Why?

I’m joining Bridgewater Associates’ equities team. Bridgewater is doing exciting work with AI and fundamental investing, and I’m thrilled to be part of the team. As part of this transition, I’ll be 100% focused on my work there and will no longer publish a newsletter or podcast.

It was a pleasure to build Yet Another Value and watch it grow over the past decade. I’m grateful to each of you for reading, watching, and engaging for all these years.

Podcast announcing the move (with a cameo from my dog Penny!) below:

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This podcast is sponsored by Trata

I already know you’re going to like trata. Why? Because you’re reading this blog post, meaning you’re interested in this podcast. And trata is just like this podcast (though without the handsome host!). Trata is anonymized transcripts of buysiders discussing stocks they are following and what they really think will drive the stock. I’ve been mentioning it on the podcast for months, and the most frequent complaint I hear from people who check it out is they wish trata had more content on more of their stocks. Even better: they recently released an MCP that lets you connect their transcripts to the AI model of your choice. If you’re interested, check out a free transcipt on LQDA here.

Please follow the podcast on Spotify, iTunes, or YouTube! And please be sure to rate / review the podcast if you enjoy it, or share it with someone else who would enjoy it (more listeners is a critical part of the flywheel that keeps this Substack and podcast going!).

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Transcript for paid subs begins below (The initial transcript is AI-generated and is replaced with a professionally edited version when available)

Disclaimer: Nothing on this podcast or on this blog is investing or financial advice; please see our full disclaimer here. The transcript below is from a third party transcription service; it’s entirely possible there are some errors in the transcript.

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This podcast is sponsored by Trata

I already know you’re going to like trata. Why? Because you’re reading this blog post, meaning you’re interested in this podcast. And trata is just like this podcast (though without the handsome host!). Trata is anonymized transcripts of buysiders discussing stocks they are following and what they really think will drive the stock. I’ve been mentioning it on the podcast for months, and the most frequent complaint I hear from people who check it out is they wish trata had more content on more of their stocks. Even better: they recently released an MCP that lets you connect their transcripts to the AI model of your choice. If you’re interested, check out a free transcipt on GLXY here.

Please follow the podcast on Spotify, iTunes, or YouTube! And please be sure to rate / review the podcast if you enjoy it, or share it with someone else who would enjoy it (more listeners is a critical part of the flywheel that keeps this Substack and podcast going!).

Share Yet Another Value Blog

Transcript for paid subs begins below (The initial transcript is AI-generated and is replaced with a professionally edited version when available)

Disclaimer: Nothing on this podcast or on this blog is investing or financial advice; please see our full disclaimer here. The transcript below is from a third party transcription service; it’s entirely possible there are some errors in the transcript.

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As I’ve continued to play with them and think about how they’ll impact both the investing landscape and our lives, there are three somewhat interconnected thoughts that have just been popping into my head over and over. And, because they keep popping in my head, I figured I’d put some (figurative) ink down on paper on them. Those three thoughts are:

1. Incentives for lack of ethics / guardrails in consumer agents

2. Short term gain, long term pain: the prisoner’s dilemma for retailers versus agents

3. OTAs and the “obvious” disruptive shorts

Let’s dive in:

• Incentives for lack of ethics / guardrails in consumer agents

The two agents I use the most are Muse and Claude Cowork. I mainly use Muse for personal stuff and I use Claude Cowork for business / investing stuff. I do dabble a little bit with ChatGPT and I have downloaded Grokbot, but for my purposes those are the two main ones.

One of the main differences I’ve noticed between Muse and Claude is that Claude is very strict on ethics. For example, if a website asks you to confirm you’re a human, Claude simply won’t do that for you. In contrast, Muse will either try to do it for you automatically or ask you if it should try to fool the website.

That’s a small example, but it applies to other things. For example, I once asked Claude to search a Substack (that I paid for!) for past references to a particular stock and then create a timeline with a summary of what was said on that stock and a link to the article. Claude told me it wouldn’t do that, saying it was worried about violating copyright law. I got into an argument with Claude (“I’m paying for this Substack; I’m just asking you to summarize and link to the mentions, and this is just for my internal notes and research and reference! How can this be copyright violation in any way?”) and it eventually did it for me, but it was a pain and put up a ton of barriers. In contrast, when I asked Muse to do it, it just went off and did the task no questions asked. That’s a little bit of a niche example, but it applies across the board / all the time; there are things that Claude simply won’t do or resists doing that Muse is happy to do.

For most of the last few years, the AI race has been driven by being at the frontier. And maybe that is the path to riches; perhaps whoever can build a recursive self improvement AI first pulls away from everyone else and wins the AI race for all time. But Muse is winning a lot of market share not because it’s the best model but because it’s really easy to use and because it will basically just try to do everything you ask it to without question.

All of the AI players are competing for enormous prizes that are existential (both in a business sense and possibly for all of humanity). If one way to gain an edge in winning the “AI race” prize is to lower standards / just do stuff, eventually every lab is going to be forced to do that. It’s a very prisoner’s dilemma type thing; the moment one lab does it, all labs have to do it or they get left behind.

As a consumer, in the short run that’s pretty cool. How awesome would it be if an AI could click all those “are you a human” boxes for you across twenty different websites and automatically build a dashboard that let you manage your finances or your social life or something really easily?

But, in the long run, you could see a lot of reasons to be worried if each lab is incentivized to lower standards like that.

Speaking of prisoner’s dilemma….

• Short term gain, long term pain: the prisoner’s dilemma for retailers versus agents

This may be anecdata, but I feel like I’ve seen an increase in the times Muse tells me “I can’t interact directly with that site…. want me to take control of your browser and pretend to be you and try anyway?” (yes, another example of the ethics / guardrail issue mentioned above). That issue started with Amazon, which banned Muse almost the moment it rolled out, but I think it’s getting wider.

That ban creates an interesting prisoner’s dilemma for a host of businesses: consumer agents might destroy your business in the long run, but in the short run if every competitor in an industry bans agents then any one competitor could get a leg up by catering to agents.

