imagine for a second, two different investors.
We'll call them Deep Diver Dave and Sufficient Generalist Steve.
So Deep Diver Dave absolutely loves detail.
He invests in maybe just one thing a year and he knows everything there is to know about the industry.
Someone like Shelby Davis comes to mind here, an investor who only really invested in insurance and knew all the key players and developments inside of that one industry.
Now deep diver Dave reads everything about the industry every news article, every 10K analyst reports, industry reports and journals and feels the need to know more than literally anybody on the planet about the industry that he's digging into.
But something dangerous has happened in Deep Diver Dave taking this exact approach.
Where he once had several winners, he's now experiencing many large losers that have erased a ton of the returns that he's had over the past five years.
And this is because he's become a little too overconfident in his information.
And because he feels he spent so much time and effort understanding this one industry, he's paralyzed to move somewhere else, keeping his capital in some pretty mediocre investments.
Now we look at sufficient generalist Steve.
He's obviously a generalist.
And while he doesn't know nearly as much about one industry as deep diver Dave, he's perfectly fine with that, because he focuses on information that he needs to know to make investments that will bear adequate returns.
So you could say he focuses specifically.
He's very, very picky about where he spends his time, as he realizes that there's an opportunity cost to everything that he does.
This means that Steve has to live with incomplete information at times, but he's okay with that as long as the incomplete information is unlikely to harm his investments.
He still does a ton of the research, but he takes a more direct approach, focusing only on the information that he needs to make an investment or take a pass.
So sometimes he'll even speak with experts on an industry or a business just to get key insights that he wants from that person who probably has a lot more knowledge than he'll ever have.
Anthony Bolton himself is an excellent example of this investor archetype.
Now, Bolton's insight crystallizes the difference between Dave and Steve.
The question that Bolton would pose to us investors is what kind of edge do we get from spending say, 40 hours on a company versus only 20?
And if we know more than 99 of the average investor after spending 20 hours, what does 40 hours get us?
99.5%?
Does that actually make a difference in our investing process?
If I knew Micron was good, cheap and had good growth potential, did it really matter what small adjustments competitors were making?
That probably wouldn't really affect Micron's business.
The more I thought about it, the more I came to the conclusion that depth is not the same as clarity.
Depth is a great way to spend time and unfortunately even waste it.
When you are thinking about clarity and time in general, you must focus on where your time is best spent and not on wasting time trying to get a negligible edge versus other investors.
So now we get back to that Micron example.
Once I realized that all the time spent researching all this extra stuff was unnecessary.
It led to a potent insight.
I began to see that information isn't always better.
What matters is knowing what actually matters and acting on it at the right time.
So even today, I still wrestle with this problem.
It's so easy to spend another five to 10 hours on a business I might already own to just learn a little bit more about it or learn about a specific aspect of it.
But I have to ask myself, will this make a difference to me in the long term?
I generally have an excellent idea of what KPIs that I'm looking for in all of my businesses.
And as long as I'm staying on top of the developments inside of that company that directly affect those KPIs, I'm in pretty good shape.
But if I spend too much time needlessly deepening my knowledge, I'm simply taking time away from putting that into better things.
So what I learned from Bolton was that the edge regarding information isn't from knowing everything.
It's from understanding and focusing only on what matters the most.
And to gently remind yourself to stop once you know enough.
So now when I'm looking at a business's quarterly, I'm not scrambling to spend five, 10 or 20 hours needlessly trying to understand some low impact nuance that may subtly affect the company.
I focus on my KPIs, their current state, what's moving them and what's likely to happen over the near, medium and long term.
It's my simple way of telling myself that I know enough already.
Now I remember waking up on April 2nd of 2025, opening up my Yahoo Finance app, rubbing my eyes and seeing just a sea of red.
And this wasn't just a small drop.
I remember some sizable minus 5 or greater drops that day, not too long after the market had opened.
But I was pretty calm.
I've been through situations like this before.
After doing some reading, I saw what all the fuss was about, the US tariff news.
I had text messages and direct messages from other investor friends who were checking in and talking about all the carnage that was going on in the market that day.
Many investors were panic selling, predicting that other investors would sell.
They reasoned that they would just do it first so they would lose less.
For me, it was just another wild day in the market.
Now reflecting on this day got me thinking what if the hardest part of investing isn't in the analysis but in the waiting part?
So let me explain a little more.
I recently did an episode about something called intentional inactivity.
