By far the dominant theme in the markets this year has been AI. AI winners are skyrocketing and AI losers are left for dead.

But AI is the dominant theme for investors as well. Almost every conversation I have with an investor at some point turns to AI. For investors, AI is alternately terrifying and exciting: exciting because it can function as a force multiplier that allows you to build tools that were previously prohibitively expensive, analyze data in ways that previously weren’t possible, or dive deeper into research than one person would have been able to on their own. But that excitement comes with a terrifying price. For me, AI has created more than a little existential fear: given how powerful AI tools are, it makes me wonder how long humans will have a real role in the investment process (and if we should hedge that career risk by buying some of the AI winners!).

On top of that existential fear, AI causes one other fear: the fear of being left behind.

There’s an old saying in investing, “whoever turns over the most rocks wins.” AI can improve an investor’s ability to turn over rocks in a lot of ways. It can summarize earnings calls, automate workflows, improve productivity, etc. Imagine that an investor discovers a way to “turn over” 5x more rocks with AI. That’s an incredible advantage…. it’s not a lasting one because other people will figure out how to do that as well, but it’s also one of your worst nightmares as an individual investor. Why? Because, unlike many other industries, investors are generally self taught or learn through an apprenticeship model very early in their careers. If a new tactic (like using AI) comes along later, it’s really easy for an investor mid-career to fail to learn it and get left behind.

Imagine being an investor who started in the 80s and didn’t know how to use spreadsheets or email…. maybe that can work for you if you’re Warren Buffett (so you can do spreadsheets in your head and you’re already so rich/powerful that people are willing to work around your lack of email), but for mere mortals you’d need to learn spreadsheets and email or get left behind. There’s a decent chance AI today is what spreadsheets were in the 80s, except on steroids: it accelerates everything you do, not just math.

So, given all that, I’m always trying to learn how to use AI in better ways…. and I think a lot of you are too, because all of my posts on AI have gotten a torrent of responses from people looking to swap tips and tricks. I mentioned that to my friends at AlphaSense, and they agreed to host a webinar focused on using AI as an investor. I’ve done a lot of AlphaSense webinars, but this is probably the one I’m most excited for.

Why?

Because I think we have the perfect experts to address exactly those fears.

• Dave Wang is the CEO of Wall Street Prompt. They charge Wall Street banks >$25k/day to train their employees on AI; I think there’s more than a little signal in how valuable his training / teaching is in that number, and I believe it’s a real coup to get him for an hour on a free webinar.

• Ben Collins works directly with investors on implementing AlphaSense’s AI tools, so he’s the perfect person to ask about using more finance focused tools (like AlphaSense) and getting more granular color on how the most AI-forward investors are incorporating AI into their workflow.

We’re recording the webinar early this week and launching it next week…. which means there are two things you can do if you’re interested:

1. Most importantly, you can sign up here to access the webinar when it launches

2. If you have questions that you think I should ask either Dave or Ben, you can lob them into the comments below and I’ll try to hit them.

I can’t promise this webinar will have you turning over 5x more rocks…. but given what Dave charges Wall Street for his time, I’d bet you walk away with a few new tricks for free. Sign up here.

This podcast is sponsored by my upcoming AI webinar with AlphaSense

The AI landscape has never been more crowded — or more confusing. Everyone’s telling you to adopt AI, but almost nobody’s asking the harder question: which tools actually give you an edge?

I’m sitting down with Dave Wang of Wall Street Prompt and Ben Collins of AlphaSense to break down the modern AI stack for investors — from horizontal platforms like OpenAI and Claude to agentic workflows and finance-specific intelligence tools — and where each one actually fits in a real research process.

If you’re trying to build an AI-enabled workflow that sharpens your judgment rather than replacing it, you won’t want to miss this. Join us on June 25th - register now!

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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Part 1 (which you can find here) explained how unique Google’s equity raise and structure was. Part 2 (which you can find here) built on that piece; once you understood how unique the Google raise was, it isn’t a long throw to see how massive their capex spend is about to get.

I ended part 2 noting that it doesn’t seem like consensus has caught up to just how much capex the big AI companies are about to spend. Based on just their commentary and equity raises, it seems pretty clear that META and GOOG are going to blow away estimates for capex spending. Given there are rumors AMZN and MSFT are thinking about raising equity, I’d guess their consensus capex numbers are low too.

Remember that these capex numbers are enormous, so small misses can be pretty meaningful. Street estimates call for Google to go from ~$180B in capex this year to ~$240B in 2027. I believe their equity raise suggests Google will blow through that number; that belief means estimates are short by tens of billions of dollars. If META, AMZN, and MSFT capex estimates are off by similar amounts…. well, semiconductors and all things AI have been on a massive run so far this year, but if consensus estimates are that far off there’s a decent chance that the run has a long way to go.

It’s enough to make an investor want to throw caution to the wind and yolo into a basket of AI bottleneck plays. Sure, they’ve all melted up, but you’re talking about basically all of the world’s largest companies in an arms race to spend capex. Even after the melt up, it’s not hard to imagine that the market is underestimating the bullwhip effect that race to spend is going to have on near-term profits up and down the supply chain.

Given how bullish the implications of that capex boom are, I did want to try to throw some cold water on the first two posts with some of the bear points that are bouncing around my mind. I’ll run through the standard bear arguments (and why I’m skeptical of them) in a second…. but I’ll tell you upfront: the bear case that actually worries me comes from an old market saying: “I’ve seen gluts that haven’t led to shortages, but I’ve never seen a shortage that hasn’t led to a glut.”