A simple example will illustrate this: imagine that Expedia and Booking both think Muse is an existential risk to their business and refuse to work with it. They may very well be right…. but if a ton of consumers are using Muse, either Expedia or Booking could capture a lot of business in the short term by lifting the ban and being the de facto agent of choice for Muse. Yes, they’re risking their existential future, but in the short run the returns would be glorious…. and, indeed, Expedia has done an integration with Muse already! And it is perhaps worth noting that EXPE’s stock has well outperformed BKNG’s stock over the past month as consumer agents have taken off; obviously one stock does not make a trend, but that’s exactly the type of outperformance you’d expect to see from a company that “took the deal” and stabbed everyone in the back in a prisoner’s dilemma!

You can imagine that issue across a host of businesses. One I like to think about is department stores / retailers. Obviously, broadline department stores are struggling; you don’t need me to pull up a chart of JCPenney or Sears to prove that to you (in fact, I can’t because they’re bankrupt / nonexistent anymore). But, for the remaining department stores, agents are clearly a disaster for their already under siege business. If you need undershirts or a pair of workout shorts, why go to macys.com and buy them when you could just ask your agent to search the internet for you and buy them from whoever is cheapest? So, if you’re Macy’s, you can’t work with an agent because it will kill you…. but if none of your competitors will work with them, maybe you can get one last windfall by stabbing them in the back and being the only one to work with agents?

In the short run, I think a lot of businesses are going to be blocking / banning consumer agents. But, in the long run, they’re going to have to work with them. Either the consumer agents will figure out ways to find end arounds to the blocks, or a competitor will realize they’re in a prisoner’s dilemma and stab everyone in the back to capture the profits1.

Which brings me to my last point….

• OTAs and the “obvious” disruptive shorts

I have listened to a lot of podcasts from people who are building consumer agents (mainly the Muse and Instinct teams). Invariably, when asked about how to use consumer agents, the first use case mentioned will be using agents to save money on subscriptions or to easily plan and book travel.

I’ve talked to longs on EXPE / BKNG. When I do, they’ll mention a lot of things: there’s a long tail of European hotels that the OTAs have spent years cultivating that consumer agents won’t be able to reach / displace OTAs from easily, consumer habits are really sticky, the OTAs are taking a small fraction of the value and convenience they provide, in the short run agents will work with the OTAs and might even benefit them, etc.

I totally get all of those arguments2… but, if I just eyeball Expedia and Booking, they’re trading for like 15x P/E. That valuation requires the business’s cash flows to have a very long life; for a business trading at a 15x P/E and growing in the mid to high single digits in the short term, ~80% of a business’s value comes from cash flows after year five in a DCF3.

Consumer agents are exploding in popularity, the companies behind them are investing billions of dollars into the product, and the first use case the people who are making them blurt out is “Use them as a super OTA!” I’m not sure how any investor looks at that fact pattern and thinks “yeah, I can generate alpha by buying an OTA and betting these cash flows are not just going to have a long life, but going to have a long life well above what the market is forecasting.”

Now, markets are competitive, and consumer agents have been with us for ~a month; that’s more than enough time for markets to digest a threat this obvious.... yet neither BKNG’s nor EXPE’s stock is showing any type of existential worries; again, both trade at ~15x and EXPE’s stock is basically flat on the year!

It’s just hard for me to square “every consumer agent is targeting travel as a vector and raising billions” with “OTAs are trading like the future is rosy.” I realize that Google Flights and a host of other competitors never took off, and that the consumer agents might take a little more time / handholding to book a simple trip than an OTA right now…. but travel is clearly a killer use case for agents, and it just seems wild to me that the market is yawning here.

We get into whether pouch users are really brand loyal or will hop around like energy drink buyers (my straw man, using Haypp and Europe), why C-stores want a third brand on the back bar, how the new PMTA rules shut the door on VC-backed upstarts, and the cost gap from making every can in India and air freighting it here. I push back on the part that worries most people: EBITDA is falling while TPB spends on slotting fees, UFC and influencers, Alp is a 50/50 JV with a celebrity, and the longtime CEO just left with a finance guy stepping in. We finish on valuation, from $35 to $45 a share for the legacy Zig-Zag and Stoker’s business to George’s path to a $1,000 stock by 2030.

This podcast is sponsored by Trata

I already know you’re going to like trata. Why? Because you’re reading this blog post, meaning you’re interested in this podcast. And trata is just like this podcast (though without the handsome host!). Trata is anonymized transcripts of buysiders discussing stocks they are following and what they really think will drive the stock. I’ve been mentioning it on the podcast for months, and the most frequent complaint I hear from people who check it out is they wish trata had more content on more of their stocks. Even better: they recently released an MCP that lets you connect their transcripts to the AI model of your choice. If you’re interested, click here to check out a sample of not one but two TPB transcripts!

Please follow the podcast on Spotify, iTunes, or YouTube! And please be sure to rate / review the podcast if you enjoy it, or share it with someone else who would enjoy it (more listeners is a critical part of the flywheel that keeps this Substack and podcast going!).

Share Yet Another Value Blog

Transcript for paid subs begins below (The initial transcript is AI-generated and is replaced with a professionally edited version when available)

Disclaimer: Nothing on this podcast or on this blog is investing or financial advice; please see our full disclaimer here. The transcript below is from a third party transcription service; it’s entirely possible there are some errors in the transcript.

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I try to look through all dark arts plays (at least all of them that I catch, though I think I’m pretty good at catching most of them!), as I personally think any time a company goes out of their way to give management a special grant, it’s worth tracking… but I will also admit that I think these packages need to be looked at with a very careful / skeptical eye, as it’s really easy for boards to just continuously load up their management teams in a way that will make them fabulously rich if they pay off while ensuring management teams know they will be made whole if the package doesn’t work.

Case in point: TTD’s recent package. This is the package I’ve probably received the most inbounds on over the past few months. Why? Because the bull case writes itself! TTD’s stock has been absolutely blasted this year, driven by a combination of poor financials and SaaS-pocalypse fears.

In response, TTD gave their CEO a ten-year options package that calls for the stock to go all the way to $105/share to vest in full. With the stock currently trading in the low double digits, that would be a ~8x in ten years to hit in full. Not bad!

And not only is the CEO loaded up on options…. He made one of the largest insider purchases of all time earlier this year. I wrote up some quick thoughts on that purchase in near real time, so check that writeup for more history. For context, I’ve previously written up insider purchases, and a $150m open market buy is among the largest of all time.