Now, in that episode, I discussed a really, really good story.
So it was about this gentleman named Fabius, who was a Roman emperor and general.
And so the story goes, he basically did nothing as his enemy attacked him.
Basically, he knew that his enemy was trying to lure him out to have a conventional battle.
Now, instead of fighting a fight that he knew that he would probably lose, he simply did not move his troops out onto the battlefield.
Now to the lay Roman, this might have looked like he was frozen and afraid.
But to Fabius, he was just coiling.
You see, intentional inactivity can easily look like incompetence until it starts to work.
And Fabius was simply biding time allowing his army's numbers to swell as more and more soldiers were called to the front.
Now, once he knew he had the edge, he met his enemy on the open battlefield and he defeated him.
Now, back to April 2nd.
While the average investor may have looked at my inactivity as incompetence, I too was practicing intentional inactivity.
I sold zero stocks in the month of April because many of my businesses were just simply well-positioned.
I thought to deal with tariffs.
And I felt that many countries would begin bargaining to reduce tariffs.
Sure, there might be a hit to the margins of some of my businesses, but it was nothing that would really break my thesis.
And besides, why sell companies that I didn't think lost that much intrinsic value when their share prices were being beaten to a pulp?
But I also realized, like all humans, that I'm wired to want to do something under stress.
I just noticed that I don't really get stressed about my investing during the exact same times as probably the normal investor.
I get more stressed out when a business that I own shows weakness in its fundamentals.
So my wiring for doing something in these situations is an area that I know I need to work on.
Like Fabius, I needed to focus on controlled disengagement and patience during these times to avoid coming to the wrong conclusion.
So intentional inactivity isn't just about emotional discipline.
It's also about structural advantage.
When I did my episode about systems and mental models, I began to create some very interesting connections with Fabius.
When I thought more and more about feedback loops, I realized that compounding is like a contained machine.
When you open the door, you let heat escape and it takes a lot of time to heat back up.
Now, these minor interruptions have very high costs.
So any small adjustment that I could make to my portfolio, such as trimming or what other people do, like sectional rotations or panic selling, obviously create a drag on compounding.
So in this sense, inactivity isn't laziness or incompetence at all.
It's really a form of engineering.
So I realized that my portfolio was most likely to compound when I touched it the least.
So if you got a chance to look at Buffett's best investing decisions, it wasn't some sort of brilliant trade or financial engineering with the use of heavy amounts of leverage.
They were simply able to find great businesses and hold them.
Investors tend to admire Buffett because he's very smart.
And I also believe this to be true. but his true superpower is his ability to just sit still.
Charlie Munger said, never interrupt compounding unnecessarily, and Buffett was a master at it.
The irony in Buffett and Munger's success stories had from the tariff tantrum was that I didn't deploy enough capital when the market was showing weakness.
Well, it's easy to blame that on maybe a lack of courage on my part to deploy cash that I had during a downturn.
When I actually look back at my portfolio, that problem wasn't really a problem because I just didn't have cash to deploy then.
So if I wanted to add to a position, the only strategy that I could have used was to just sell a current position that was probably going to be trading at a loss.
Robert Leonard.
So when I look back at that event today, I feel a deep sense of regret that I just couldn't buy more of the businesses that I thought deserved a larger weighting in my portfolio.
So one possible strategy that I've been kind of formulating and tinkering with is to just add cash from my job each month, based on my savings, but then to put a restriction on how often I'm actually buying new stocks or adding to current positions.
I still haven't figured out exactly how this would look like, but I'd really like to start taking advantage of situations like the tariff tantrum in April or the AI scare that we just had in October and November, all in 2025.
So my temptation to act takes the form of deploying money from my brokerage account immediately into the best possible situation in my portfolio or into a new idea.
But that's probably not the way to take advantage of intentional inactivity.
Fabius and Buffett would disapprove.
My compounding machine might be letting the hot air out using this strategy rather than maybe being more selective about where I pick and choose my spots to get the compounding engine even hotter.
So the two big lessons here are that I initially felt that action on a monthly basis, such as keeping my cash allocation as close to zero, made me feel productive.
It allowed me to continue building positions, but at a cost.
And that cost is that waiting is what produces the most remarkable results.
So instead of deploying capital throughout the year, maybe I should have deployed the lion's share of it when the market decided it temporarily did not like stocks.
Had I done that, there's no doubt in my mind that my returns this year would have been much, much better.