The three most frequent bear points I hear are somewhat connected, and they’re the typical arguments you’ll hear against a speculative boom. They are:

• AI is a circular business. Brilliantly captured by the meme below, a simplified example will show this best: NVDA invests in a hyperscaler who takes the money and invests it right back into NVDA chips. Thus, the demand and profits are somewhat self-perpetuating while the cycle is hot and every AI company can raise near unlimited amounts of money at ever increasing valuations. Eventually, that type of perpetual motion machine ends, and when it does you realize there wasn’t any real underlying demand. This concern has some callbacks to the dotcom bubble, when Yahoo would invest into a startup who would then spend the cash buying banner ads on Yahoo.

• Demand is way overstated: Ever been to a concert that’s a little out of the way and needed a ride home? It’s a true free for all; everyone at the concert is requesting a car, prices are surging, and there are no cars available. You know what happens? Every person pulls out their phone and makes a request on both Lyft and Uber, and then they start cancelling the requests in favor of whatever will get there fastest. Imagine you’re there with your wife and best friend. The three of you will request six cars in total (three Lyfts and three Ubers), and then you’ll start cancelling the worst matches until a car finally gets there (i.e. if you get matched to an Uber 15 mins away and your wife gets matched to one 25 mins away, you’ll cancel hers). So Uber and Lyft each see way, way more demand than actually exists (in that example, they see a demand for 6 cars total even though real demand is 1 car!). Bears will tell you something similar is happening in a lot of the AI bottleneck areas; there’s a shortage in so many places that companies are placing orders with every supplier and then will start cancelling orders when they actually can find supply. There are parallels to this from the dotcom bubble; infrastructure (particularly fiber) was in huge shortage, so fiber companies would say that they were matching their capex to demand only to see most of that demand vanish when their capex came online.

• Demand is subsidized and will fall off without the subsidies: Remember the height of the post-Covid boom when you had a ton of VC backed online companies that got funding at insane valuations and were using all that cash to acquire consumers with discounts and promotions? I live in NYC; for a while, if I was craving ice cream, it was cheaper (and sometimes faster!) for me to have it delivered to me than it was for me to actually walk out of my apartment and go buy it from the corner store a block away. Ubers and Lyfts were so subsidized for a while that, on the right route, they were actually cheaper than taking public transit. Bears would argue you’re seeing something similar with AI right now; the AI companies are so desperate for growth that they’re heavily subsidizing usage. So the demand you’re seeing for AI right now is AI demand at a heavily subsidized number…. but, in the same way I won’t get ice cream delivered to my apartment once a week without a massive subsidy when I could walk two minutes to the corner store to buy a pint, AI companies are going to realize a lot of this demand evaporates when it’s priced rationally.

I completely understand those arguments, and I’m sure there’s some truth to all of them…. but I think they’re misguided here. Why? Most of the companies that are racing to increase their AI spending (AMZN, MSFT, META, GOOG, etc.) aren’t just selling AI to customers…. they’re huge users of AI in their core business. And all of them are telling you that the ROI for the AI they’re deploying in the business is massive (remember Google led their capital raise call by noting AI is “lighting up every part of our business, driving an expansionary moment in Search, turbocharging Cloud and much more”). So this spending is being driven in large part by these companies seeing the tangible results of what AI is doing for them and thinking that is where the puck is going for other companies as well.

On the “demand is subsidized” point specifically, I’d also note that the history of all compute is everything getting drastically cheaper over time. Say it takes X tokens to replace a software engineer making $250k/year, and today X tokens cost $500k but the AI companies are subsidizing them down to $50k. Sure, that demand would collapse if the subsidies went away tomorrow…. but in a few years X tokens will actually cost $50k, and at that point the demand is real!

So I’m a little skeptical of many of the traditional bear arguments… but there is one bear area that I don’t hear about a lot that I think is worth exploring.

Let’s get back to that old “glut and shortage” saying. Right now, there’s an incredible amount of stuff in shortage: memory, power, etc. As discussed above, I think the demand for the stuff is real, so I don’t think the demand side leads to a glut…. but I’d be shocked if the supply side doesn’t lead to a glut. I mean that in two ways.

First, just on general AI infrastructure, in part 1 I shared this quote below from Google all the way back in Q2’24. I think it’s really instructive:

Google’s commentary on AI spend has evolved over time. Q2’24 is actually the last time they really defended increasing their AI spend; they’d soon just note that all their increases in capex were justified by “strong demand” or “healthy ROI on our investments.”

So I have no doubt that Google is seeing positive ROI on the investment that they’re putting into AI…. but they have also made clear that they will lean towards overspending rather than underspending. That’s actually a very rational wager; history is littered with companies that missed big shifts and saw their franchise evaporate. If you’re a multi-trillion dollar company like Google and the downside to overspending on AI capex is you waste a few tens of billions at subpar returns, but the downside to underspending is you miss the AI shift and your multi-trillion dollar franchise melts away, it’s pretty rational to lean heavily to overspending. It’s pretty clear that every other AI company of note is attacking AI in a similar “this is existential” way; it’s simply impossible to have an industry where every company is committed to overspending and not have some type of glut / excess. Even if they’re underestimating the near term demand, that simply means they’ll course correct and overspend once they’ve realized they underestimated near term demand. Eventually, you’ll get an overbuild one way or another.

But the more pressing concern for investors is in the bottleneck industries. Google has been telling you for years that they “obsess” around every dollar of capex they spend and that they have a “relentless focus on ROIC.” They’re prepared to spend hundreds of billions of dollars in capex. If you’re investing in a company that is currently experiencing a super cycle of profits thanks to shortage, you have to ask yourself not just how long that super cycle lasts and if the industry can maintain discipline around bringing supply online….. but you also have to wonder at what point does Google (or META, or AMZN, or MSFT) just build a competitor to you to end the supply shortage if your industry maintains supply discipline?

Consider Micron. Their book value is ~$65/share. If you strip out intangibles and excess cash, it’s probably closer to $50/share. They guided to ~$19/share in net income in Q3’26 alone, and I’m seeing consensus says they’ll do ~$100/share in EPS in FY27. I don’t think it’s crazy to say they’re doing >100% ROE right now.