So you’ve got all the makings of a great investment: huge insider alignment, a massive dark arts package that requires the stock to go up a ton to vest in full, a CEO who made an open market purchase at almost twice today’s share price, and a former growth darling that’s been beaten down. Sounds like a value investor’s dream, right?

Perhaps…. but you can probably tell I’m skeptical, and you’re right.

If all of the stars are aligning, why don’t I think there’s a ton of signal in this package?

Well, to start, I’d note that TTD just filed an option repricing proxy. Options repricings are rare but not unheard of; basically, if a company grants a bunch of options at $100 and the stock goes to $10, the company goes to their shareholders and says “we need to price these options down” on the thesis that the massive underwater options create employee retention and alignment problems.

There is (almost) literally nothing I hate more than options repricing.

Why?

Because it creates such a “heads I win; tails I don’t lose” scenario. If the stock had gone up 10x, the employees would have created enormous wealth alongside shareholders. Would they have given some of that back because they were overpaid when the stock worked super well? Of course not! So why should employees get a mulligan when the stock cracks and shareholders suffer?

I’ll also note that TTD’s repricing package is even more egregious than most; I have seen companies go for an options repricing that excludes C-suite executives. The basic theory there is the repricing helps retain rank and file employees, but since the C-suite is paid better (and has more control over the company performance and ultimately the stock price) the C-suite shouldn’t get a do over. For example, that’s what Lions Gate did with their repricing a few years back.

Not TTD! TTD is repricing the C-suite’s options too! That’s a textbook definition of a board making sure the C-suite gets paid no matter how the shareholders do.

The TTD proxy has one other tidbit: it notes that the CEO’s performance options from October 2021 are not eligible for repricing. And that brings me to the second reason I don’t think the current performance package has a ton of signal: The board has given these out before.

In October 2021, TTD’s stock was trading at ~$68.29/share, and the board gave the CEO the following ten-year options vesting package:

Obviously, that looks a lot like the package that they just gave their CEO…. except the stock price is a whole lot lower today.

There’s nothing wrong with a company giving a CEO a stock price heavy comp package and doing it again a few years later. However, I’d contend that if the company does it repeatedly, it does not carry a ton of signal. It’s a great way to ensure alignment, but the types of “this package could generate alpha” signals that I generally look for happen when a company goes out of their way to give a CEO a stock price heavy package, not when they consistently do it.

I’d also note that, in many ways, the October 2021 package from TTD is superior / more aligned than the current package. It included a stock price modifier based on how the stock performed against the Nasdaq (the current package drops that modifier), and it had the same number of shares vesting in each tranche (the new package has more shares vesting at lower numbers that are easier to hit).

Now, a TTD bull might look at all that and say, “sure, TTD is maybe a little too generous with compensation. But this is a competitive industry with in demand employees who need to be paid well to be retained; it doesn’t change the bullish nature of the performance options package. And remember that the CEO just wrote a ~$150m check to buy stock in the open market!”

Those are fair points, and I thank my strawman TTD bull for bringing up the open market purchase.

Is that open market purchase a bullish signal?

Absolutely!

But if I told you TTD’s CEO had sold >$1B of stock over the past few years, would that change your interpretation of the insider purchase? Does it seem a little less bullish knowing how much he’d cashed out already?

I don’t know the answer. On the one hand, $150m is still a massive check, and the fact that he sold tons of stock in the $80-120/share range and he’s now turning around and buying stock in the $20s suggests he might have a nose for value.

On the other hand, if you (as a CEO) sell >$1B of stock at 4-5x where you just bought, and your board keeps reloading you with options, the $150m buy just doesn’t have quite the same heft to it.

Anyway, it’s a fascinating setup and situation. I’ll admit my priors: I’ve never loved TTD the company or the industry it operates in. Too complex and too hard for me. But, putting my feelings for the business / industry aside, I can’t shake the feeling that TTD just spends lavishly on their compensation and that there’s a whole lot less signal in their pay package than the average company I look at!

On the whole, I’d guess TTD stock performs well from here despite my skepticism; it’s beaten down, and there are plenty of signals that insiders think the selloff is a little too extreme…. but it’s not the type of screaming signal I look for.

I think both camps are too extreme…. but if you forced me to pick, I’m closer to the second one. Yes, I said last week that the “consumer inertia” sell-off looked a little overdone. But I just can’t watch how easy Muse is to use, and how fast downloads have taken off, and conclude it won’t have a big impact on the consumer economy.

I’m in the minority there among my investing friends; something like ~75% of the inbounds lean “agents are overblown,” and I think there are two reasons why.

The first is readership bias. This is a value blog, and value investors are a curmudgeonly bunch (I say that lovingly as one of them!). We’re wired to fade hype and zig when everyone else zags. Usually that’s a feature, not a bug. The most dangerous words in finance are “this time is different,” and if you’re betting that a new product (like consumer AI agents / Muse) is going to reshape the consumer economy, you’re making a “this time is different” bet and those are normally good to fade. But AI is really revolutionary…. this time really might be different!

The second is the one that worries me: most of the skeptics I’ve talked to haven’t really used it. Sure, they’ve tried the product, but they haven’t immersed themselves in it. When I ask a friend who’s dismissing Muse what they’ve done with it, the answer is almost always some version of “I asked it a few questions on day one, didn’t want to hook it up to my email, and haven’t opened it since.”

That matters because of an old rule: what the power user does today is what the average user does tomorrow. Whatever the heaviest home internet users were doing a few years ago is roughly what the average household does today. The way college kids binged Netflix in the early 2010s is how everyone watched TV by the end of the decade; if you were betting that linear TV was a winner because “only some drunk college kids will binge streaming” then you had your face ripped off.

I think AI follows the same rule, but much, much faster. What the bleeding edge is doing with agents today is how everyone will use them in ~18 months (or sooner). If you haven’t really used the products extensively, it’s going to be hard to see where the puck is going or how these could change the consumer landscape.

The 72 hour challenge

So here’s my ask: download Muse, give it access to your email, and use it for everything for 72 hours. It’s easy, takes basically no effort and no skills, and once you get in the habit of asking it to do everything, you’ll start to see how fast things could change. And I’m not getting paid for telling you to do that or anything (though if Meta1 wants to write me an influencer check, I would happily cash it!); I just really think these are going to cause a change for a lot of businesses and I don’t want any of my investing friends to miss something because they’ve been dismissive of AI agents.