So that was my lesson from April.
I underestimated the strength of patience as a part of my compounding engine.
But inside the companies I invest in, the compounding engine looks much, much different.
It's not just patience, it's people.
And this year I saw something in the Netflix story, the Amazon story, then again in the nine case study that I outlined in the book.
So let me take you into that story because it's added another lens through which I analyze businesses today.
Now, when I think about what makes businesses such as Netflix, Amazon, Bergman & Beving, Constellation Software, or Heiko so great, I also think about how these companies can survive highly competitive industries.
After all, they all certainly have very, very big advantages.
But they just can't rest in their laurels because a competitor is probably waiting right around the corner to eat their lunch.
And the magic fairy dust that connects all these businesses is culture.
Culture is often visible long before a stock price appreciates for decades.
So let's discuss exactly why that is.
So in 2001, Netflix had a significant issue.
The tech bubble had just popped and funding for tech-focused businesses was drying up faster than the Mojave Desert.
They just fired 33 of their workforce and their founder, Reed Hastings, felt sick to his stomach about it.
But oddly enough, a few weeks after firing these poorer performers, he observed something very, very strange and unexpected.
Productivity rapidly increased.
Hastings realized that these poor performers were dragging down the excellence of the outperformers that were already inside of Netflix.
And this became the bedrock of his principal talent density.
The other two bedrocks, candor, be open, blunt, and have quick feedback loops to avoid complacency.
And the final one was a reduction in control.
When you remove rules, you empower your employees to make great decisions without wasting time seeking approvals.
These three principles gave me my first clue that a culture helps predict behavior and behavior helps predict compounding.
Before founding Amazon, Jeff Bezos worked at D.E.
Shaw, an elite quantitative hedge fund.
But D.E.
Shaw was fascinating because he wasn't just recruiting these traditional finance types.
They were actually recruiting people like mathematicians, computer scientists, physicists and generalists who had these kinds of unusual problem solving capabilities.
Their interview process was famously very quirky and probing.
It was built around some open-ended analytical puzzles rather than focusing solely on the applicant's resume.
They'd ask questions that seemed quite odd, such as how many fax machines are there in the United States?
Now, as a result of these experiences with Shaw, Bezos cloned many of Shaw's hiring practices when he started at Amazon.
And embedded into Amazon's culture was his unique hiring operating system.
They had a concept called the Bar-Razor Program.
And this was a single person in the hiring process who had the power to veto any hire.
This prevented the culture from being diluted by mediocrity, and it ensured that Amazon kept raising the bar on new hires.
They also focused on two themes that were heavily emphasized in the compounders, which were decentralization and long-termism.
Amazon fostered this mental model that Bezos called the two pizza teams.
Any team working on a project should be small enough that it can be fed with two pizzas.
That meant that teams stayed small and efficient.
If you could get the same output from a two pizza team, why bother with a 10 pizza team?
Bezos was also fond of his day one philosophy which showed that he thought Amazon still had a very, very long way to go in its maturation.
This allowed him to take some long term bets that maybe were a drag on the business in the short term but had potentially very, very large effects years down the road.
Amazon was my second confirmation on the power of culture, and it showed that high talent, autonomous cultures behave very differently under stress.
They remain resilient and even can improve their abilities, while the average corporation just simply fails.
Amazon showed me that high-quality, scalable decision-making was a key to the compounding process.
Then we move on to the compounders.
So these were boring businesses like Heiko, which manufactures third-party plane parts, yet has quietly destroyed the market's return for decades.
Across all nine of these case studies, the DNA was very similar to Netflix and Amazon.
The businesses used small teams and empowered them to make decisions.
They optimized the incentive system to keep employees accountable and to make them feel like owners of the business.
They also had employees who just loved what they did and helped carry the culture forward for these winners, for the next generation.
The companies outlined in the compounders had a kind of cultural feedback loop.
Good culture attracts high caliber talent.
Good talent makes high quality decisions.
Better decisions compound at higher rates and with lower risk.
And compounding reinforces culture.
And culture continues to attract top talent.
It's a reinforcing feedback loop, the kind of feedback loops that I'm always searching for inside of a business.
Now, let's complete the circle and connect these three stories.
Netflix showed this high level of cultural innovation by emphasizing things like talent, candor and responsibility.
Amazon... making autonomy.
The compounders showed that creating compounding feedback loops based on culture improved and extended a business's runway, which helped allow it to compound for decades.
