Yet Another Value Podcast - Artem Fokin on Improving with AI and Expert Calls

Episode Date: September 18, 2025

In this episode of Yet Another Value Podcast, Andrew Walker teams up again with Artem Fokin, head of Caro-Kann Capital, for a deep dive into research tools reshaping modern investing. Originally recorded as a webinar for AlphaSense, they explore how AI and expert call libraries have revolutionized solo and institutional investor workflows. Artem shares how he integrates AlphaSense’s newest tools—like Grid and Deep Research—into his diligence process, and the pair compare approaches to conducting and analyzing expert calls. This is a tactical, in-the-weeds discussion on using tech to sharpen your edge.You can see the first podcast with Artem Fokin (Perfecting the investing craft) here: https://www.yetanothervalueblog.com/p/perfecting-the-investing-craft-with__________________________________________________________[00:00:00] Intro and AlphaSense partnership[00:03:43] Focus on investor improvement[00:06:03] Rise of expert call libraries[00:07:53] Expert calls vs AI usage[00:11:31] Sourcing expert interviewees[00:13:19] Determining expert call relevance[00:19:23] Comparing customer and sales views[00:23:52] Bias in former employees[00:30:31] Weighing extreme expert feedback[00:34:01] Best expert screening practices[00:39:40] Switch to AI conversation[00:43:42] Efficiency gains via AI tools[00:44:43] Using AlphaSense Grid effectively[00:51:35] AI for transcript filtering[00:55:22] Deep Research feature walkthrough[00:56:21] Keeping up with new features[00:59:27] Underrated AlphaSense user tip[01:01:34] Closing and final remarksLinks:Yet Another Value Blog - https://www.yetanothervalueblog.com See our legal disclaimer here: https://www.yetanothervalueblog.com/p/legal-and-disclaimer

You're about to listen to the yet another value podcast with your host, me, Andrew Walker. Today's episode is, this is a follow-up to the podcast I did with Artem Fokin, my friend, on perfecting the investment process. This is a webinar that we did on AlphaSense. We talk a lot about using AI and expert calls in the research process, using them for improvement, all that sort of stuff. This was behind a paywall for AlphaSense, but they said after month, hey, we're getting good reviews. Why don't you put it out on the podcast and try and get more listenership and, like, you know, we want this to be out there. So I think you're really going to enjoy it. I hope you do. I'll include a link to the prior

perfecting the investment process podcast with Artem in the show notes, which was, to be frank, one of the most popular podcasts I've ever done. We got tons of great feedback on it. So I think you're really going to like that podcast. I think you'll really enjoy this podcast if you like that podcast. So we're going to get all there in a second. But first, a word from our sponsors. Today's episode is sponsored by AlphaSense. Look, over the year, You've heard me talk about it, nonstop, Alpha Sense, Tegas, they've become core to how I do investment research. They've got a virgin set of AI tools. They've got the expert calls, which I absolutely love, the expert call library.

They've got over, as they tell me, over 500 million premium sources from company filings, broker reports, news, trade journals, everything, plus the expert calls. They put it all in one place. Their AI tools let you search unique data sources in really interesting ways. This October, they're hosting their first ever Alpha Summit, 2005, in Brooklyn. dropping in and out. So the event will feature all sorts of leaders from finance, UPS, Wells Fargo, Central, Google, who's who are going to be there, sharing how AI is reshaping the investment research and decision-making landscape.

What's going to make Alphison special is it's just not just about the ideas, it's about really talking about how AI can improve workflows and the strategies that top firms are using right now. So I'd love to see you there. If you're going, you can join me there. Alpha Summit, 2025, October 6th through 8th at the refinery at the Dominole. You can sign up at AlphaSense.com slash YAVP. That's Alpha-Sense.com slash YAVP.

All right, hello, and welcome to the, I guess it's just the AlphaSense user webinar with me, Andrew Walker, the host of Yet Another Value Podcast. And my good friend, Arndham, Fokin, he is the head of CAROCOM Capital. Arndham, how's it going? Hi, Andrew. Nice seeing you again. Look, Artem, let me, well, let's just start, disclaimer, nothing on this webinar's investing advice. I don't think we're talking specific stocks, but we might dive into some like real-time

example. So people should remember that. And I'm sure AlphaSense will do disclaimers out of wazoo. Look, also at the stage, and then we can dive into everything. We were talking to the people at AlphaSense. So we are both users, subscribers, whatever you want to call it. I think we both find huge amounts of value from the product. I think we find huge amounts of value in different pieces of the product. AlphaSense and Tigis are like, they've got everything at this point. But we said it and they said, hey, why don't you guys come on and do a webinar talking about you know, we just did a podcast talking about, I don't think it was quite process improvement, but our process is investors. And a lot of that, for me personally, a lot of the process

improvements for me over the past 10 years has been adopting AI into my investing process and adopting expert calls into my investing process. I was already doing a little, but, you know, both have ramped up. And both of them have ramped up materially in large part, thanks to TECUS Alpha Sense and the tools and, you know, the expert call library network and everything. So we told them about that, all that sort of stuff. And like, hey, why don't you guys get on talk about using AI in your process? talking about using expert calls in your process, talk about how you use office and share expert process.