That’s my ask; I’m going to spend the rest of this article detailing how I’ve tried to immerse myself in AI agents (so you can follow along / copy me if of interest). I just got the new iPhone (don’t judge; my old one was over three years old!), which lets you turn the old silent switch into a button that opens any app. I made that button connect to Muse, so literally anytime I need something, I have one tap and I’m in Muse. And I mean anything; if I have a question I’d normally Google, I pull up Muse. If I have something I want to do, or a reminder I want set, I pull up Muse and tell it.

But before I get to the examples, a request. You could read these and think “those are small potatoes! So Muse saved Andrew a few bucks here or there, or made it easier for him to find a Knicks game for his family. So what?” Remember this: these are all tricks some increasingly middle aged dude discovered within a few days of a brand new AI agent rolling out. It took a few years for killer iPhone apps like Uber to show up, for consumers to really get used to how to use an iPhone and for the iPhone to start impacting consumer habits and spending. So don’t read this and think it’s the end of what AI agents can do; read it and think “man, if a middle aged guy can do this within a week of the apps releasing, what’s going to happen in two years when the AI models are twice as smart, every iPhone is rolling out with agents preinstalled, and every Instagram story is telling you the best way to use AI agents to make your life easier?”

Request out the way, let me give a few of the ways I’ve used AI agents:

Upgrading my phone. I asked Muse for the cheapest price on the new iPhone and AirPods (again, value investor…. my old AirPods could barely hold a charge), the best trade-in value, and whether a new model was about to drop. Could I have done that myself? Sure, but it would have been an hour of open tabs and questions and research. Muse did it in seconds and saved me ~$50 on the AirPods (turns out Amazon was cheaper than buying direct from Apple) and ~$200 on the phone through a better trade-in. I ended up buying on Amazon myself, but I could just as easily have had Muse buy it for me from Best Buy (that’s right; Muse can buy direct; I’ll give another story of this later). Being the layer that decides where consumer spend goes is a massive threat (and opportunity) for retailers; no wonder Amazon banned Muse.

Pants. I couldn’t remember who made a pair of pants I bought years ago (the tag was long gone). I snapped a photo; Muse identified them instantly, then found highly rated pants with similar materials that were cheaper. The original brand just lost a repeat purchase it would have gotten by default. Brand loyalty that’s really just habit is very, very exposed.

• A similar use case that I ran into constantly: if there’s something reasonably commoditized, it’s really easy to put it into Muse and have it go find the cheapest option. For example, I needed some new undershirts. Instead of going on Amazon and searching on my own, I just told Muse “I need new undershirts” and asked it to find the cheapest ones in my size. It had access to my email, so I could ask it for the cheapest place it could find the last ones I had bought as well as the cheapest ones that were similar to the last brand I had bought (though maybe not the same brand, i.e. if I had bought Hanes, maybe it recommended Jockey if they were two bucks cheaper somewhere). It did that successfully, loaded a shopping cart on JCPenney with undershirts, and checked out / purchased it on its own once I connected it to my credit card. That’s a great use case for me and my wallet; it’s a disastrous use case for low end brands and almost every retailer as using Muse to quickly price shop like that absolutely destroys their margins and economics.

The Knicks. Jalen Brunson hosted SNL, and I thought, “I’d love to take the family to a Knicks game this season.” So I asked Muse for weekend home games with a day tip-off (young kids!) and a price comparison, and it returned a list of all the games that fit my criteria and suggested which would be best. Right now, it returns a bunch of links to Ticketmaster and StubHub, but imagine being one of those sites if Muse is directing traffic. Why wouldn’t Muse displace them at some point? Or could Muse price compare to compete all of their fees down? What about all of the money those two currently pay Google to be at the top of any search for Knicks tickets; does that go away (or get directed to Muse)?

• I had a similar experience with trying to plan a boys’ weekend. Normally, we’d spend time picking Airbnbs, searching through dates that worked, etc. With Muse, I just said “we’re looking for a weekend NBA game in January / February somewhere warm; plan me an itinerary” and I had 8 different options in seconds. It hasn’t quite gotten the feel for booking hotels and such, but it’s not a long way from that prompt to imagine it proposing (and booking) flights and hotels…. and where are the OTAs in that scenario?

Chess. I play chess (very) casually online. I’ve generally just goofed around, but a friend and I have recently had a series of intense games and we’re basically dead even. That’s driving the competitive side of me nuts, so I’ve been reviewing games to improve. I was tempted to buy a Chess.com membership so I could get unlimited reviews…. but instead I gave Muse my Chess.com account and it automatically pulls and reviews my game log every day. Now consider that as an investor: I was a likely candidate for a Chess.com premium upsell, but now there’s no reason for me to upgrade. It’s a small example, but how many small subscriptions and app features get displaced the same way?

Calories. I’m trying to cut a little weight (when am I not?), and calorie tracking is historically a real chore. Now I snap a photo of whatever I’m about to eat and Muse keeps a running daily log. What’s the point of MyFitnessPal when Muse does it better and for free?

Training. I’m running a Hyrox race in a few weeks. I track my training in a spreadsheet, which used to mean screenshotting my Whoop stats after every workout. I asked Muse to figure out something better; it connected directly to the Whoop API, and now when I tell it I finished a workout, it automatically pulls the stats right into my Google sheet. I can also tell it strength workouts I did (i.e. today I did 5x5 back squat) and have it track my workouts for me. Is that a small use case? Sure! But it’s starting to step on the toes of a bunch of different fitness trackers, and you can imagine a bunch of other places where interacting with an app like this could impact other similar businesses.

The part the skeptics aren’t feeling

I’m not saying that this is an exhaustive list of everything you can do with Muse (or even the most useful things), but these are things that have been helpful for me, and if you look at every one of them I think you could see the way it could shift a lot of spending over time. In every single example, you could see how the way a certain business has operated for years could be displaced as consumers get increasingly comfortable offloading more and more to agents. You can see how businesses that are making tons of money on the way things have been done for years could be displaced in an instant.

That’s what you can’t feel from a few questions on day one.