The key here is that culture is the upstream indicator to search for in businesses that can compound for decades.
The financial results are the downstream outcome of that strong culture.
And once you see this, it really becomes impossible to unsee it.
So how did these insights affect how I analyze companies?
By emphasizing company culture when I speak to management.
I'll also see where businesses are using things such as centralization versus decentralization, and which direction that they're moving towards.
I also pay special attention to the candor that management exhibits to ensure that they are highlighting both wins and losses.
I also try to ask questions that cover longer timeframes.
Maybe I'll ask something such as, if all things go well, where do you see yourself in three years?
And see if they have a quick answer or if they just haven't really given it much thought.
All these learnings weren't just a nice idea to just ponder.
They have become a genuine filter and checklist item that I can add to my toolbox to help separate good from bad investments, as well as sharpen or dull my conviction in current positions.
Now that I understand the compounding engine inside of a business, I'll continue to find ways to identify cultural aspects as quickly and accurately as possible.
Were founder-led.
I've actually challenged the whole founder's effect this year.
So doing my company DNA episodes actually showed me one of the greatest strength of founders.
Now, do founders matter?
Of course they do, but I think not necessarily for the reason that most investors assume.
Great companies don't just survive purely because they have a founder at the helm.
They survive because founders left behind a codified DNA that outlives them.
So, when you look at businesses like Netflix, Amazon At Home Depot, these were four businesses that I researched quite in depth this year.
And even though they're no longer founder-led, these businesses continue to generate significant cashflow and remain very, very relevant today.
Now, why is that?
So when Bernie Marcus first came up with the idea of Home Depot, it wasn't just to replicate what he'd already done at his former job the do-it-yourself experience for his customers to make it the best possible experience.
Bernie Marcus and Arthur Blank were just obsessed with service and empowerment.
Let's take a quick break and hear from today's sponsors.
You know what sets the best businesses apart?
It's how they leverage innovation to turn complexity into growth.
That's exactly what Amazon Ads is doing, powered by AWS AI.
Every day, Amazon Ads processes billions of real-time decisions, optimizing ad performance across a 31 billion advertising ecosystem.
The result is campaigns that run 30 faster and deliver measurable business impact at And better yet, every enterprise can apply the same innovation playbook that Amazon perfected in-house.
See the Amazon ad story at aws.com slash AI slash R dash story.
That's aws.com slash AI slash R dash story.
Startups move fast.
And with AI, they're shipping even faster and attracting enterprise buyers sooner.
But big deals bring even bigger security and compliance requirements.
A SOC 2 isn't always enough.
The right kind of security can make a deal or break it.
But what founder or engineer can afford to take time away from building their company?
Vanta's AI and automation make it easy.
Plus, Vanta scales with you, backed by support that's there when you need it, every step of the way.
With AI, changing regulations and buyers' expectations.
Vanta knows what's needed and when, and they've built the fastest, easiest path to help you get there.
That's why serious startups get secure early with Vanta.
Our listeners get $1,000 off at vanta.com slash billionaires.
That's V-A-N-T-A dot com slash billionaires for $1,000 off.
It's the new year, which means that it's the best time to finally start the business you've been dreaming about.
Just a couple of years ago, I launched my own e-commerce business, and Shopify was exactly the tool I needed to get started.
While many people continually push off their dreams until the next year, I am here to tell you that now is the time to capitalize on the opportunities right in front of you.
Shopify gives you everything you need to sell online and in person.
Millions of entrepreneurs, including myself, have already made this leap from household names to first-time business.
Shopify grows with you every step of the way.
In 2026, stop waiting and start selling with Shopify.
Sign up for your $1 per month trial and start selling today at shopify.com slash WSB.
Go to shopify.com slash WSB.
That's shopify.com slash WSB.
Hear your first... This new year with Shopify by your side.
All right back and to go out of their way to serve them as best as possible, rather than what some of their competitors were doing, which was running away from customers and trying to keep distance.
Bernie and Arthur eventually left the management of the company to their predecessors.
And yet when you looked at the culture that they created, it hasn't really changed that much since they started the business in Atlanta.
Home Depot's orange-blooded DNA has replicated itself from just four locations at inception all the way up to about 2347 locations today.
McDonald's offers a very unique way of looking at culture.
Ray Kroc wasn't even the founder of McDonald's, but he really defined its DNA.