So that's the overall idea for this webinar, an hour of us talking about all of that. Would you add anything to that or anything else people should feel like they're going to get from this hour of the webinar? I think the theme of the both our prior conversation on yet another value podcast and today's webinar is the same theme, improving and perfecting our craft as investors. So I stand behind that. Obviously, when you and I were talking on the public, so to speak, podcast, we were speaking more broad themes as opposed to concrete specific tools of the trade. We were talking about how to use a hammer to hit on a nail or whatever other tool you may be using. Here, we will probably be talking a little bit more about, okay, how do you choose a hammer or any other tool?

or how do you use it and how you're changing in use cases. So I think probably this conversation are more likely to be more specific. So I'll be sharing some of my examples in use cases. You may throw some of yours, so I'm really looking forward. But the theme is, I think it is the same. I think you're exactly correct. And I think the way we're going to structure this is we're going to talk about using expert calls, using AI, and then as we continue that, dive deeper and deeper

and narrow into how, if people are listening to this and are subscribed to Alphson-Santigas, how they can use specific AlphaSense Antigas tools in their process as we dive deeper and deeper. So let me just start off. I made a contention in there that I'd love for you to push back on, agree with, disagree with. Over the past 10 years, I think the biggest change in improvement in my process has been, you know, when I was at McKinsey or when I was at Bing Capital, we would do expert calls all the time. But when you switch from a place kind of with approaching unlimited resources to being,

let's just call it more individual investor, small solo practitioner, whatever it is, you lost that access to, hey, I want to learn this company. I'm going to go do 20 expert calls and spend a thousand bucks an expert call. Or you didn't have 15 analysts to go summarize everything that's ever been written in a research report. I think the biggest process improvement has been expert call libraries. So you can get access to basically unlimited amounts of expert calls for an annual subscription. That's new over the past 10 years. And then AI, it can summarize 20 earnings report.

So you don't need 10 analysts under you to like. kind of get summaries of big earnings report. Would you agree with that contention? Would you disagree? Have you kind of thought about those just two overall process improvements over the past 10 years? I wouldn't necessarily call them process improvements per se. I keep using that term and you keep pushing back. I would call them disruptive innovation that came to the investment research space.

And in terms of tools that I use, use. Those, meaning expert call libraries, and bespoke expert calls, because the price dropped dramatically, as you pointed out, with the advent of TIGUS and stream, Mosaic, alpha, sense. Again, I will use the alpha sense in TIGU's interchangeably, because now it's under the same umbrella, and we don't need to trace exact corporate history. Those low the cost. And the library, again, technological innovation, network effect that was built by connecting creators and readers. can be both great and read at the same time, that usually expands the total addressable market

and lowers the cost because of that. You convert your variable cost model into semi-fixed semi-variable. That would let you the expansion of entire time and usage of expert calls, in my opinion. I haven't seen the data, obviously, but that's my guess, and I think I'm fairly confident that I'm right about that.

So those were two disruptive innovations. People may bring some credit card data alternative data that are still very, very, very, very expensive. We don't use that much of credit card. We don't use credit card data. And our alternative data is pretty simple, such as Google Trends. By the way, Opposance, maybe you figure out how to build something and lower the cost in that vertical as well.

But for me, personally, expert call libraries and advent of AI were two biggest disruptive innovation in the environment that I've been implemented into my process. I agree. Let's dive into expert calls. So the reason I want to start, I think AI is a little buzzier, and I think AI, like everyone should and it should be experienced with AI. But I want to start with expert calls because I think that your tool that bluntly wielded can be useful. But I think the finer you kind of like sharpen that sword, I think that it's like a force multiplier in terms of the effectiveness of expert calls. And I mean that both for reading expert call libraries, reading expert call transcripts, but especially for conducting. expert interviews. Like, I know you and I've done some together before. I've been on calls with other people. When I'm on an expert call with someone who's really good versus someone who, you know, someone who's really good, someone who's super prepared versus someone who might be doing it by the seat of hand. I'm just always impressed by how much more I learn and everything. So I just want to stop there. How do you use expert calls and then we can start diving into the

different ways to use them and everything? Okay. So as I joke, most of my time I spend either listening or reading. So and if you use these two modalities, unsurprisingly, these are two use cases for expert calls. I either listen, meaning I conduct a bespoke expert call or I read a certain number of calls that are already in the library. And that number can, if there are already a lot of calls, the number of what I am reading can vary from just a few because they made it. that are not that many. And I think the record one was probably 70 calls across Tigris and

AltaSense that I've read. And I did probably five or six of my own as well. And I literally read 70 calls. Since then, the number has only gone up. Now it's probably up to 100 or so. And I literally read all of them. And that was a lot of fun because the business was sufficiently complex. And by the way, I could mention the business to put things in perspective. It's an IWG, the hybrid, working flex space provider that does operations globally. Full disclaimer, Cracken Capital, LLC, and or its affiliates are on the shades of IWG. This is not investment advice or recommendations to buy yourself any securities. So I'm just giving it for context.

The business is complex and has a long history, a lot of evolution, lots of moving pieces. So my first thinking was, I'll do five expert calls and I'll figure this out. Did five bespoke expert calls? Did not figure anything out. Back to square one, I'm like, okay, I guess I need to read this 70 calls. And then I methodically read all of them, but both on IWG and we work because it's a very close P.N, when you study the industry, we want to study several players if they exist. And that was incredibly educational for me and informant.

And now many things that come up, I like, yeah, I know the answer. I've read this call and someone in the industry or a client mentioned this. It was mentioned two or three years ago, but there is same. Chanel that's applicable today. So I love reading those things. And I also love doing my own. In fact, what often excites me when I research a company is when I log in into Alpha Sense, I put the ticker and I choose that I want to get search results only for expert calls and it shows zero calls or one or two calls. It means that probably nobody really looked at it. And that's for me is an opportunity to learn more about this in company that I perceive as an interesting investment

opportunity and deepen my research tremendously compared to probably what is out there. We're, let me, a lot of questions, but let me start with one, just like sourcing of experts. So I run the yet another value podcast. And one thing I've started doing recently is I've actually started trying to do an expert call on every company before I have the, before I do the, before I do the podcast on the company, you know, it's an idea-focused podcast for those who haven't listened one hour long. You can listen to it. It doesn't matter. But I've started trying to do an expert call on every company before I do the podcast so that I have more informed questions, more interesting insights, all that sort of stuff. But one thing that's jumped out to me is like, you know,

some podcast, it's so obvious who I want to do the expert call on. You know, you're doing a company that has one 80% customer. Guess what? I want to talk to somebody who works at the 80% customer and get their insights into the company. You know, you're doing a company that's got a new drug. I want to talk to a doctor who's prescribing the drug. Ask them how they're viewing it. Ask them how they're seeing. Some companies, you know, I would use as a very loose example.