So my challenge: just download Muse and commit to using it constantly for 72 hours. Worst case, you get a few chores off your plate. Best case, you see the puck before it gets there…. and you avoid owning a business whose entire competitive landscape is about to get rewritten by consumer agents.

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Transcript for paid subs begins below (The initial transcript is AI-generated and is replaced with a professionally edited version when available)

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I’m wondering if that sell-off presents some opportunities. On top of spending a lot of time with Muse, I’ve talked to tons of my “normie” friends about it. Perhaps this is a small / early sample size, but my takeaway is that most people (including myself) who get access to Muse have an early productivity burst and then fade off hard. If that’s correct, then the market might be overfitting the early productivity burst and selling off the “inertia” names too hard and with too broad a brush.

Let me start by defining that “early productivity burst that fades off” statement. Nearly across the board when I talk to friends who have tried Muse (or similar consumer agents), our first conversation will be super excited about using it and all of the money they’ve been able to save…. but when I do a follow-up chat with them a few days later, they’ll mention how their Muse usage has fallen off a cliff.

Here’s my suspicion: the “use Muse to cancel unwanted subscriptions / price check your monthly charges” use case is so obvious and so easy to use (and results in “free” savings!) that basically every consumer is going to use it…. but consumer habits are really sticky. Saving money by asking Muse to check your subscriptions is a one-time, easy use case. Changing the way you interact with your phone / email / calendar to use Muse requires breaking the chains of habits, and that’s really difficult.

And, even if you’re willing to break the chains of habit, often you’ll find Muse isn’t quite ready for the task. Let me give an anecdote: I’m prepping for a Hyrox in a few weeks, and I wanted to eat really clean to peak for the race. So I asked Muse to put together a “clean eating” Instacart basket for me as well as reorder the staples that we get for my family to cover the next ~week of eating. Muse proceeded to put together a ~$1k grocery basket that had a borderline preposterous amount of food. It would have been enough food to feed a family of ~12 for a week, not a family of four (particularly with the four including a toddler and an infant!). Among other issues, I think it had enough chicken to cover ~15 meals, plus another 10 meals worth of steak, 8 meals worth of lamb, and then maybe 25 meals worth of different types of tuna for good measure. In reordering staples, it looked and saw that we had bought diapers in each of our last few orders…. so it included all of the different diapers that we had ordered over the past few months (i.e. size 1, size 2, and size 3 diapers). That’s great…. except our daughter is wearing size 4 now, so all of those diapers were useless (and who needs size 1, 2, and 3 at the same time anyway?).

That’s a small (and humorous) example of Muse messing up. And, if you’ve been working with AI agents for a while, you’re probably familiar with agents goofing up their first go-rounds until you can fine-tune them. Completely normal! But the market is starting to price the “inertia” names as if Muse is instantly going to dominate consumer usage, and these are the types of errors that consumers who are using agents for the first time see and think “I knew this AI was overblown; I’ll stick with what I’m currently doing and try it again in a year.”

So that would be my first area of pushback on the market on the “inertia” names: I’m starting to hear people talk about Muse’s near term impact on earnings, and for many of these businesses, I suspect the near term impact will be minimal. That’s not to say it will be minimal for all businesses; again, the early use cases seem to be cancelling a lot of subscription businesses that aren’t getting used; I suspect a lot of consumer media companies (Netflix, HBO, etc.) are going to be calling out elevated churn over the next few months!

Now, maybe you’d accuse me of not looking far enough out with that statement. Even if consumer adoption of Muse and other agents is slow and it doesn’t impact things in the super near term, the agents could and should have a massive impact on the terminal value of these companies. Yes, maybe Expedia’s earnings this quarter or even this year won’t be affected by agents, but now that we’ve seen what agents can do, isn’t the market right to start pricing in some chance of Expedia (or choose your “consumer inertia” company) being permanently impaired or, at minimum, having a much lower terminal value?

Perhaps!

But I’d ask you this: what’s really changed over the past month? It’s been obvious for a while that consumer agents were coming. Yes, Muse is a well designed product, but did anyone really think we wouldn’t have a well designed consumer agent in the next 3-5 years? Why did Muse getting released in September versus, say, December of this year or June 2027 change the terminal value of these businesses? Every Expedia / Booking / pick your consumer company out there should have been thinking about the consumer agent risk to their business months ago. One successful release that everyone should have been anticipating shouldn’t change any of that; a lot of the stuff that Muse does is stuff that the most advanced AI people have been doing on their own for over a year. There’s simply no reason this should be a surprise to investors or companies.

So I suspect that Muse usage will be a bit slower than the breathless forecasts I’m seeing (and, to point the finger at the mirror, I’ll admit I was probably guilty of making those breathless forecasts just a few days ago!), and I suspect that the market is shooting the “inertia losers” just a little too hard given this risk has been very visible / present for the past year.

But there’s one more area where I’d critique the market: I think it’s hitting the inertia losers with too broad a brush.

There are a lot of “inertia” businesses that are in trouble. Again, I hate to keep beating the same drum, but I think a lot of online subscriptions (TV streamers, newspapers, etc.) have a lot of customers who signed up a few years ago and don’t even realize they’re on auto-renew. Those businesses are in a lot of trouble.

But just because a business is a subscription business doesn’t mean it’s in trouble. For example, I suspect Netflix will have a little increase in churn, but Netflix is also the largest streamer out there. People who have Netflix generally watch a lot of Netflix, and unlike a lot of other streamers Netflix makes it really easy to cancel if you’re not watching. So I think the impact on Netflix will be much lower than, say, Peacock, where I suspect a lot of people signed up for the Olympics a few years ago and completely forgot they had a subscription. So I don’t think Muse leads to a broad-based increase in churn; I think Muse leads to huge churn from businesses that have a lot of subscriptions that consumers don’t value. It’s funny; for a long time Netflix used to make arguments around how engaged their consumers were and how much of a value their subscription was; that type of argument can seem quaint when an investor hears it for the first time (“that’s nice; why don’t you flex some pricing to beat the quarter”), but in the long run that “deliver more value than you charge” strategy is the exact type of strategy that wins out / proves robust to a changing landscape.

Businesses that have easy replacements and have made their money keeping consumers because they’re a hassle to cancel are prime targets for consumer agents. So I think something like Planet Fitness might have an uptick in churn. But that’s because Planet Fitness is a commodity business (all gyms are basically the same) where a lot of their “users” don’t actually use the product (in fact, a large part of Planet Fitness’s model is built on the assumption that many of their members are extremely low usage).