Historically, memory is a very cyclical commodity business. Micron’s 20 year average ROE is ~9.2%:

That 9.2% ROE is somewhat dragged down by the GFC; if you want to cherry pick that out their 10 year ROE is closer to 15%.

Now, bulls will tell you that memory companies are an oligopoly that have gotten religion on avoiding oversupply. Perhaps that is true. And perhaps cheap Chinese competitors won’t emerge…. but, even if you believe all of that, Google is about to spend $200B/year in capex with a relentless focus on ROI (their words, not mine!). Micron has spent <$100B in capex cumulatively over the past ten years. How long is Google (or AMZN, or META) going to let memory companies make >100% ROEs and serve as a bottleneck in the AI supply chain before they just start building memory plants themselves?

MU (and memory plays like it) are going to earn a fortune in the near term….. but there will be a supply response at some point. And, given this spike is currently the mother of all shortages, I’d be shocked if it wasn’t met with the mother of all gluts on the backend. MU has done ~10-15% ROEs historically; I wouldn’t be surprised if the supply response from the current shock was large enough to push them well under that average for multiple years when the shock ends, and I think there are plenty of industries that are in shortage now that will face similar gluts. One way or another, the capital is coming….

I’ll wrap the series with a confession: part of the reason Google’s raise grabbed me so hard is that I’ve been thinking about (and working with) AI nonstop this year (if you missed it, my series on using AI as an investor starts here). The tools and possibilities for investors are improving just as fast as the capex is growing… and, in the same way GOOG and the big tech companies are leaning towards overspending because the downside of underspending is existential, I’m leaning towards “over-experimenting” with AI because the downside of not playing with it is somewhat existential….. so I’m always happy to swap notes on AI capex, using AI tools as an investor, or anything else!

PS- Might as well end by noting I’m taping a free webinar with AlphaSense next week completely focused on using AI as an investor; if you’re interested in learning more, you can sign up here.

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This podcast is sponsored by my upcoming AI webinar with AlphaSense

The AI landscape has never been more crowded — or more confusing. Everyone’s telling you to adopt AI, but almost nobody’s asking the harder question: which tools actually give you an edge?

I’m sitting down with Dave Wang of Wall Street Prompt and Ben Collins of AlphaSense to break down the modern AI stack for investors — from horizontal platforms like OpenAI and Claude to agentic workflows and finance-specific intelligence tools — and where each one actually fits in a real research process.

If you’re trying to build an AI-enabled workflow that sharpens your judgment rather than replacing it, you won’t want to miss this. Join us on June 25th - register now!

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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That’s the question that kind of keeps me up at night right now, as the answer to that question has enormous implications for pretty much any area of the economy that is touched by AI (which, at this point, is basically every area of the economy).

Yesterday’s post focused on all of the ways Google’s big raise broke with precedent: the sheer size, the ATM program, the capital allocation U-turn (from share repurchaser to share issuer), and the way they marketed the deal.

But I left one thing out: the thing that makes Google’s raise shocking. Google is gushing cash flow (they’ll do ~$200B of operating cash in the next twelve months), and while free cash flow is coming down as AI capex spikes, they are still decidedly free cash flow positive (~$10B of free cash flow in Q1’26 alone, and they will be solidly free cash flow positive in 2026). On top of all that cash flow, they have ~$50B of net cash on their balance sheet (plus another $100B of non-marketable securities that will get liquid real fast after the SpaceX IPO!).

It’s borderline insane for a company with Google’s financial profile to look at their business and outlook and think “we better raise some equity capital.” And it’s even crazier once you factor in their (recent) corporate history and how dedicated to returning capital to shareholders they had been. If any other company had this much net cash and cash flow and put out a press release saying they were cancelling their capital returns in favor of raising equity, the stock would have been down 20% and investors would have assigned the company a permanent “capital misallocation” discount while begging for an activist to get involved.

So that big equity raise marks a sudden U-turn; why did they suddenly change their tune?

If you’re a bear or an AI skeptic, perhaps the answer is simply looking at Google’s chart and thinking “hot damn, these guys are good traders! They bought back loads of stock when it was cheap in the $160s in 2024 and the $190s in 2025 only to issue it back when it was overvalued in the mid-$300s in 2026. Get these guys a hedge fund!”

But I don’t think that’s right. If Google was trying to just time their stock, I think they do a lot of stuff differently. For one, if they’re trying to just blast out overvalued stock, they do the whole issuance now instead of saving ~half for the ATM program that starts in Q3. They probably don’t do the whole CEO/CFO presentation showing what an opportunity AI is; that’s too out of line with their history. They just call their banks up and say “we want to print $85B of stock” and have it done in a few days.

My read is that they really believe what they’re saying when they come out and say “AI is the most profound platform shift of our lifetimes. It’s lighting up every part of our business.” And they’re backing that talk up with their actions / capital allocation dollars; just under $200B in capex in 2026 and “significantly” more in 2027.

If you’re really online, you’ve probably seen someone say something like “GOOG is blasting out capex. They have better access to their roadmap and the bleeding edge models than you; what does that tell you that they’re seeing?” So I hate to repeat that point because it’s so overdone…. but the thing about that point is you don’t even need to infer it or play chess to reach that conclusion. On just that one capital raise call, Google is telling the whole world “our capital investments are informed by our view of ROIC.” Not only that, but they’re telling you that this capital raise (and the ROIC they’re projecting from it) is in large part informed by their customers’ backlog.

So Google isn’t just making up the AI demand and ROIC. They’re seeing it in their core business, and their customers are telling them about it and demanding more of it. Google is telling you that the return from investing in AI isn’t imaginary or speculative. They’re telling you it’s here, it’s real, and it’s happening now.

And the implications for investors are enormous. Google isn’t going to invest just this equity raise into AI. Google made clear on their equity raise call that they’re going to be financing their AI investments with everything they can: operating cash flow, the equity raise, and debt.