If I was going to do an expert call on Berkshire Hathaway, what the heck expert call would I do, right? It's this conglomerate that is basically Warren Buffett and like a former wouldn't really help. Charlie Munger had any rest in peace, but he wouldn't even talk to me. but, like, I wouldn't do a former. It's really a culture concept. And I say that because Constellation Software, like, what that is a roll-up of, you know, software businesses focus on municipal governments, if I remember their core focus correctly.

What is, what am I going to do with Constellation Software if I'm going to talk to an expert? Like, it's literally a hundred different small companies rolled up together. There are several other ones, but I share with that. So when do you know if an expert company, an expert call works for a company, works for an investment thesis, versus maybe doesn't like the Berkshire Hathaway example. Okay, great question. Before I answer that, let me just clarify something that what you probably meant to say. I think he was saying that if a company has a very large customer,

you may want to talk to the customer. I think what you meant to say is that you want to talk to a former employee of that very large customer. Yes, yes, you are exactly. It was from compliance perspective, talking to a big customer is not proven or smart. You are right. The TIGA's compliance people will hop on. Yes, and I'm going to be very clear.

Alpha Sense has fantastic compliance team who is very thoughtful, very diligent, conservative, in a good way conservative, and they would not source an expert, which could present a compliance on legal issue. So in Andrews example, the right way to go about it will be find someone who left that customer a year. Yes. Who may understand the product, understand the process, understand the relationship, understand the relationship, the relationship, but that person has no information that may restrict the investor. Yes. And then again, Alpha-Sense team, fantastic on that sense.

And by the way, that's another great thing about using Alpha-Sense call expert library or asking to organize calls by Alpha-Sense. There is a record that has been reviewed by a compliance team, and you know that you're clear, you're good. That's another, again, it's where you start what you asked, but it was very proximate point you make right now. Okay, going back to the heart of your question is sourcing expert calls. Remember our conversation about golf and different calves?

Yes. Yesterday. So you need to use a different way for those who didn't listen to our prior conversation. I do not play golf, unfortunately. So, but the analogy which I used yesterday was that for different situations, you use different tools. similar in golf or different terrain, you use different cups. Otherwise, you're not going to do well at golf. So he's the same.

This is how I approach it. Usually, you figure out the key ingredients for success of your investment thesis. For example, if your idea is based on product superiority that the company has launched six months ago, and you believe that this product is massively superior to everything else out there. Maybe it's safer, maybe it's cheaper, maybe it's more efficient. You know, people in Silicon Valley like to say like, oh, this is 10x better or 10x cheaper. Now 10x is a more of a figurative way to describe that.

It may not necessarily the 10x better, but it should be better, very substantial. In that case, you need to focus, I would want to focus all my research efforts on that product and understand customer perspective, both people who already using that superior product, people who switched, people who have not switched but tried, and people who didn't even bother, learn out about the product and understand what's stopping that. That's one example. In another example, there may be a thesis, which is based, okay, product is fantastic. I got comfortable with that.

In business, there are two problems, as my Stanford Business School professor joked. Do you know those problems? Number one, not enough sales. Problem number two, everything else. Okay, so you got the product. Can the company sell tons of that product or service? Do they have a well-established sales motion and incredibly running sales machine or not? Guess what? In that case, I will want to talk to former sales people.

What's the sales process is like? There is another company that Caracan Capital LLC and or its affiliates own called softwave, software medical listed in Israel. Again, this is not investment advice. So in my opinion, based on my research, they have superior product, and you can ask me later how I got to that conclusion and why it's superior, etc., etc., But I also wanted to understand the sales process. So Alco Sands helped me source a former salesperson. And I spoke with him for now.

And I literally asked him, would you role play with me your conversation? Imagine I'm a doctor, dermatologist. You came to my office. We shake hands and I asked you why you're here. Why you're taking my time away from my schedule and from my patients. Let's go through that. And we'll literally borderline in the role play probably for 20 minutes

overall over the course of entire hour. And then I was asking different other questions. That's incredibly helpful to understand how this sales happen. Because sometimes it's very easy when you are in our Excel or Notion or Microsoft Word, whatever we use. It's very easy to think that sales just happen. But sales just don't happen. someone needs to sell it.

But everything which is in my office here has been somehow sold to me. So, and I think understanding sales process is one of the most incredible things. Like overall, I believe that if someone, by the way, like, so I'm in my early 40s, if I look back of my life, I wish I spent six months in sales in something, ideally B2B, just to understand the process and psychological. challenges of that and how it works, I think it would have made the better investor. Now, I mean, in my only 40s, I'm not going to go back and get the job, but the best I can do is either talk to people who are in sales and learn from them or read expert co-libraries

about sales, process, and how it works. You know, so I'm going to keep, I think you will know the company I'm talking about. I'm going to keep it anonymized intentionally, but one really interesting example I've seen recently is there's a company, and they have an FDA-approved study that says, their, let's just call it device defective rate, is 1%, and all of their FDA, all of their peers are last generation products, and it's 10%. So when you see that, you would say, oh, my God, this product is literally 10x better. You chose 10x and 10x, and these defects are, they're pretty bad. You know, it's an implant device. If you have a defect, it's, there's another surgery

at minimum require, right? So you read that and you say, oh, my God, this is a 10x better product. And it's so interesting when you do expert calls on this company, when you talk to sales people about how they're selling it to people using that, using that, hey, this product is 10x better, do you really want to take the medical malpractice risk of putting a different product in when this product's 10% better versus when you talk to doctors and then you hear doctors and you say, hey, I'm reading an FDA study that says this product is 1% defect rate versus other last. products at 10%. Why are you still using a 10% last-gen product? And they say, hey, the last-gen products were only, all of the FDA studies were done in the 90s. Guess what? There have been huge process improvements and huge improvements in surgical techniques since then. We think that the last-gen products are just as safe as the current-gen products, and we've got our own evidence and our surgery specs up. So it's just, it's really interesting, you know, you hear the company spin, and then you can use the expert calls to dive in and hear how the Salesforce is using

it, and maybe if the customer, in this case, the surgeons are buying it or not buying it. I have more questions on expert calls, but I think that's a really interesting anonymized example I tried to give. I'll pause there and let you just comment on any piece or if that would mention you from that. Again, on and on a company that we own and it has FDA clearances. It's very interesting. I asked probably six, seven, eight doctors.

and they, and I asked them, so again, I'm talking about softwave here, right? I'm still talking about softwave. We still loan the shares, nothing changed in the last five minutes. So they have almost 10, I think it's, I believe, number nine. So let's round it to 10 for the sake of simplicity, FDL clearances, for various indications. And as far as I understand, based on my research and conversations, by AlphaSense, almost nobody else has as many. So then ask doctors, doctor.