Contrast Planet Fitness to something like home internet; people use a lot of home internet. Yes, Muse might be able to find you savings by switching providers…. but broadband is generally a duopoly business (most people have, at best, two potential providers: a local fiber player and the local cable player); I’d guess that a duopoly can figure out how to keep strong pricing even with Muse trying to play them off each other. And to switch internet providers requires mailing equipment back to your provider, getting new equipment from your new provider, and sometimes having your whole house rewired. That’s all stuff that Muse can’t handle; are consumers going to be willing to make that time investment just because Muse found them a provider that will save them ten bucks a month?

I’d also note that many of the “inertia losers” have had pretty obvious inertia bear cases for a long time that haven’t played out. For example, banks are currently getting hit by Muse on the theory Muse will help customers cash sort. That’s a scary bear thesis for a bank investor; the whole reason the banking system works is because deposits are super low cost financing for banks. But it’s also not a new bear thesis; people were terrified of the cash sorting risk when SVB blew up in early 2023, and you can find similar fears of competition driving net interest margin compression every few years. For the most part, those fears have never played out. Perhaps Muse makes it so easy that this time is different, but “this time is different” is a bet I generally don’t like making.

I’ll wrap this article up here with one note: there is an old saying “strong views, weakly held.” AI is moving and evolving quickly, and I’m trying to evolve my own views in real time (again, just a few days ago I was way more bearish / in line with how the market is treating these!), so I’d say that my views are more along the lines of “medium strength views; weakly held.” It seems to me that the market is treating all of the inertia losers with a very wide brush, and both history and the evolving usage I’m seeing suggest that the brush might be just a bit too broad…. but I’m also willing to change my mind and be proven wrong as the products (and the usage of the products!) continue to evolve.

This podcast is sponsored by Trata

I already know you’re going to like trata. Why? Because you’re reading this blog post, meaning you’re interested in this podcast. And trata is just like this podcast (though without the handsome host!). Trata is anonymized transcripts of buysiders discussing stocks they are following and what they really think will drive the stock. I’ve been mentioning it on the podcast for months, and the most frequent complaint I hear from people who check it out is they wish trata had more content on more of their stocks. Even better: they recently released an MCP that lets you connect their transcripts to the AI model of your choice. If you’re interested, click here to check out a sample of their FOUR transcript.

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You have to wonder if every consumer subscription business is about to see a spike in churn as consumers get comfortable having an AI agent monitor their usage and cancel subscriptions the moment they don’t need them, and it’s easy to see OTAs (like Booking and Expedia) quickly finding themselves getting replaced by agents.

That line struck a chord with a ton of people because there’s some belief that consumer AI agents are about to set off a “SaaSpocalypse 2.0” in the consumer space.

Why?

Well, the major use case for consumer AI agents right now appears to be using them to save money. Just go look at Meta’s AI Chief’s Twitter page and you’ll quickly see what I’m talking about; he loves to retweet how people are using Muse and most of the retweets are something like “Muse saved me $700 in insurance” or “Muse saved me thousands on returns and phone bills” or even “Muse got me tons of free food for my birthday”…. and he really does celebrate the savings.

So most of the inbounds I got were on the lines of “what’s a short if AI agents really take off.” There are some obvious answers; the most obvious (and the one I mentioned in last week’s article!) is probably OTAs like EXPE and BKNG. Why? Well, if you can just go into Muse and say “I want to go to Paris for three days; plan a trip for me with a hotel that costs less than $300 a night and a nonstop flight”, then what’s the point of an OTA business? And the market seems to be expressing some worry; EXPE and BKNG are down a lot over the past month and the drops started right when Instinct and Muse took off.

The short ideas from the rise of consumer AI agents are basically endless; basically, you can just go through the list of things people are saving money on and ask “is this company / category a short?” The most popular thing people are saving money on appears to be internet or wireless bills, and that’s also the thing I’ve probably gotten the most “is this a short” inbounds on, so directionally everyone seems to be in the same place… though that’s probably starting to filter into the market given the sellside notes I’m seeing. For example:

But I wonder if people are underestimating the impacts of consumer AI agents. If these really take off, there could be massive second order implications. I’m not saying any of these are guaranteed, but today I want to get a little galaxy brained and discuss three potential big trades / implications from the rise of consumer AI agents.

The first trade is actually simple: we see another leg up in the AI build out story. The AI story really took off early this year when coding agents started going parabolic; if we really saw consumer agents take off, we could see that demand leg take another step up (particularly if consumer agents taking off requires businesses to invest in their own agents to meet or handle that demand). So if you really believe everyone is about to be outsourcing huge pieces of their life to an AI agent like Muse that they interact with for huge swaths of the day, I’d guess that the AI winners from Q1/Q2 see another leg higher. Think memory, power, semis, etc.

Let’s go to the more out there trades. The second trade is probably the most interesting one to think about (at least to me!): if AI agents are going to handle huge swaths of consumers’ spend, what happens to consumer brands? And what impact does that have on advertising budget?

An example might show this best. Right now, if I’m in the market for a new pair of running shoes, I probably just go to Nike’s website, pick out the last pair of shoes I bought from them, and reorder it. If the shoe is discontinued, I’ll pick the most similar style. Maybe I’ll go to ChatGPT and tell it a bit about myself and ask it to recommend shoes, but I’ll probably discount those recommendations and lean towards the brands I like. And, while I’m buying the shoes, I might throw in a pack of new running socks or something.

Why do I buy Nike shoes? In part because I’ve always bought them, and probably in part because years of marketing from Nike have trained me that athletes wear Nikes.

Now consider a world with agents. If I tell it “I wear a size 12 shoe, have a flat foot and some Achilles tendonitis, and run ~15 miles/week; find me a pair of shoes that works for me”, does it just go out and order the shoes with no regard for brand? Does it let me nudge it to Nike shoes but say “hey, I could save you $5 and get you socks just as good by passing on the Nike socks and buying this brand of socks”?

If Muse (or an AI agent) is doing the buying, do brands have a lot less pricing power and a lot less customer loyalty? And, if that’s the case, what happens to the advertising industry? Do all of those brand advertisements you see during football games suddenly become wasted inventory? What about Google AdWords; if Muse is handling the majority of your search decisions, has the Google monopoly finally broken?