The business was founded by the McDonald's brothers, but where Kroc's principle value came was in really scaling the systems, products and services that McDonald's is so well known for today.
Kroc employed the right people to help set up these systems and make it a core part of McDonald's operations.
So what were some of these systems?
First was a standardization of operations, making sure that California tasted the same as a burger in Illinois.
And Kroc knew that customers wanted food quickly, not in 20 minutes.
So he created the systems inside of each McDonald's so that McDonald's could pump out its product at a very quick pace while maintaining quality.
He also made sure that locations were clean and were desirable places to go quickly eat a meal.
And he made sure that all of these procedures were replicable not only in the US, but all over the entire world.
And the ironic part, the man who wasn't the founder created one of the most durable founder DNA of any business today.
Next was Coca-Cola.
So, in terms of DNA, Coke has outlived literally dozens of CEOs, as the business was founded all the way back in 1886.
So Coke has survived numerous leadership transitions, wars, and even globalization.
Now where Roberto Goizeta came into play wasn't so much in creating Coke's DNA, but in strengthening the DNA that it already had.
Instead of diversifying Coke's focus into non-Coke-related areas such as media, shrimp and wine, Goizueta ensured Coke stayed focused on what it's known best for Coca-Cola.
And even he actually made a massive mistake with New Coke, but he was able to overcome it due to the strength of Coca-Cola's brand.
Goizueta was hyper-focused on brand dominance, expanding distribution and bringing Coca-Cola to every corner of the earth.
He designed Coca-Cola to focus on generating cash, running efficient operations, by incentivizing things like profits and relentlessly pursuing consistency.
Coca-Cola is strong proof that a business with exceptional DNA can compound across multiple eras and compound at even higher rates once it has the right person under management, focusing on the right things.
And it also shows that a business even as great as Coca-Cola can be misled by wrong management for a time.
Now Bezos, who I've already discussed today regarding the bar raiser program, the day one mentality and the two pizza teams brought his own unique flair and experience with him when he created Amazon.
But it wasn't just those things that drove him to engineer Amazon's DNA.
I would say that, similar to Ray Kroc and Bernie Marcus Bezos, was just obsessed with his customers and with delighting them at every possible opportunity.
And another vital aspect of Amazon's DNA that was passed on from Bezos was this high velocity decision-making.
So in his 2015 letter to shareholders, he wrote, speed matters in business.
Many decisions are reversible and do not need extensive study.
So he split decision-making into two types.
So there are type one decisions which had these kind of one-way doors and there are type two decisions which had two-way doors.
A type one decision was high stakes, hard to reverse and required a slow and deliberate thinking process.
Type 2 decisions were low stakes, reversible, and should be made pretty quickly.
Bezos felt the biggest mistake that companies make is to treat type 2 decisions like type 1 decisions.
This wasted time and energy that could have been better spent elsewhere.
This is why Amazon tested out many choices that just didn't end up working, such as their attempt at a mobile via the Amazon Fire Phone.
Now, similar to many compounders which Amazon clearly has been, Bezos also focused on decentralization.
Bezos designed the company to be this kind of loosely coupled but tightly aligned company.
Amazon can be thought of as kind of a conglomerate of thousands of small startups glued together by a shared culture.
And Amazon has flourished even after Bezos has stepped down as CEO, showing that a well-developed system can outlive even the most legendary founder.
Now there are four lasting DNA traits I think were repeated among all four of these exceptional businesses.
The first, customer obsession.
Home Depot displayed customer obsession by making sure that its customers left the store with exactly what they wanted, and at unbeatable prices.
Amazon focused its efforts on delighting customers rather than just focusing on the competition.
And McDonald's focused on consistency as it already had an exceptional brand.
Number two is service ethos.
McDonald's relied on its speed and predictability.
Home Depot made sure all of its employees, even if they weren't consumer facing, knew how the business worked at the floor level.
Number three is operational discipline.
Coke focused on its global distribution network to ensure that customers could easily access its product, no matter where they traveled in the world.
McDonald's had their hamburger university, where they educated their staff in detail on the inner workings of McDonald's functions.
And fourth here is aligned incentives.
Coke under Goizueta focused on profits over growth.
Bernie Marcus and Arthur Blank made sure every Home Depot employee felt like a business owner, which is why they went out of their way to end up helping customers.
And McDonald's made sure that they served their franchisees as best as possible to help set them up for success.
That's the founder DNA framework.
A good founder makes themselves just non-essential to the running of a business.