Soapwave has this number of the clearances. And that device doesn't or has only one or two. Do your doctor care? And interestingly, I receive a fairly broad range of responses. Some people care because they say my liability if something goes down is a lot lower. the risk of that, because I was using an FD clear device for an indication that was clear. For me, it gives me a comfort. I like that. On the other extreme, and I will skip all the shades between those two extremes,

someone may say, I don't really care. I'm really good at what I do. I can use it off-label. I'm super confident, doctor, I don't care. For me, it's just a marketing boss. I don't care. That's a range of opinions. And that's, again, something that I've gotten more comfortable as over the years, as I've done many, many, many, many, many export calls is that sometimes there will be no one answer because different customers may have different opinions, and that's okay.

because probably I was obviously less experienced back then and I was in general and less experienced and conducts an expert calls. You go and you expect like, you'll ask a question and every single doctor in our example will give you the same answer. Yes, yes, yes. Great, I got it.

It's certain. Nothing is certain. Different people have different opinions. And that's okay. But it's incredible helpful to understand the broad range of opinions and incorporate them into your thinking about the investment thesis,

whatever that thesis is. Let me go back. So you mentioned when you were talking about Software, talk to a former salesperson. And formers are actually the discussions I have the hardest time with because most formers, by definition, have left the company.

And I find that they can... I think it's not almost. I think it's everybody left the company. Otherwise, they're not former. By definition, that's why I said, by definition, they've left the company. They, many of the, most of the time, the formers leave, I don't know if it's a much time,

but a lot of the formers I talk to have left through a layoff, especially now, you know, on the heels of the 2022, like kind of all the growth stocks going through a round of cost cutting, around a fat trimming. A lot of the former's left through layoffs. And I find sometimes it is hard to cut through the bitterness of having left from a layoff versus how the customer is actually treated. Or sometimes the person loved being at the place.

was wildly successful left and they've got nothing to say but great things about the company. And then you look in like the company is kind of going up in flames and you're like, oh, well, it's hard to marry them. So I want to ask like, how do you kind of separate the bias of a former, whether it's positive or negative, versus what you're learning in the call? Because I just find they can be such double-edged swords when you talk to them. It's difficult. Let me ask for this before I answer the question. As far as I know, you're married. I know you're married. I know your wife's name.

I think you mentioned it publicly, so I will say her name is Alicia. It's okay, fantastic. Have you had girlfriends before you met? Arnhem, are you trying to give me a trouble of you, bro? No, no, I'm not. I might have had one or two. Okay, so I'm hoping that if someone calls them and asks, is Andrew a good human being?

They will probably say that you're a good human being, even though you're not together anymore. So, I think formers is a little bit the same. And by the way, farmers may be formers for a variety of reasons. Not all of them got laid off. Some of them got a better career option. Yes. They accepted the offer.

They moved on. There is no really, there is not much bitter feelings in that case. There will be some farmers. But where I'm leading with my question about your dating history, Alicia, I'm really sorry. I hope I will not get Andrew into trouble. So is, I think, how the company would treat a former employee, if that employee was dismissed, whether it fired or laid off, doesn't really matter.

It also tells you a lot about the company culture. I think one of the best indicators about indirect evidence about culture that I've had with farmers is when a person will honestly tell me there was a lot. round of layoffs, and fortunately, I was let go. I think it's a great company. It's unfortunate. And then you ask them if they call it tomorrow and say, hey, business is doing better. We need more people.

We love you. We're sorry that you had to leave. Would you like to come back? And many people say, oh, yeah. Some people say no. Some people say yes. That's a telling sign. Similarly, would you recommend your brother or sister or a nephew or a niece to work there?

It tells you something about the culture. Now, it's only one piece of evidence. And again, you and I spoke about this yesterday. We are in the business of making judgment and decisions. So similarly, in this case, when we talk to any expert, we need to make a judgment about their credibility. And it's not always easy. Often it's difficult. You know what I was doing before I went to business school, right?

In my prior professional life? Yes. Okay, what I was doing before that? You were a tax lawyer. Yeah, I was a lawyer, right? So now, in law, there is this concept of preponderance of evidence. So I and some of those frameworks from my legal days, I think I still use them as mental frameworks in my investing.

So I think preponderance of evidence would be one of those. I cannot establish with certain saying that were 10 experts, customers, for my employees, industry consultants, whoever told me is true. I don't know. They may be lying, possible. They may be telling me the truth, what they believe is truth, but they're simply wrong. It could happen. All of us are human beings.

But what you're trying to do, you're trying to build a case that way there is a very high chance. supported by the preponderance of evidence that this would be a good investment to make based on your thesis. Can you ever get to beyond the reasonable doubt, which is the standard in criminal proceedings? Probably not an investing, unfortunately. But could you get at least to preponderance of evidence, kind of more likely than not standard? I think so. That's what we're trying to do.

Let me, I like what you said. You're never, like, it would be awesome if we could interview 5,000 formers at every company and, like, really build on database and be like, oh, yeah, there were 20 who were upset, but 4,980 didn't, this is great coming. You know, in terms of extremes, right, I've done calls before, and I'm thinking of a specific company with three farmers, right? And this was a smaller company. So three formers is a large percentage of their firms.