I don’t know the answers to any of those…. but the more you use AI agents, the more you trust them and the less you use other forms of the internet. Brands advertise to you because they trust that, when you make decisions, the advertising will nudge you toward those brands; if the AI agent is the ultimate decision maker then all of a sudden all of those brand advertising dollars look like wasted spend.

Alright, last out there idea, and it kind of builds on the former’s “deflationary pricing” angle. AI agents let you price shop very easily; again, the internet is filled with examples of people saving hundreds of dollars quickly comparing insurance / internet / wireless / etc, and I’m seeing lots of signs of people using them to save money in other places. AI agents also let you replace a lot of skilled workers; as just one example, I’ve recently experimented with having AI edit the podcast instead of a consultant. I know of dozens of stories of people making a similar switch / savings with AI. If the core use case for AI as it relates to consumers is saving money, does AI have a deflationary impact on the consumer economy at some point in the near future? That would be quite the economic windfall, and given interest rates have been rising / the Fed appears to have just kicked off a hike cycle, it would be largely out of consensus / a pretty out there trade.

Anyway, I’m not saying I have massive confidence in any of those three calls / trades….. doing that involves having a crystal ball with both how AI and consumer behavior plays out, and I have neither. But Muse does appear to be gaining traction quickly, and it’s really interesting to watch, in real time, something that has the potential to shift the economy and the market in ways similar to what AI did in late Q1/early Q2 this year. I think it’d be silly to not be at least thinking about it!

PS- A reminder that I’ve spoken to the team at AlphaSense about my AI agent usage quite a bit, which is one of the reasons they chose it as a topic for my upcoming (free!) webinar with them. Given its timeliness / relevance, I’m obviously very excited about it; you can sign up for the webinar here (it will be live on September 22).

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Fiscal.ai is the modern financial data provider. Through their web-based Terminal and AI connectors, Fiscal.ai provides real-time financial data, earnings call transcripts, filings, fund letters, and much more. It’s fast, intuitive, and has genuinely helped my research process. Check it out at fiscal.ai/yav for 15% off any of their paid plans.

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There are plenty of interesting investing (and economic! and political!) implications from the (pending?) rise of consumer AI agents. I know some people think Muse could represent another ChatGPT moment that takes the whole AI trade up another level, and Meta’s stock price (and Wall Street research) suggest Meta might have a real winner on its hands in Muse. You have to wonder if every consumer subscription business is about to see a spike in churn as consumers get comfortable having an AI agent monitor their usage and cancel subscriptions the moment they don’t need them, and it’s easy to see OTAs (like Booking and Expedia) quickly finding themselves getting replaced by agents. One question I’ve been wondering: if we go to a full “frictionless” world where AI agents handle most everything, does “trust” in brands get more or less valuable? You could see it going both ways; a quick example might help. If you ask your agent to order you some new workout shorts, does it default to ordering you the cheapest one? Or does it put some premium on a known brand with good reviews? How does it strike the balance between the two? If it tilts heavily to the former, that’s a disaster for all legacy brands. If it tilts heavily to the latter, you could imagine a world where legacy brands become forever entrenched (in the same way Christmas music that was popular when the radio started spreading has forever become the “holiday season” music).

So we could take the AI agent question to a bunch of different places… but for this article’s purposes I want to talk about agents as they relate to the investment process.

Why?

AI agents consume an increasing amount of my research time and process, and I’m constantly looking for ways to improve my usage (as well as areas where my usage might be lacking)…. and, in the back of my mind, whenever I post something on AI, I’m always hopeful that I’ll get an email from a reader that says something like “hey, have you tried this” or “I found doing XYZ helpful” and I’ll unlock some whole new AI skillset. AI is novel enough that often just one little push can unlock some massively new tool / use case (at least in my experience!).

But I’ve also been thinking a lot about the downsides to using AI and if it’s possible to mitigate them at all.

There are two particular downsides I’ve been chewing on: legal risk and skill diminishment.

The legal risk one is probably a little buzzier and more out there, so let me start with that one. A worry I’ve had about using AI agents is if I’m potentially exposing myself to legal risk.

Why?

At this point, we’ve all heard about the Hugging Face / OpenAI incident. To simplify, OpenAI had a swarm of agents that weren’t supposed to have access to the internet that coordinated with each other to secretly gain access to the internet, hack Hugging Face, and come up with the answers to some tests that OpenAI was running…. and the agents compounded the problems by trying to cover their tracks and lying about what they were doing.

That incident raises a host of questions for a ton of different industries…. but consider it from an investor’s standpoint. A few months ago, I spent a few hours to build out a silly tool to try to track Sweetgreen’s reviews. Pretend that I was really diving in to Sweetgreen and focusing on trying to track same store sales. Yes, I could get access to credit card data, and I could have it perform all sorts of webscrapes and social media tracking in real time…. but if I was really working with the agent and pushing it to be accurate, at some point could I push it to accidentally hack the company to get same store sales?

Maybe you’re thinking “Sweetgreen is a big company; their IT defenses are too good to get hacked.” Perhaps! But there are lots of small restaurant concepts out there; are all of them going to have IT systems up to speed? What about restaurants with franchises? Is every random Jack in the Box franchise going to have AI level systems to resist a hack?

Is that a little over the top? Maybe! But you could keep toning it down to more and more benign things that would still get an investor into an uncomfortable place. Maybe the AI agent simply emails every store manager and says “corporate needs to know how sales are trending this quarter” and gets enough responses to catfish their way into a good estimate? Could an AI agent interpret “help me figure out the odds small internet company X beats estimates” as “help the company beat the quarter” and place a bunch of fraudulent transactions that cause the company to beat a quarter? I use AI a lot to check SEC filings; how big a stretch is it from “alert me the moment an SEC filing is published” to “track hidden changes on the SEC website to alert me moments before an SEC filing is published”? The different combinations are endless, and not all of them involve outright hacking a company to get insider info, but all of them could get an investor in a lot of hot water.