That's the mark of a truly legendary founder.
Because once the business is able to copy their DNA, the company is just set up to survive, no matter what obstacles come its way.
So you could say the best founders don't build companies, they create cultures that can survive them.
Now we've discussed a lot here about culture and company DNA, which helps businesses survive across multiple eras.
But at my heart, I'm an investor, and I also want to focus on things like survival.
If I hope to achieve financial freedom, I need to make sure that I actually reach the finish line.
So let's say I want to make it to the finish line with as few war wounds as possible.
Well, in that scenario, I've come to realize that I need to place probably less emphasis on the upside and even more emphasis on downside protection in order to maintain durability.
So the interesting thing about compounding is that yes, it's very, very powerful, but it's shockingly fragile as well.
One single bad decision, excess leverage, poor portfolio management or emotional overconfidence can easily erase years of great decision-making.
Whereas I used to think of downside protection as being overly defensive, I now see that as a vital part of keeping the compounding engine running in an uncertain and unknown world.
It's no surprise that I've underestimated and how to quantify it.
As time has passed, from gambling with sheep bones to gambling on sports, we have learned that risk has some sort of structure, but it's definitely not intuitive.
Humans want to believe that the world is stable, but in reality, it's probabilistic.
And progress comes from taming randomness.
We can never entirely avoid it simply because randomness will never stop breaking things.
And investing is no different.
Outlier events will dominate our results both to the upside and to the downside.
So what exactly do we need to do in order to make sure that we're not blowing up our portfolio?
We focus on the key lessons of Seth Klarman, the margin of safety.
So Klarman understood that in investing, there are two types of investors the speculator, who relies on stories, momentum and short-term narratives to justify their investments.
And then you have the investors those who focus on things like durability, cashflow and buying assets for more than they're worth.
While it's easy to think of the margin of safety as being a purely analytical tool, it's really a psychological tool first and an analytical tool second.
The margin of safety is protection from our own misjudgment, which happens a lot more often than even I'd like to admit.
It's humility, which helps determine the proper position sizing.
It's in refusing to pay for a business that's priced for perfection.
And lastly, it's in designing a process that assumes that you will be wrong but can still survive when you swing and miss.
So when I invested in crypto, I had no margin of safety.
I used leverage, which I thought was a multiplier of returns.
But in reality, it just multiplied my own fragility.
I also had too much emotional reasoning that I allowed myself to masquerade as in-depth analysis.
So the margin of safety essentially serves to reduce fragility, a concept that I've taken embarrassingly long time to understand.
Now, one investor conditions.
He was intentionally looking at how businesses would grow when everything was just going to crap.
And this meant that in the case of things going decently or well, that was just pure upside.
Now, this matters more than ever in current times.
Interest rates have climbed and they're unstable.
Inflation has been rampant.
Geopolitical arrests are evident around the world and even in our backyards.
Supply chains have been disrupted by onshoring.
The number of unknown unknowns is following kind of this exponential arc.
Now, I've been pretty good at finding investments that haven't gone to zero.
Only one business I've ever owned is no longer on the market, and that's because it was bought out at a premium.
Every other business still has ongoing operations.
But I must admit that I bought some companies that I thought could perform well in adverse conditions, but then when those conditions arose, they just didn't perform as well as I'd hoped for.
Alibaba was a great example where I thought the business would perform well, but they had several headwinds that I didn't weigh heavily enough and therefore I was heavily disappointed as a shareholder.
This year, I saw how businesses would react to many of the issues that I listed previously.
Businesses like Lumine and Topicus, which specialize in vertical market software companies, continue just kind of chugging along because they have very little inventory and are therefore unaffected by tariffs.
They also don't need to worry about moving their manufacturing or switching suppliers.
While businesses like Lumine or Topicus aren't exactly the sexy kind of AI plays that seem to be dominating the markets today, they are the types of businesses that are much less likely to be killed.
Those are the businesses that I love the most.
So these stories tell me three things.
One, risk is much older than markets.
Two, fragility is an underappreciated attribute of the margin of safety.
And three, durability under stress separates the winners from the losers.
When I combine these three things, I was able to develop a much more robust downside protection system.
So how have I integrated this into my investing this year?
There are a few ways.
If I'm looking at the more analytical angle, it's simply by increasing the probabilities of my bear thesis.
Instead of using low numbers like 10%, which is unrealistic, I might now default to 33%.