Two of them were happy, had good things to say. and one of them, you know, was one star review would have been too high, right? It was as little as they could go. This was the worst place in the world. Now, all of these guys had left through layoffs. And I don't know, like the guy who I was interviewing, he was there for nine months. You know, he might have been surprised by the lay if it was a pretty miserable experience. But I just wondered, how do you weigh the extremes, whether it's my example where there's one person who is unbelievably bitter or, you know,

sometimes I'll do calls and three people are met, you know, company's fine, wouldn't go back, but no bad words today. And one person is over the moon. Do you, you know, in investing extremes are what makes much of an investing career. So do you weigh extremes more or less? How do you think about that? I need context. I cannot apply in general without reading those transcripts and making a specific judgment call.

That's number one. Number two, you also get other data points. For example, this is my frame of reference, which may be incorrect, but I believe that generally, generally, companies with crappy culture and unhappy employees do not make great products, usually. It means that if I'm seeing that the company has really crappy product And one out of three employees, new example, was unhappy and speaks very negatively with

one-star review, will be too generous. I'm more likely to believe that expert testimony, let's use that word, while if the company is shipping great products and has happy, happy customers who are enthusiastic about the product or service, I am probably less likely to put more weight on the unhappy. a former employee. And by the way, all of us had this type of experience. Few years ago, I invested, that's not a current position, I invested in a healthcare service company.

And healthcare service company broadly defined. It was more than dealing with insurance company, let's say. So, and I spoke with a few formers, and one of them was very, very negative. But when you look at his specific lines and what he said, and you match it with management commentary, you match it with what the people are saying, you get to the conclusion that he's probably of base and too emotional and too unhappy,

and he is not really supporting it by facts. And then there is another thing here, which is important, is the art of asking follow-up questions. If someone says, like, company, culture is horrible, it's horrendous, it's toxic. You're very interesting to hear. I'm so glad you said that. could you give me an example? And if you get one example, then you ask for another example.

You keep digging. Like think about it. You put the person on their witness stand. And you're trying to get respecting their confidentiality, agreements on NDAs and everything else, of course. You try to get what is behind. And if they give you examples that for you seem totally toxic, yeah, maybe there is a problem. If they cannot come up with any tangible things, and it's all big words, they probably have credible.

That's great on expert calls. And again, the reason I want to start there is because I, I mean, at this point, you and I've talked about it, I do an expert call a week. I probably read a transcript day. Like, I find them as a hugely helpful tools. And just the more you apply them to investing, just even in terms of if you're following a company, calling a customer, a different customer, once a month, what's a quarter, whatever it is, and asking them,

or asking them, hey, you're buying this product. What do you think? And obviously within all compliance rules, I mean, what do you think? Like, it's just really interesting to continue to build that mosaic. And if people aren't doing it, I think you're getting left behind. And it's one of the few areas where you can build kind of mosaic information that is going to be pretty unique to you. Any last thoughts on expert calls or can I start switching over to AI?

I have a few ones on expert calls. So, first, screen questions. Screening questions alone can be a fantastic source of value. Yes. So what I usually do, I always design my own expert calls and ask the team, could you ask these questions? Okay, I never ask anything about the career history because that will be available in bio.

You don't want to waste a screening question on that because you cannot ask 20 of them. You ask like three or four. So that's number one. Number two, I always try to understand what that person was doing day to day. Sometimes it's pretty obvious. Sometimes it's less obvious.

So that's what I try to understand. I try to ask questions of two times. It can be either open, it. And I'm hoping that expert will write two, three, four sentences. And sometimes you learn a lot from those sentences a lot. And some questions I might ask. And this is more applies for a very, when you look for a proverbial needle in a haystack. You ask them, rate me, give them several areas of business like marketing, sales, so supply chain management, et cetera, procurement, et cetera, and then you ask them, rate your knowledge of each of them

based on the scale of one to 10. And what ideally you want to do, you want to see a lot of ones and twos and one or two, eight, nine, ten. Because it would mean that the expert is honest and not exaggerating their expertise. Because if they show, I can talk about sales and technology and product management

and marketing, probably they know nothing unless they will see you. But if they say marketing, I have no idea. But supply chain management, nine out of ten, I'm very knowledgeable. I was blah, blah, blah. That was my telltale was doing. That's a very different game.

So then also, when I read a lot of expert calls, as you and I discussed, and sometimes it's very clear that people who conduct them ask questions that it's very clear almost in advance that the expert will not be able to answer. For example, do not ask salesperson about accounting or do not discuss with a marketing person why stock base compensation is so high. They wouldn't know unless they're accounting junkie and study accounts in textbooks for fun on Saturday and Sundays.

So you need to collaborate that. Now, sometimes I get it. You may have a call for an hour. It's 40 minutes in. You ask all your questions. You kind of realize that expert may be not as good as you hoped, which happens. And then you just, okay, let me ask everything else. It could happen.

But sometimes I see like, oh my God, why they're asking this? They should have followed up on this. And I'm sure I make my own mistakes. I'm not saying I'm perfect whatsoever. That's a continuous improvement. But that's another common mistake. And then one use case that I wanted to highlight on our prior investment at Caracan Capital, and we don't own shares anymore, is a company called Crocs, the way I joke then, those very

interestingly looking shoes. So this is the stage. Let me set up the stage. As far as I remember, summer 2022, Crocs is trading probably at five and a half, maybe six times earnings for 2022, and it's already. some, let's say June. Okay, it doesn't take a genius to figure out that either the company is going out of business soon in the next few years or it's horrible and mispressed.

And what happened, Crocs had tremendous uplifting sales during COVID. And the key question was, is it just another COVID beneficiary and it's all going to collapse? By collapse, I don't mean the sterile stock price. it was already down horrible, I'm talking about fundamental performance. Or whether it's not, how do you figure this out? It's very difficult. And what we did, I spoke with several former employees. And they pull, and some of them left even before COVID.