Remember, Google will generate ~$200B in operating cash flow over the next twelve months. They’ve got $50B of net cash on their balance sheet (plus another $100B in investments, largely from the SpaceX stake). They could easily take down $100B of extra debt. They looked at all of that and said “we need more equity capital, and we’re probably going to leverage that up.”

Bloomberg tells me consensus estimates for Google’s capex are ~$240B in 2027:

I don’t think Google’s raising $85B in equity capital thinking they’ll spend $240B next year. They could have paid that out of operating cash flow plus maybe dipping into their net cash balance a little! My guess is that the Google capex number blows away those estimates. Ditto Meta; consensus is for them to spend ~$160B in capex in FY27; I doubt they’re looking for “creative” ways to raise cash if their capex is going to be roughly in line with their operating cash flow!

Everything that touches AI (power, memory, semis, etc) has been in “melt up” mode over the past few weeks as demand gapped higher and prices went parabolic. My guess is that there’s more than a little euphoria in a lot of those stocks, but I will tell you this: it’s very hard to reconcile the Google equity raise with the consensus for Google’s capex in 2027. Google is going to blow through those projections. And, if the Google capex consensus is anywhere close to what the market is pricing in to all of the “AI suppliers,” then we could still have a long way to go before the market catches on to just how enormous the spend here is about to get.

But before you take that as a license to YOLO into a basket of AI bottleneck stocks, history has a warning about what happens when this much capital actually shows up to a shortage / price squeeze. I’ll talk about that bear case in part 3; see you tomorrow. (And if you’re not subscribed yet, sign up now so you don’t miss it!)

Ok, I’m not exactly breaking new ground with that statement. Depending on the day, Google’s EV is ~$4.5 trillion, making them tied with Apple for the second largest company in the world (NVDA is the largest at around $5 trillion). On top of their sheer size, the Google equity raise is the largest public equity raise in history2…. even larger than the pending SpaceX IPO.

Plus, to add a little bit more spice to the story, Berkshire Hathaway took down a huge slug of the raise, so the raise has a bit of a “Buffett blessing” piece to it3.

Put all of those pieces together, and the Google equity raise was well covered. Bloomberg had background on the Berkshire investment within 24 hours of the deal, basically every major publication (Reuters, WSJ, FT, CNBC) had some type of coverage, and you could find plenty of quick takes on what the raise meant (for example, Stratechery).

Still, I’ve been thinking a lot about the GOOG raise…. and, despite all of that coverage, I think there are a few interesting angles that haven’t been picked up, so I wanted to put some pen to paper on the topic. I’ll cover six topics in this series; they are:

1. A quick clarification on the mechanics of the raise

2. How unique this financing structure is

3. How Google broke from their own corporate history (and recent financial market history) in marketing this deal

4. Google’s capital allocation flip

5. What is Google seeing to raise like this?

6. The bear case

Today’s post covers the first four topics; part 2 (tomorrow) digs into what Google is seeing, and part 3 wraps the series with the bear case.

First, a clarification on the raise mechanics that will be important later. While the headline number here is “Google raises $85B in equity”, it’s actually split into two tranches: they raised ~$45B this week, and they’ll raise the other $40B through an at-the-market (ATM) offering that will start in Q3.

Second, let’s dive into just how unusual that structure is. Google is raising $45B now and $40B through an ATM later this year. ATM programs are by no means rare; they’re actually very common among capital heavy companies. Almost every large utility (NEE, SO, D, AEP, XEL) and REIT (O, PSA, DLR) has an active ATM program or has used one in the recent past. ATM programs are also very popular among smaller companies, particularly ones on the “meme” side of the coin (AMC and MSTR4 have been frequent users, and BBBY desperately tried to hit an ATM when they meme’d a few weeks before filing). ATMs have also historically been popular among companies in distress that need a lot of capital (the cruises and airlines were popular ATM issuers in and around COVID).

So ATMs are not rare…. but they are extraordinarily rare for a company with Google’s size and with Google’s cash flow and asset value.

How rare?

I cannot find a single S&P 500 company that is not a REIT or a utility that has an active ATM program. Google is a one of the five largest companies in the world and (as I’ll detail in a second), absolutely gushes free cash flow, haven’t done a secondary offering in over 20 years, and was buying back stock as recently as Q4’25. It is wild that they’d feel the need to establish an ATM.

Third, I think it’s really notable how Google broke from both their own corporate history and financial market history in marketing this deal. Alongside the raise, Google did a webinar with their CEO and CFO explaining the rationale behind the raise and provided a slide deck:

Google is aiming to raise $85B through this secondary / ATM; that’s an enormous amount of money in the absolute…. but Google is a ~$4.5 trillion market cap company, so the raise is actually a drop in the bucket relative to their size (<2% of their market cap in total, and ~1% if you’re just talking about what they’re raising this week). I see companies do secondaries all of the time; it’s pretty rare for them to have a public management call alongside the raise, and it’s even rarer for them to do a corporate deck. To give you an idea of how big a break from history this was: the largest previous follow on raise I can find was Boeing’s ~$24B raise in 2024; Boeing was a ~$100B market cap company at the time, so they were raising a much bigger percentage of their market cap…. yet they did their big raise without hosting a special call or producing a slide deck5.

Just on that history, Google’s current raise is already a major break from market precedent…. but it’s even starker when you consider Google’s own history. Google rarely produces public slides or investor communication with their top brass. Historically, they didn’t even do earnings slides; they only started providing slide decks with their earnings in 2025:

Alongside those earnings slides, they provided a deck when they bought Wiz in early 2025:

Outside of those few examples, I can’t find a single example of Google producing a financial deck in the modern era6.

Bottom line: Google did not need to produce a deck alongside this raise. Both Google’s own history and the history of similar raises suggest that Google could have done this without a deck…. but the fact Google decided to break so strongly with that precedent shows you just how important this raise and capital build out is to them (at least IMO!).