In my inflection point businesses, I use an even higher number, maybe closer to 40%.
Doing this helps me take into account just how a company will perform under adverse conditions, and it builds right into my evaluation and analysis.
Another way to think about this is in the multiples that I use at terminal value.
When I look at the price of businesses today, it's very obvious that investors are projecting the present into the future.
The S&P 500 trades at around a 28 times multiple.
This means that many investors are pricing in future growth and enthusiasm, and that's only under solid conditions.
What happens in a downturn?
Do all these businesses continue growing at historic rates?
Are investors likely to hold them once they see a cut in profits?
This is why I focused on multiples that are better aligned with a business's average, rather than those that the market is focused on, just maybe over the past year.
After spending time thinking about fragility and downside protection, I realized that much of it doesn't come from macro shocks or competitive threats.
It comes from people making key decisions within a business.
And, more specifically, it results directly from the incentives that guide people's behavior within a company.
If culture shapes how a company operates, incentives help determine why they operate in very specific ways.
Munger once said.
I think I've been in the top 5 of my age cohort all my adult life in understanding the power of incentives, and yet I've always underestimated that power.
And never a year passes, but I get some surprise that pushes my limit a little further.
I felt like I've been studying incentives for years, but in 2025 I really made it a much higher priority.
And like Munger, I feel like I always underestimate its power.
The problematic part about incentives is that they don't shout from the rooftops about how important they really are.
They're subtle, but they create predictable patterns.
Researching them this year has reinforced the idea that if you want long-term alignment between shareholders and management, you really need incentive structures that support it.
Incentives help shape the conditions under which key management and capital allocators make very, very key decisions.
In my opinion, the best incentive structure that I've ever seen is Constellation Softwares, which is why I hold positions in both of its spinoffs.
The incentive structure for the spinoffs was nearly identical to Constellation's.
Now, the key here is the structure of these incentive systems.
So managers at various levels receive cash as part of their incentives, but this cash is bank accounts.
A portion of the cash, usually around 75, is used to buy shares in their own company on the open market.
And to make things even better, the shares are then held in escrow for three to five years.
So how exactly do they unlock this bonus?
Well, it's tied to things like return on capital thresholds.
There are no short-term bonuses tied to things like revenue or stock prices to try to make a quick headline-grabbing deal just to juice your bonus.
The system incentivizes things like cost discipline, capital allocation, efficiency and long-term thinking.
Now the outcomes of this system help shape the behavior of Constellations, managers and capital allocators.
Managers think like owners because they literally become owners under the incentive system.
If a new deal comes onto their desk and the hurdle rates aren't correct, they simply know they can just walk away from that deal and let another sucker accept the terms.
Since Constellation is a forever home for vertical market software businesses, it creates this positive reputation as well for many of its acquisition targets.
People who are selling to them know that they can trust that Constellation will treat their business respectfully if they sell to them rather than to someone else.
Now this exact system helped clarify just what strong alignment looks like to me patience, discipline and an owner-operator-focused mindset.
The system is so good that it's also spread to other VMS businesses outside of the Constellation universe, such as Computer Modeling Group.
Now today I've discussed one of Seth Karman's central teachings on the margin of safety, but he also had some really, really excellent insights in his book on the power and abuse of incentives on Wall Street.
And even though the book was published in 1991, there really isn't anything that he said that still is not relevant today regarding the narratives on Wall Street.
So his point was that there's just too many participants along the investing value chain where people are incentivized to promote certain activities which they probably shouldn't be.
And these are things such as promoting trading, selling narratives to earn commissions and closing deals, no matter what the terms are, just to earn a bonus based on that deal.
Now, the system that these people are in are not designed to really protect investor capital whatsoever.
They're really just designed to increase the profits for their employer and themselves.
Now, it's not even necessarily malicious.
They're just following the behavior that is guided by their incentive system.
Now, while I have no real ties to Wall Street in terms of my money, as I manage it all myself, the situation is still very fascinating.
It has helped me to see just how powerful incentives are and how they affect the people around me.
For instance, my mom has a registered retirement income fund which is basically just an annuity, up in Canada.
She wanted me to take a look at it once and I saw what she was getting out of it and the fees that were being charged to her.
We were both pretty outraged at how much the fees the manager of the annuity was taking for themselves, and my mom hadn't even actually realized it until I pointed it out to her.
They were making a fee that nearly matched my mom's monthly payments.
Just crazy.