But they shared with me all those internal changes that the company has made before COVID. And then COVID probably helped with the whole stay at home and very casual, very casual trend. Sure. But the company built such a fantastic, based on my research, I can be mistaken, foundation that they were able to take advantage of those COVID tailwinds. And that foundation is probably not disappearing. And that was very valuable learning. But again, that was almost a history guide.

Look, that would happen in 17, that will happen in 18. this was the change, we got the new markets in person, we changed this, we changed that, et cetera, et cetera. That was an incredible tutorial in history. It's almost like you're traveling to, I don't know, big France to see some castles from medieval times, and you get a local guide with a major in history. Guess what? They will tell you a lot of valuable things that you would not discover otherwise. That's the analogy. That was great, and I actually have follow-on questions, but I want to be cognizant of time on the webinar and everything, and I want to move on to talking about AI. I'd love to just start, you know, broadly, we can

dive into AlphaSense-specific tools, and I do want to talk about Alpha-Sense-specific tools, since this is an OfficeSense webinar and everything, but just broadly, how have you been incorporating AI into your process? How are you kind of using them? What tools are you using? Okay, so I think this is what we stopped yesterday. So the way I think about the usage of AI in my investing process is across the line of the framework that I've heard from Paul Enright on one of his podcasts. I believe it was podcast with Patrick Oshamson, Invest Like the Best. If I'm wrong, then it was in capital locators.

And he breaks it into digging, analyzing, deciding. And it's very simple. There are three stages. It's not. This is the flow chart diagram with 100 bucks. It's pretty simple. But I found it's effective in general. and especially when I think about air.

So I think, and then I break it, where AI for me is delivering most productivity boost. And it's mostly in digging. A little bit of analyzing, so far, zero in deciding. And this is my view as of August 6th, I believe today. So it could change in the future as technology evolves as I evolved. So that's number one. Number two.

Simplistically, we can break. usage of AI into, can you do something with AI that you used to do, but it will save a lot of time? Versus, can you do something with AI that you would never able to do? I figured out many use cases for the first one. I have not figured out use cases for the second one yet. I hope I will. So on digging, AI provides productivity boost in many ways, and I will walk you through some use cases. And again, as I mentioned yesterday, I feel that AI and expert co-libris were a match made in hub. So now, I can be using AI as a research co-pilot. I'll give you an example. I'm at a company, at a conference in May, the Riley conference was an interesting group meeting, came away

thinking that may be an interesting company to research. Got back home, a few days later, pull out, I'll some DIC write-ups just to get what the thesis has been. I start reading it. The write-up says, this company operates in 10 states. Okay, there are 50 states in the nation. We still have 40 states left, at least based on roughly two years ago. But did it change? It has been two years.

Maybe now they're in 30 or 50 or 60. Okay, not 60. 60 would be too much. 50. So, like, I don't know. In the old days, what I would need to do, I would need to open my Notion file, type their question list, which I have on the template, and type, how many states is this company current lapar rating?

And then I will need to go open 10K and look for it, et cetera, et cetera. Now what I do, I have my PDF file with VIC write up or VIC itself on one screen, I have alpha-sense on another, I pull out AI system, I ask, how many states is the company current leppy rating also could you please provide the history

of how the number of states changed over the years and any other relevant information such as revenue breakdown by state or group of state or whatever I don't know 5 seconds 10 seconds 8 seconds

I get an answer I quickly read and I know okay since then they expand to this number of states and they got core states or legacy states this is where most revenue comes from

and they got new states, but they're still ramping up, et cetera, et cetera. You're like, fantastic. I don't need to write this question down anymore, and then remember to check 10K and go. So that's my research copilot need. I love that. I'm completely with you, just in terms of the use cases of summarizing, or I know I want to go to the past three proxies

and see how incentive comp has changed over time. And that used to be like, I'm pretty fast, but that used to be a multi-hour process, right? You have to open three proxies, scroll through them, really compare or read. These companies don't exactly make it easy to see how much they're paying each people and why they're paying them. With any type of AI tool, it's a 10 second process. Hey, how is incentive comp involved over the past three years?

Let me ask specifically. That was just generic AI. I think there's really interesting things about merging AI and expert calls, but I think we can hit on them as we talk about. What about AlphaSense specifically? Like they have, especially over the past six to nine months, let's just talk about how are you using Alpha Sense specific tools? Because they, over the past six months, they rolled out several and they're going to roll out several more and they're getting much better. So what AlphaCent specific tools are using?

Okay, so you're right. Alpha Sense is a stripping bunch of new features, right? So that's fantastic. Teachers are getting shipped and shipped and shipped and shift and there are more and more. So now, I will tell you my, so the one obviously they have is the chat. And the chat can work in... regular chat or you can turn on deep research mode on the chat if you want something big output and you want it to think longer. So that's always that's fairly similar use case to chat GPT or perplexity or whatever general

AI or what I call horizontal AI use. My favorite personal picture of the Alpha Sense is what they call grid. And you can make greed almost, it's like a laguar in my sound place. you can turn that grid in almost whatever you work. For example, I will give you a few examples that I use. I will give you some examples that I think I would like to use, but haven't done much of it yet because of more and my investment style as opposed to limitations of Alpha Sense because that tool is very powerful.

So imagine you got, Andrew calls me and says, Artem, I have this great stock idea, this is the thesis, et cetera, et cetera. Okay, I want to understand customer perspective. I go to 12 cents, and there are 20 expert calls, most of them with customs. I got no clue which one was a good call, which one was an average call. And all of them are pretty long. 20 calls to read, that's a good amount of time. And usually when I read, I also take a lot of notes.

And it means that my reading time actually goes up. Figuring out where to focus, and this goes back to digging, stage is very, very important. Now, what I have, I pre-built, and this is important, Alpha Sense gives you some templates. You can use them, but I made those templates myself that will fit my investment style and my focus. And I have different templates for grid. I will have templates that is more targeted towards product. Another one will be more targeted towards company, strategy, competition, risk, etc. And you can build as many as you want. If your software as a service investor, you can build one for SARS, another one you can build for

industrials or for consumer, whatever you like. There's a lot of flexibility there. And greed looks exactly, think about it as a chessboard. There are horizontal lines and there are vertical lines. Horizontal lines, this is documents. By the way, documents can be any. It can be expert calls, you know, this is what I'm using as my example. It can be earnings calls.