Fourth (and speaking of breaking with financial history), it is worth briefly noting Google’s capital allocation flip. Google has been a frequent repurchaser of their own stock. They bought back $62B in 2024 (at ~$165/share) and $45B in 2025 (at ~$190/share), and in April 2025 they had reupped their repurchase authorization by $70B.

A quarter by quarter look at their buybacks is really interesting: Google buys back ~$60B of stock in 2024. They keep up a similar pace to start 2025, buying ~$15B of stock in both Q1 and Q2. That slows to $10B in Q3 and $5B in Q4. They then don’t buy back any stock in Q1’26, and in Q2’26 they make the largest equity issuance in history.

Which would bring us nicely to the last question (and the one that will keep me as an investor up at night): what was Google seeing to do a raise this large???…. But this post is running really long. So we’ll have to hold off on that natural transition until we dive into part 2 tomorrow. See you then! (And if you haven’t yet, don’t forget to subscribe so parts 2 and 3 land straight in your inbox.)

PS- at the risk of spoiling future pieces of this series, Sundar was asked about the risk of overinvesting in AI capex all the way back in 2024. His answer is really instructive on where this whole thing is going:

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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. See why I like them so much by checking them out 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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On the one hand, I find AI fascinating; I’ve been using AI to quickly build interesting research tools (and even a new Substack!), and the process of playing with AI in different ways has been insanely fun and massively ramped my productivity.

On the other hand, I find AI terrifying. As an investor, you are paid for some combination of your judgement, analytical skills, and hard work. As AI continues to improve, I worry that AI undercuts humans on all three of those levels. Consider:

• Hard work: Most professional investors get paid on some type of incentive fee. It’s comical to spell this out, but the whole purpose of the incentive fee is to incentivize the manager to work hard. So, consider the GOAT: Buffett. Last year, I reread Buffett’s Biography, the Snowball, for my book club. One thing that jumps out when you read it is just how hard Buffett worked1; there were tons of stories along the lines of “Buffett skipped XYZ family event to read one more annual report alone in his office.” The argument would be that investors in Buffett’s partnership gave him the money and the incentive fee to reward him for skipping that dinner and generating insane returns…. but what happens when you’ve got an AI running that can read every 10-k and every piece of investing material all the time. How is a human supposed to compete with that? No matter how large the fee, humans run into natural laws on how much they can read. A human needs to sleep; an AI does not. At the high end, a speed reader can comprehend 400-700 words per minute; AI basically has no limit. No amount of hard work or dedication will let a human catch up to the AI in terms of just quantity of information consumed.

• Judgement: Like in most competitions, investors generally get better with experience. There’s just something about researching a bunch of companies and investing through a market cycle or two that makes you a better investor and gives you better judgement, and there’s no real way to shortcut the process… as a human. But an AI could run unlimited backtests and near instantly consume all of recorded market history. How is a human who is limited by their own market experiences supposed to compete with the whole of human history?

• Analytical skills: When you think about a “top” investor, what generally makes them stand out is their analytical skills. They study a company or an industry, determine what future the market is pricing it for, and then swing when they think the market is wrong for XYZ reason. In math, AI has gone from unable to do basic math to “frighteningly smart” inside of a few years; how long until it can reason out industries and businesses better than any human could ever hope?

So I worry that the days of a human able to outperform the market are over… and my level of worry kind of goes up when I see things like META2 granting “YOLO” options that would likely require a massive acceleration in AI to pay off. And, while admitting that I may be prisoner to the moment, I’ll note that the SOXX going parabolic isn’t making me feel any better about my worries: yes, a parabolic move may just be part of a bubble forming…. but a parabolic move in semiconductor pricing is also what you’d expect if AI is starting to approach full AGI.

In fact, in my mind, if you’re an investor and you’re not at least somewhat worried about AI replacing humans, I’d argue you’re not thinking enough about the problem. AI has gotten so good at beating humans at every game it plays (chess, Go, Starcraft) that it stopped being newsworthy when AI conquered new games three or four years ago. If you’re an investor who is not worried at all about AI, you’re betting on one of two things:

1. You’re making an extremely binary bet that there’s something so unique about the markets (probably its fat tails) that AI can’t succeed in investing when it can at literally every other competitive field.

   1. Personally, that’s not a bet I’m really eager to make.

2. People once worried that spreadsheets would kill off accounting jobs, but the rise of spreadsheets actually killed off the lower end jobs (bookkeeping) but created an explosion in more skilled roles like accountants and auditing. You’re hoping something like that happens here, and AI kills off lower end jobs (I guess entry level analyst?) but creates an explosion of higher end jobs (portfolio manager?).

   1. I’ll admit: it’s not a perfectly clean comp, but you can see the kernels of some hope there.

   2. I will also note that I’ve gotten a little hope recently from software engineers: despite the massive improvement in AI software coding, we haven’t seen mass layoffs of software engineers. Instead, we seem to be seeing companies stop hiring at the bottom (low end / entry level analysts), but higher end engineers seem to be holding on and maybe even increasing their value by harnessing AI to massively improve their productivity. I think the hope here would look something like this: AI supplants humans as an analyst, but the most talented investors learn how to harness AI to massively increase productivity / research speed while letting them really focus / differentiate with whatever their specific edge is.

What’s an investor to do if they’re acting rationally (at least in my opinion) and worried about the AI takeover? That is a hard question to answer. My wife and I used to joke that selling pictures of our feet online was always our backup gig…. but I suspect that if AI is good enough to solve ~100 year old math proofs and displace humans from investing, it will produce foot photos far more marketable than my own little piggies will ever be. Another popular option might be “drink away your worries,” but I don’t drink, so that’s not exactly an answer for me either!