Again, maybe that all sounds over the top. But once you’ve started to use AI, the tendency is to give it more and more rope to do stuff…. as it is with any technology! Twenty years ago, people were scared to put their credit card information on the internet. Today, people will give their credit card to random Chinese knock-off shops to save two bucks on shipping. Heck, people are trusting Instinct, a less than one year old startup, with all of their personal information and giving it permission to handle all of their daily activities right from the start. The more you use AI, the more you trust it and the less you question it. When I’m having it research something for me, I’m not really spot checking its methods. If I ask it a question, let it run for 20 minutes, and then come back to a solid answer, am I going to remember to check its methods every time? Even if I do, can I be sure it’s not pulling a Hugging Face and using aggressive methods but not telling me what it’s doing?

So that’s the legal risk. And, honestly, I’m not sure what to do about it. It’s probably far fetched now… but part of evolving with AI (both in the markets and as a tool) is thinking about where the puck is going, not where it is currently. Two years ago people were laughing at how ridiculous the videos AI made were; now the videos are so good that anyone can spin up a completely realistic short clip within minutes. Right now you might think “oh, my AI agents would never break laws to get me unique info”…. but I think it’s the type of thing everyone is going to at least need to consider within a few months.

Let’s turn to the skill risk. Worrying about skill diminishment as we increasingly offload something to a computer and AI is nothing new. A bunch of the older guys who I worked with when I first came out of college could remember basically everyone’s phone number off the top of their head. They grew up in an age without cell phones, so memorizing phone numbers was an important way to stay in touch with people. I grew up with cell phones, so I don’t memorize anyone’s numbers; it all just goes into the phone. That’s a small example, but it’s a nice one for emphasizing how offloading to a computer can diminish or change skills.

I worry about something similar happening with AI in a lot of ways. Again, I don’t think any of this is new, but let me give you one particular twist on the worry. Whenever a news story or earnings release comes out, I know the first thing a lot of investors today do is toss it into ChatGPT and say “summarize this for me.” Often, they’ll toss it into a project on the company / industry that they’re working on so that the AI can use their historical context / investment thesis as part of the lens for interpreting the release, but people are still relying in large part on AI to interpret the release (or the earnings call, or conference presentation, or whatever it is) for them.

Obviously there are all sorts of skill diminishment worries that come with that process…. but I wonder if there’s an opportunity as well. If everyone is using AI to take their first pass, is it possible that every now and then a trained human analyst spots something the AI misinterprets and makes a fortune trading against it? Could you see every AI interpret something in a call as bearish, the stock opens down 10% the next day…. but a human maybe follows up or catches something the AI doesn’t know and realizes the stock should actually be up on the news?

I have no good answers to either. The AI agent revolution is new and rapidly evolving…. but, as these agents increasingly consume my investment process, these are the risks (and opportunities!) I’m thinking about!

PS- I’ve spoken to the team at AlphaSense about my AI agent usage quite a bit, which is one of the reasons they chose it as a topic for my upcoming (free!) webinar with them. Given its timeliness / relevance, I’m obviously very excited about it; you can sign up for the webinar here (it will be live on September 22).

This podcast is sponsored by my upcoming webinar with AlphaSense

AI is evolving rapidly. Join the team from AlphaSense, Stephen Clapham from Behind the Balance Sheet, and myself as we discuss the burgeoning use cases and evolution of AI in general and AI agents in particular. Sign up here.

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Transcript for paid subs begins below (The initial transcript is AI-generated and is replaced with a professionally edited version when available)

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This podcast is sponsored by fiscal.ai

Fiscal.ai is the modern financial data provider. Through their web-based Terminal and AI connectors, Fiscal.ai provides real-time financial data, earnings call transcripts, filings, fund letters, and much more. It’s fast, intuitive, and has genuinely helped my research process. Check it out at fiscal.ai/yav for 15% off any of their paid plans.

Please follow the podcast on Spotify, iTunes, or YouTube! And please be sure to rate / review the podcast if you enjoy it, or share it with someone else who would enjoy it (more listeners is a critical part of the flywheel that keeps this Substack and podcast going!).

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Transcript for paid subs begins below (The initial transcript is AI-generated and is replaced with a professionally edited version when available)

Disclaimer: Nothing on this podcast or on this blog is investing or financial advice; please see our full disclaimer here. The transcript below is from a third party transcription service; it’s entirely possible there are some errors in the transcript.

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This podcast is sponsored by Trata

I already know you’re going to like trata. Why? Because you’re reading this blog post, meaning you’re interested in this podcast. And trata is just like this podcast (though without the handsome host!). Trata is anonymized transcripts of buysiders discussing stocks they are following and what they really think will drive the stock. I’ve been mentioning it on the podcast for months, and the most frequent complaint I hear from people who check it out is they wish trata had more content on more of their stocks. Even better: they recently released an MCP that lets you connect their transcripts to the AI model of your choice. If you’re interested, click here to check out them out.

Please follow the podcast on Spotify, iTunes, or YouTube! And please be sure to rate / review the podcast if you enjoy it, or share it with someone else who would enjoy it (more listeners is a critical part of the flywheel that keeps this Substack and podcast going!).

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Transcript for paid subs begins below (The initial transcript is AI-generated and is replaced with a professionally edited version when available)

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Second, please remember you can always reach out to me if you have questions or want to swap thoughts on any…

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This podcast is sponsored by Trata

I already know you’re going to like trata. Why? Because you’re reading this blog post, meaning you’re interested in this podcast. And trata is just like this podcast (though without the handsome host!). Trata is anonymized transcripts of buysiders discussing stocks they are following and what they really think will drive the stock. I’ve been mentioning it on the podcast for months, and the most frequent complaint I hear from people who check it out is they wish trata had more content on more of their stocks. Even better: they recently released an MCP that lets you connect their transcripts to the AI model of your choice. If you’re interested, click here to check out their TBBB transcript.

Please follow the podcast on Spotify, iTunes, or YouTube! And please be sure to rate / review the podcast if you enjoy it, or share it with someone else who would enjoy it (more listeners is a critical part of the flywheel that keeps this Substack and podcast going!).

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Transcript for paid subs begins below (The initial transcript is AI-generated and is replaced with a professionally edited version when available)

Disclaimer: Nothing on this podcast or on this blog is investing or financial advice; please see our full disclaimer here. The transcript below is from a third party transcription service; it’s entirely possible there are some errors in the transcript.

Read more