It can be 10 case in Q's or proxies in your example, Andrew, in the sense of compensation, whatever like. And then columns will be questions. And I think you can put up to 12 questions. And you, what is real, and then you ask those questions, and you see what you get in the term. And by the way, that's another cool thing about AlphaSense. Okay, I'm not technologist. So if a dot I describe is actually incorrect, I apologize in advance.

But my understanding is that AlphaSense, because it's a specialized vertical AI tool, it makes the prompting by user less important, less critical to get a good output. Because I think at the back end, they kind of transform your lousy prompt into something a lot more thoughtful. Now, you can still try to be thoughtful, and I try to do that, but that's a big advantage, in my opinion, of using a specialized AI tool versus generic AI tool, a general AI tool, such as JadipT, or perplexity, or whatever else. So, and then I got this prompt, and it can be, what's custom value proposition?

what made you decide to buy this product? How long would the sales cycle? What other alternatives have you considered? Et cetera, et cetera, et cetera. And then you click it, takes a little bit of time. And then you got this grid with 20 expert calls horizontally and your 12 questions vertically. And then you can read very quickly 20 answers if they were given, because some of them maybe this did not come up, in one question just by moving in a vertical line.

You just do that. And then, number one, you got 20 points of view in just a few minutes. Remember, you and I spoke about doctors who may give different opinions about the same issue. Now you got the entire range of opinions within, I don't know, five minutes, tenets, whatever it takes for each read those. And more important, you can repeat this for all your 12th questions. But then I also figure out which expert or several of them give the most thoughtful answers. Yes. Or, alternatively, I can figure out which expert call gives me yellow flags or red flags.

In that case, I would go if I see two, let's say, out of 20 calls, I have three with red flags or yellow flags. I would go there. And then I would reduce myself from first page up to the last page including disclaimer and page numbers. And then I will, I may make a decision that given this yellow flags, I'm not comfortable making this investment, so I will kill my research ID. Alternatively, I will figure out three or four or five calls that are the best. And I'll go there. And then I may decide, reason the other 15 not important?

Or am I still, okay, knowing me, I will still read them, but it would be just to make sure that I didn't miss something because my thesis already has been confirmed. And that's a massive time boost and efficiency boost, driven by. AI. And the theme here for me, human, and I think I got this idea from Gary Kasparov, the 13th world champion, chess champion, and he coined it many years ago. And the premise is that human plus machine is more powerful than machine. And definitely more powerful than human. So that's the idea. Now, it may not always be the case. Who knows? We'll do another webinar in 10 years where my avatar will be talking to Andrew's avatar, all powered by AI tools.

And maybe I'm wrong on that premise. But that's how I approach it now. the other just if I can guess and the other interesting thing I found very similar to what you said is I like to ask a question about especially when I'm new to a company I like to ask a question in gen grid and then I just look through it and I see you know it labels kind of what what call the quotes are coming from and whatever call often one call will have the most quotes popping up I'll be like oh that call is the call most likely to answer the question that I am asking so I don't have to read 20 you know if I want something specific on the Salesforce, I don't have to read through if there's 20 transcripts, six of them until I find, oh, here's the one that really talks about salesports. It's just there.

And that might sound obvious, but oftentimes it's not obvious when you're like just looking at the overall or anything. I found that's been a great way to really speed up what I want to focus on in one thing. Let me ask. Go ahead. Can I talk about deep research a little bit feature? Yeah, please. Because I mentioned that in passing, but I think it's very much worth paying attention. So this is how I mostly use the deep research feature. Imagine I got an idea from somewhere. It may be a screen, it may be an Andrews podcast, yet another value podcast, please go and subscribe.

It can be a peer in my network who shared with me an interesting thesis, whatever the source is. I believe, so my old process would be go read 10K or go read several earnings calls and conference call presentations such as Morgan Stanley TMT or GP Morgan Health. care, whatever the case could be. And I slowly build a mosaic in my head. And it's at that point, even after reading those five, eight calls, it's far from perfect. Because I'm trying to really put different pieces into their places. Who is the customer base? What's the segmentation? What's the pricing? It's slow. Plus corporate history, et cetera. Now, I also believe,

and this is a second input for what I'm going to say as a conclusion is that Think about this as reading books. If you read a book first and then you reread it three months later, you will probably get a lot deeper understanding of more intricate and complex concepts second time when you did the first time. I believe same applies to reading investment materials. If my mind is not prepared to absorb a lot of information and immediately put it into a lot of right places,

and the right places here is the key, I will probably create a little bit mass in my head and it will take me more time to sort it up. But how can I apply that concept of reading book first and then reading it three months later? Or a better analogy would be this. You got a great book recommendation.

You go, I would go and listen to a podcast with the author for an hour, get the key concepts, and say, okay, my mind is prepared. And then I will go and read the entire. And my level of comprehension and retention will be a lot higher. Same with here in investing, what I'm trying to replicate. I have a prompt.

I have a few prompts. I will use for deep research feature. And it's a pretty long prompt for only five pages. And I will ask AlfaSan's deep research to return me a pretty detailed output, which will cover a lot of my questions. And then I will sit down and usually, print it out because that's how I like reading. I sit down in my reading chair, get a pencil, and go through that, highlighting, writing something on the margins, put in stars,

Slamish remarks, etc. It's probably usual output. It's 30, 40 pages, would be my guess. Similarly, it will have great sources, all references to expert calls, or earnings calls, and then what Andrews said, then you can read those that most frequently cited. But after I read those 30 or 40 pages, my mind is prepared. It's an equivalent of listen and show a podcast with an author for an hour before reading the entire 300 300 page book. And then I will go and with prepared mind, I will start reading all those primary documents or I will start with the most important ones.