With excessive drinking and profiting off my feet scratched off, the best option I can think of as an investor looking to insure against the rise of investing AI is a “Texas hedge”: buying stocks that would benefit from the rise of our AI overlords3.

What’s interesting is that putting on a Texas hedge actually isn’t that expensive right now. Yes, volatility on Micron and the like is off the charts, but those moves are being driven by shortages and super-cycle style profits. I struggle to believe that we live in a world where we have superpowered AI that can’t figure out how to respond to pricing signals to solve shortages over the medium term; if you’re buying one of those plays, you’re really just betting on how long (and how deep) the current shortages last. I don’t have any view on that.

But consider META and MSFT. It’s hard to imagine a world where you get a real AI takeoff and at least one of them isn’t a winner. On top of their own AI efforts, MSFT owns 27% of OpenAI (plus an insane amount of compute and hardware from Azure). META probably has more data than anyone on the planet plus their own (suddenly) promising AI efforts. Both trade for reasonable multiples (fiscal.ai tells me both are in the low 20s forward P/E) and have long-dated LEAPS that are reasonably liquid and pretty cheap: META’s December 2028 LEAPS have high 30s vol while MSFT’s are in the low 30s…. that seems way too low for businesses that could be on the verge of a massive AI inflection.

Maybe I’m suffering from AI psychosis…. but, to me, buying META / MSFT at around a market multiple with the added kicker that at least one of them probably goes parabolic if AI really takes off from here does not seem like a bad “hedge” on AI taking all of our jobs.

Note that I’d settled on MSFT and META as the “value” hedge (given their low multiples + AI exposure) to AI taking over the world a few weeks back…. but it’s interesting that they’re now two of Ackman’s largest positions (and that he basically sold Google to buy MSFT4). You could look at Ackman buying them and treat it as a contrarian signal (MSFT and META are now the “boomer” way to play AI, and what are the odds the boomer way is going to work out?), or you could see it as reassuring that someone with near unlimited resources to talk to people on the edge of the AI fields has decided to back these two horses. Really depends on how you feel about Ackman!

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So let’s start with the basics. I built the whole One Idea Per Day Substack with Claude Cowork; if you haven’t started using it yet, I’d highly encourage you to do it as it’s really easy to use (no coding background required!) and I think it will really blow your mind once you start using it (here’s a very basic Cowork overview if you haven’t picked it up yet).

What I really wanted to build was a Substack that could run fully hands off, but with the option for me to lightly nudge it or provide input over time if I wanted to tilt it in a different direction.

Below, I’m going to provide a ton of screenshots of exactly what I told Cowork to get this project up and running. If you’re already super familiar with using Cowork, this might be boring or look simple to you (if you’ve got feedback on prompting and the like, I’m always open!). But, if you haven’t used Cowork or are just starting to dabble, I suspect a lot of this will be eye-opening to you. If I had to give you just one piece of advice for using Cowork to build interesting projects, it would be this: just start using it. Think of something that would be useful, ask Cowork to do it, and iterate with it back and forth until the task is complete.

In fact, that was the whole point of this project: I wanted to play around with AI to continue to test how easily you could spin up unique projects. The new Substack is fun on its own, but the bigger reason I built it is that it’s an easily shareable example of what’s possible; I’ve been using the exact same approach to build research and portfolio management tools for myself (and many of those aren’t as easy to share for a bunch of reasons!).

Basics out of the way, let’s turn to actually building the project. I started by opening a new Cowork project called “idea per day substack”:

Here’s what the instruction looked like to begin with, as well as my first prompt:

After my first prompt, Cowork asked me a few questions, including how hands off I wanted to be (answer: extremely!):

As we went through the project, I slightly modified it to allow for a little more input on my end if I wanted to tilt the project a little:

From there, it was just a lot of iteration. For example, I gave it rules on what ideas to use and to avoid repeating ideas:

And I had it build disclaimer and about pages:

I asked it for ways to incorporate reader feedback:

And, recently, when I thought the ideas were getting too focused on vanilla merger arb, I gave it a course correction:

All in, the project took an afternoon to set up, and there’s no real ongoing cost or time spend on my end (I’ll read a write up if the name interests me, and every now and then drift in to make sure everything’s working properly…. but other than that I’m totally hands off!).

If you've used Cowork to build something interesting or you've got better prompting ideas than what's in those screenshots, my emails are always open!

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. Plus, if you’re interested in CELH, you can see the transcript I used to prepare for this podcast 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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For anyone who benchmarks to an index, I'm not sure we've ever seen anything quite like the current memory / semi cycle: a single cyclical boom that is big enough to move the whole market by itself.

In the short term, the supply of memory and semiconductors are somewhat fixed; it doesn’t really matter how strong the demand is, it takes years to build up new plants to make more of these. The AI boom has driven seemingly unlimited demand for memory and semiconductors. Combine skyrocketing demand with no immediate supply response, and memory and semiconductor prices are soaring… and taking their underlying stocks with them.

Nothing in that sentence is new when it comes to cyclical booms/busts. Most big commodity industries have relatively fixed supply in the short term, and they all run through booms and busts….. but the AI boom is somewhat unique in its structure. Consider a few factors:

• Scale of demand increase: most commodities tend to have pretty stable demand because they’re reasonably mature industries. A really strong economy is going to send the demand for energy up by a few percent at most. The auto cycle tends to swing on 5-10% moves in annualized new car sales. In contrast, memory demand has gone up by ~400% inside of a year or two.

• Lack of supply response: Send prices up enough, and you’ll find some form of switching. When oil spikes, governments will release their strategic reserves to smooth out prices. If nat gas spikes, you’ll see switching from nat gas to coal. And it only takes a few weeks to bring on some marginal supply of nat gas / oil…. but there’s no strategic memory reserve to release from, and there’s really no alternative to memory a la nat gas / coal.