So what her annuity manager was doing is to collect a bunch of cash from my mom and invest it into something that just generates income.
Then, when she reached a certain age which she's already reached they would pay her with the principal and interest that was accrued.
But they're making money on the principal that they invested and on the annuity that they pay her today.
The managers are most likely part of some sort of large bank or institution.
So they're interested in maximizing their own profits for the bank and themselves, and not in the best interest of my mom.
Now, I couldn't leave this part on incentives without mentioning the impact that Charlie Munger has had on my thinking of it.
Incentives are deeply intertwined with how we behave.
But what Munger taught investors from his talk on psychological misjudgments is that incentives also change perception.
Yes, incentives obviously cause people to do weird things, but they also cause people to rationalize very specific behavior that they might otherwise be appalled at.
When your behavior determines how much money you make, you will twist reality to justify what you are doing.
I can't tell you how many shows or movies I've watched over the years where you see some drug dealer who's justifying what they do because they say if I don't do it, someone else will.
This is them just justifying what they are doing, even though it's very apparent that it's not a good thing.
Now, obviously, this is an extreme case, but I think you get the gist.
Now, the terrifying part about incentive cause bias is that it's stronger very weird things.
So let's look at an otherwise normal business like Wells Fargo, the US bank.
So in 2016 they had a scandal that went public, but the misbehavior that had been happening was from many years prior.
So what was happening was that Wells Fargo set these uber aggressive sales targets for their employees.
They needed to hit eight products per customer.
So employees were paid and promoted based on the number of accounts that they opened, and managers were evaluated based on sales team growth.
So you had a system in which both parties work together.
And unfortunately, their system was broken.
Thousands of employees, many of whom were hardworking, honest and normal people, began opening millions of fake accounts for customers.
3.5 million accounts to be exact.
These people weren't unethical by nature, but they justified their actions based on the incentive structure that they followed.
That is incentive caused bias.
So, when it comes to incentives, there are three areas which these stories really teach us to focus on.
The first is that aligned incentives create owner-like behavior, which is what we want to see from the businesses that we invest in.
Second, misaligned incentives predict short-termism and unnecessary activity.
And third, incentives shape our perceptions, decision-making and culture.
After meditating on this over the years, I've examined how it's impacted how I analyze businesses and invest.
When I'm speaking to management teams, I always try to emphasize the incentives of managers, lower-level management and salespeople.
This helps me see if employees are incentivized to create shareholder value or just to pad their own pockets.
When I'm speaking with management, I'm also actively listening to just how they discuss them.
Are they talking about how well they're going to do next quarter or in the next five to 10 years?
How focused are they on cost discipline?
I pay very close attention to compensation structures as well.
And these can easily be found in a company's filings.
I pay special attention to whether they have long-term or short-term incentive KPIs and whether they help align or misalign management and shareholders.
I've also spent time thinking about my own incentives regarding my own stock portfolio.
So my goal is to double my capital every five years.
And that means I am technically incentivized to take risks to achieve that lofty goal.
So I think that's why risk has become so significant to me.
I have to play this delicate game of finding great opportunities with the right upside, but also, you know, can't go to zero or hopefully not even go close to zero.
Hopefully they can't go down 50%.
I want my pie and to eat it too.
So when I used to analyze companies, I didn't place enough emphasis on the proxy or circular.
Now, it's one of the first things I do, as I want to make sure a business has shareholders best interest in mind, or else there's just no real reason to continue researching it.
So while incentives can be boring, like many long-term compounders, they have outsized effects when done right.
When your investments are being managed by people whose behavior is set up specifically to benefit all the parties involved, you just tip the odds in your favor of that investment being a good one.
And that is something that we can all strive for.
Thanks for spending time with me today.
If you'd like to continue the conversation, please follow me on Twitter.
At irrational, just search for Kyle Grief.
I'm always open to feedback, so please feel free to share how I can make this podcast even better for you.
Thanks for listening and see you next time.
Thanks for listening to TIP.
Follow We Study Billionaires on your favorite podcast app and visit theinvestorspodcastcom for show notes and educational resources.
This podcast is for informational and entertainment purposes only and does not provide financial investment tax or Thank.
You and the Investors Podcast Network may hold positions in securities discussed and may change those positions at any time, without notice.
References to any third-party products, services or advertisers do not constitute endorsements, and the Investors Podcast Network is not responsible for any claims made by them.
Copyright by the Investors Podcast Network.
All rights reserved.