That's how I use deep research. Now, I also want to mention the new AI feature that I think just got shipped. And I have not even used it yet, but I'm very curious to use it. I think it's AI generated export calls with experts. So it's AI asking questions. So I haven't got a chance to test those. It's got released very, very recently. So with the earning season happening right now, I didn't get a chance to try it.

But I'm really curious. Well, that actually brings me. I want to be cognizant in time because it's an Alphicent's webinar. It's not my podcast where we can wrap for an hour. But that does bring me nicely to what I thought was going to be my last question. Maybe we'll make this the second to last question. Look, in the same way, Bloomberg was, if anyone's had a Bloomberg, they're always releasing a feature. and everyone knows they only use like 5% of the Bloomberg features.

Alphacin's releasing features really quickly. I didn't even know about this expert AI transcripting. And I use Alphacin's pretty, sorry, this AI talking to AI transcript. Maybe I haven't seen it. Maybe I wasn't on the beta. I don't know. But how do you, what have you found the best way to keep up with new tools? And look, with AI tools, many of them are much different than tools we've ever used before.

So you get this new tool and you might think, oh, you know, that's free. I don't know. And it might be the most powerful tool ever really. So how are you keeping up with, you can do AI broadly if you want, but I'd prefer just because this is Alphacin's particular, all the new features that they continuously roll out? 90 or maybe even 95% of what I know how to use AlperSense, especially on the new features and new use cases.

I've learned from account manager of Carcan Capital, who is responsible for our account and he's incredibly helpful. Okay, Amar, Amar Kapelan, shouting out to you. Thank you so much for teaching everything. apologize for asking a bunch of dumb questions. So thank you for your patience. I've learned from my account manager. I will ask, oh, I have this feature is released. Would you show me how to use it? And also, because I've been working with Amar for a number of years, I think he got to know my investment style and what I do and what I don't want to do reasonably well. So he will point

out, I think he will like this use case for this feature. I'm like, oh, that's great. I do. That's So that's number one. Number two, sometimes I will ask Amar to spend 30 minutes with me on Zoom and just do a regular catch-up call maybe every six months, maybe every eight months. And I will be asking, like, hey, do you have any new things that you change or improved or added or something? Could you show me? So that's another way for me to get up to speed and know what's changing there.

So that's second. For example, Amar showed me how to use the grid and different use cases for export calls or for earnings calls and another cool feature for grid. you can, for example, let's say you cover 20 consumer good companies and you're trying to figure out what they spoke about, macro consumer confidence. Yeah, yeah. Right? You can pull it out into the grid.

I don't do it as much because I'm not necessarily like the industry specialist, but it's another great use case. I have found it's real, because look, every company when they pull guidance or they miss guidance, or they reduce guidance, let's say, what's the most common excuse? Consumer, the consumer soft. And I have found it really, really. good. You read it and, you know, most people do follow-up calls with the management team, not all, but most people do follow-up calls with management team 24 hours, maybe 12 hours,

maybe 12 minutes after the earnings call ends. And I found it so useful to be like, hey, this company said the consumer was soft during the quarter. What did their three, here's X, Y, Z, here's their three peers. What did they say? And then you get on the call with them and you say, hey, you guys said it was soft. You know, X, Y, and Z over there, all their results were better than yours. They said the consumer's strong. They said trends were so. What is it about your company that the consumer is soft. Are you guys just using an excuse? Is there something about your specific consumer?

And I found it's just so good. And again, that's something you can do on your own. But if you want to do that fast, you can't do that fast. It takes a lot of time and it's great summary. And then again, if you want to dive into it, you can go and say, okay, X, Y, and Z, this is what the Gen Gurd said. Let me go dive in and see specifically what they said. Last thing, again, we're running out of time.

So I want to ask, you talk to your account manager a lot. You use Alphicin's a lot. What is something I use OfficeSense a lot? and I know that I'm not using all their products properly. What is one thing that you're getting a lot of value out of Alphacense that you think maybe the average user underutilizes, doesn't realize out there or anything? What's one Alphson's tool that you think would recommend for that?

I don't necessarily know what a typical user may or may not be doing. So my best guess, would be this. Over the years, I've spoken with a number of product managers who are responsible for building specific features. And now I'm talking about broad features like notebook product manager or some other, like broad, broad features, categories, features, not small ones. And I've spoken with a number of them over the years.

And I think it's also a great way to learn about the potential use cases and potential very powerful use cases, which may not be obvious to a user right away from actually the people who were running the entire process, probably from ideating to building a prototype, to testing, to QA, to quality assurance, to shipping to users. that's probably the most knowledgeable planet on the person about that feature. So that's pretty cool. And also, and I'm hoping that it was also a way that I was useful to those people who generously shared their time, at least somewhat, at least a little bit, because it's also a way to get customers' voice. And sometimes you may say, like, oh, do you think you can add this thing, this wrinkle? It will be really, really cool. And look, over the years, probably some of those thoughts from customers like me got implemented. I'm sure some thoughts from me

maybe choose specific to my style and they're not relevant for many others and they probably will be ignored and it's totally fine but some probably I hope would get into the program because few users like me would speak up about those things. So it's also, I hope I contribute to it a little bit

and not just wasted people's time for a very, very busy with building the product. But that's probably my best answer. I'm not sure whether many other users of AlphaSense platform. Is this a satellite build app? No, I think that's great. I certainly am not reaching out to the product ministry.

So, okay, anyway, I think we've run for a little bit over an hour, so I think we're really breaching the limits of what the Alpha Sense webinar platform can handle. Arndham Foken from Caricon Capital, I mean, both of us are power users, both of us are happy users. Thanks for hopping on this podcast and discussing all things. AI, expert calls, Alpha Sense, not AlphaSense, everything. It's really fun. And we will have to chat soon. Okay, talk so.

Bye, Andrew. Everybody. A quick disclaimer. this podcast should be considered an investment advice. Guests or the host may have positions in any of the stocks mentioned during this podcast. Please do your own work and consult a financial advisor. Thanks.