• Lack of demand destruction: When oil prices double, people respond on the margin with less oil consumption. Flights get cancelled, road trips get shortened, etc. When electricity prices go up, you’ll see factories ration production. But the AI boom has shown no sign of abating, and the only demand destruction we’ve seen has come from the AI labs throttling their users to meet booming demand.

So those factors make this cycle even hotter / faster than a normal commodity cycle. Consider this: Micron did ~$1b in free cash flow in FY25 and was trading for just over $100B EV. Today, Micron is forecasted to do $100B in free cash flow in 2027. That’s right: Micron’s free cash flow is up almost 100x in ~2 years, and they’ll print almost their entire EV heading into the cycle. Again, we’ve seen cyclical booms before, but the scale and speed of this one is mind blowing!

Perhaps my memory (pun intended) is lacking, but I’m not sure we’ve ever seen a cyclical upswing like this drive an entire market before. As I write this, the S&P 500 is up ~10% YTD. Basically half of that return is coming from just four stocks: Google (~7% of the index, up 25% YTD), NVDA (~7.6% of the index, up 16% YTD), Micron (~1.6% weighting, up ~250% YTD), and AMD (~1.2% of the index; up 140% YTD).

If you broaden it out a little bit to include just AAPL, INTC, AVGO, and AMZN, 8 stocks have driven 75% of the S&P’s YTD return.

And the top 20 contributors to the S&P have generated more than all of the index’s returns YTD:

Those are large companies making massive moves! Again, it’s nothing crazy to see companies generating massive returns during a cyclical bull. What is crazy is to see it happen to companies this large and have them single handedly drive an index.

Now consider what those massive, concentrated moves mean for an active investor benchmarked to the index: if you were underweight a single one of those stocks, you’re trailing the index by a mile. If you were underweight a handful of them and long a single SaaS stock (shudders), you’re currently writing your first draft of your H1 letter explaining to your LPs why you’re trailing the index by 1500 bps.

I was in grammar school during the dotcom bubble, so I can’t claim to have personally known what it was like investing then. But you’ll read about value investors then tearing their hair out as dotcom stocks doubled seemingly every week with no fundamental value while their value stocks languished.

The current market is nowhere close to that bad. The AI beneficiaries are minting money while they’re riding the current wave. Again, Micron might do $100B in free cash flow in fiscal 2027; that’s roughly what its EV was in mid-2025!!!!

But a lot of value stocks are languishing. And while AI bulls would tell you that cycles are over, I’m somewhat skeptical that this time is different when it comes to the boom/bust nature of semis or memory. These companies are simply printing too much money for there not to be a supply response, and history suggests that a super cycle this profitable will eventually be met with a supply overbuild for the ages.

If and when that happens, it’ll be interesting to see what happens to the indices!

PS- there’s a wave of big IPOs coming (SpaceX, Anthropic, etc). These are some of the biggest companies the markets have ever seen, and they’ll almost certainly quickly get added to the indices. While they will carry a lot of AI related “factor beta”, I would guess they’ll also be less cyclical than something like Micron or AMD. So, humorously, you could live in a world where MU and AMD drive the indices up, then see their weights diluted when a new wave of mega IPOs get added to the indices, and then don’t have anywhere close to as big of an impact if their stocks go down as the cycle ends. Being an active manager is hard!

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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What did I build?

Well, the basics are that I built a substack called One Idea Per Day; you can go sign up for it here. Every day, One Idea Per Day scours the web for investing ideas and then does a brief write up of whatever idea it likes the most. Some days the idea is an event driven idea, some days it’s a value idea, etc. The Substack also has an iterative function; reader feedback on ideas (likes on posts, feedback or suggestions on its feedback form, etc.) can change what ideas get published in the future.

I will be honest with you: the posts are nothing particularly special. They remind me of the types of posts and ideas I would come up with when I was getting serious about investing as a junior / senior in college: really eager, relying heavily on other investors’ ideas and thesis, and without a lot of my own thinking.

If the posts are nothing special, then why did I start the Substack?

Because I wanted to experiment and play around further with AI. And here’s the thing about that Substack: I don’t write a single thing on it. I used AI to build the whole thing and I set up an automated AI that now does all of the writing / research / publishing (it even automatically generates all of the images in the post!). In fact, since I launched it, I haven’t looked at the Substack or touched it unless it surfaces a name I want to brush up on.

So I think the whole thing is fascinating. I built it over the course of a few days with maybe 3-4 hours of total work on my end. Again, I’m not claiming it’s the most impressive thing in the world, but I wanted to share it (and some of the process that went into it) with you for three reasons. One of the reasons is positive; the other two are negative.

Let’s start with the positive reason for sharing: I talk to a lot of investors, and the disparity in AI usage is striking. Some investors are so deep into AI that they’re talking about using agents to go out and build their own replacement for software that they’re currently spending tens of thousands of dollars on (Bloomberg, Capital IQ, etc), while others are still wondering if they can even use AI as a google replacement for fear of hallucinations. My hope is that sharing a silly little project like building and automating an idea generation substack will help encourage some added creativity on what’s possible with AI and get a few more investors to dip their toes further into the water (and maybe give me some notes and tips if they’re seeing anything that’s really helping them improve as an investor!).

Alright, let’s turn to the two negatives.

First, one of the real issues of our time is going to be the flood of AI generated content. This chart with the proliferation of e-books post-ChatGPT has lived a little bit in my mind for the past few months:

The rise of AI content is going to apply to a ton of places, but for investors it’s fundamentally shifting how you can read investor letters, substacks, and other sources of investment ideas. I find that investors who haven’t experimented much with AI are much more prone to fall for all of the tricks of AI (“it’s not X; it’s Y”) than investors who have been using it, so a small hope of the One Idea Per Day substack is that by openly admitting it is 100% AI generated it will help open investors’ eyes to what AI generated content looks like.

The other negative reason I launched the substack is that I remain very concerned that all investors are “cooked” (to use language the youth will understand). As an investor, your job is to gather and process a bunch of information (10-Ks, podcasts, industry journals, management interviews, etc.) and use that to identify pockets of the markets that are mispriced. AI doesn’t need to sleep, and it can identify and process information faster than any human could ever hope to. If AI can consume more information faster and more completely than a human, what is the missing ingredient that will keep AI from becoming better than humans at investing?

I don’t know the answer to that question1…. but I wanted to play around with the One Idea Per Day substack to experiment with how an (admittedly unsophisticated) AI might approach idea generation.

/Fin

I’ll let you check One Idea Per Day out and decide how useful or interesting it is for you… but, in a “teach a man to fish” way (and similar to what I did with my Sweetgreen review tool), I also want to show some of the things I did to build out the substack (or, more accurately, the prompts I used to have AI build it out!). I’ll include that as a separate post later this week just because that post is running long / has a ton of images in it. I’ll see you then (and, if you’re not subscribed, be sure to to make sure you don’t miss that post!).

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. If you’re interested in trata, you can check them out 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. Plus, if you’re interested in DASH, you can see the transcript I used to prepare for this podcast 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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• AGL: another proof point that these can work FAST

• RIVN gets a mulligan

• COTY’s midstream adjustment

• DUOL: what happens when you halfway vest?

• TPB’s CEO chooses stock

Let’s dive in.

• AGL: another proof point that these can work FAST

On April 27, AGL hired a new CEO. His contract had 200k PSUs that started to vest at $50 and vested in full at $150. Given the stock was trading <$30 at the time, it was a pretty bullish signal.

On May 6, the company reported blow out earnings. The stock more than doubled, and it’s almost doubled again. Not only are the first set of PSUs set to vest imminently, but it seems like the second set might vest before the summer is over!

• RIVN gets a mulligan

One of the issues with the “dark arts” is management can turn it into “heads, I win; tails, I try again and then win” pretty easily: give yourself an aggressive stock grant…. and then if you miss it give yourself another one! Thus, there is no signal in a dark arts grant because management is greedy and will just keep giving themselves packages until they get fabulously wealthy, fairness (and shareholders!) be damned.

Rivian serves as a nice example. They gave their CEO a massive package in the boom days when they deSPAC’d…. but with the stock getting hammered and the CEO going through a divorce, they just reloaded him with a $400m package that would be worth >$4B if it vests in full.

The option targets are definitely aggressive….

But if you’re a shareholder, you have to ask yourself: is this package a one time thing meant to incentivize a CEO to pursue a massively value accretive path that insiders are seeing? Or will the board just keep handing these big packages out until one of them pays out?

• COTY’s midstream adjustment

COTY pairs well with the RIVN example; instead of a mulligan, COTY appears to have slow walked setting the actual terms of their new CEO’s pay package to adjust for the business melting down as he took the reins.

Let’s back up; here’s a little secret: sometimes a company will make an executive hire and they won’t give all of the details in the 8-K. When that happens, it’s worth tracking closely to see what’s going on. That’s exactly what happened with COTY; they brought in a new exec chair and interim CEO in late December. His contract called for 6m performance options to be granted, but it didn’t detail what the performance criteria for those options were. COTY buried the performance criteria in their next 10-Q, and they are aggressive. COTY’s stock was trading for ~$3/share when the options were granted (and that’s where they are struck); the stock needs to hit $7.81/share for anything to vest, and full vesting isn’t until $10.50. If the options do vest in full, they’d be worth just shy of $50m pretax. Again, aggressive. Also interesting that the bottom end of the vest is $7.81/share; that is a strange number. How was that specific number chosen? Does management and the board have some view or inside information that informed that number?

Even more interesting, the exec chair / interim CEO didn’t file a Form 4 until March 18 (the same day COTY revamped their whole board). Curiously, if you read footnote 2, both the strike price and the option vesting prices appear to have been nudged down (the strike from the ~$3/share COTY was trading for in December to its current price around $2/share; the vesting from $7.81 on the low end to $5.56/share). Makes you wonder what the company was seeing to adjust all of these down midstream…. though perhaps worth noting that this package (and the adjustments) keeps the CEO in line for a ~$50m payout if he vests the full high end.

• DUOL: what happens when you halfway vest?

I was reading my friend Adam Wilk’s DUOL write up, and he had this table on the PSU DUOL’s CEO got at the time of the IPO.

As I write this, DUOL’s stock is trading for ~$108/share.

Which creates a kind of interesting hypothetical: if a CEO vests ~half of their PSUs and then the stock falls off a cliff, do they have a perverse incentive structure now? Are they incentivized to lever up to try to increase volatility and hit the out of the money options? Or are they incentivized to tamp down volatility and hold on to what they’ve already vested?

I’m not saying either is the case at DUOL; the CEO owns enough stock outside of the PSU grants that he’s probably pretty aligned / not suffering from perverse incentives. But it’s fascinating to think about, and the DUOL structure provides a nice little hypothetical even if it doesn’t fit perfectly!

• TPB’s CEO chooses stock

Sometimes, the signal is not in the action… it’s in how an action changes. Consider TPB: earlier this year, their CEO took his 2025 bonus in RSUs2 with the stock in the mid-$80s/share. Plenty of executives do that…. what’s noteworthy is that he took the bonus in cash in 2024.

Sure enough, Q1 earnings crushed, and the CEO managed to increase his bonus by >10% by taking stock instead of cash.

Side note: the CEO engaged in an interesting forward swap on >$12m of stock that settles in cash or shares; I could definitely see how a swap like this incentivizes him to keep the stock price elevated this year, but I haven’t fully thought it through…

/Fin

Ok, that’s it for post 12. I’ll be back next week with post 13 to wrap the series up with high level takeaways. Don’t forget to sign up to make sure you don’t miss the conclusion of the series (or any future posts)!