Thursday, September 3, 2026

@catechwilliams Dec 4

catechwilliams on X

The $WYFI data center which was formerly a food distribution center. https://t.co/t2cpUNZXqp

@catechwilliams Dec 4

catechwilliams on X

$WYFI Retrofitted a food distro warehouse into a NC-1 DC. Lost anchor tenant ($20M rev), promising a new large customer since 10/27. CEO claiming “very very soon” for last 20 days. Increasingly evident will not happen. Sell-side & stock prices assume huge rev ramp. Burning cash.

@LaughingH20Cap Dec 2

Laughing Water Capital on X

@mil01425146 @yummyCenturyEgg @JBonfato @23Titan31 Happy to talk about $NN, Part 15, antenna science, radar science, tolling, etc., but I prefer to not be tagged on anything having to do with baked goods and personal proclivities. TYIA.

@LaughingH20Cap Dec 2

Laughing Water Capital on X

Interesting framing for $NN. $95 is pretty far above my upside case, but agree the $T / FirstNet arrangement is interesting context, despite some obvious differences. https://t.co/b3FsHVkivk

@LaughingH20Cap Nov 26 1 click

Laughing Water Capital on X

@FishOnCapital IMHO best to view this in context of the pod w/ the banker from the 600 MHz. To paraphrase, all of the likely buyers wanted the 600, but AT&T won b/c they were able to move fastest. I suspect $VZ, $TMUS & others will be ready to move fast for $NN's 900. https://t.co/5gRpmej4Bk

@MultiplesCap Nov 23

Multiples Capital on X

Thinking more about this, the timing feels increasingly closer: The market concentration is extreme: Mag 7 + $AVGO sits at a combined market cap of $18 Trillion. Contrast that with the entire Mid/Small-Cap universe: S&P 400 (Mid): $3T $MDY S&P 600 (Small): $1.4T $IJR Russell 2000: $2.8T $IWM A 10% shift in allocation ($1.8T) from Big Tech could easily double the market cap of these mid/small-cap indexes. It's not a new insight, but with growing AI bubble nervousness in market participants and rising FED rate cut expectations extending into 2026, the potential for this capital shift is getting compelling. #GreatRotation #SmallCaps #MidCaps #MarketTiming

@catechwilliams Nov 20

catechwilliams on X

$PTRN Recent IPO. $AMZN Mktplace wholesaler. Buys products up front, capital intensive, bears price, inventory risk. Exposed to FBA cost & AMZN algo changes. Claims AI optimization which AMZN explicitly blocks. Razor thin margins, neg op leverage. All peers went BK in last 3yrs.

@HaydenCapital Nov 15

Fred Liu on X

It feels like Bromberg might be able to turn-around the Unity story after-all. Was impressed with his admission of Unity's prior mistakes, and fact is, the new Vector product is working. Also I wasn't aware of the long-relationship between JR and Bromberg. In these turn-around situations, it always seems to work better when the new guy is familiar / trusted, instead of a complete outsider without buy-in from management or the team. Curious to see how this unfolds... $U https://t.co/u9ntzroZnR ** So, as part of the runtime fee, you raised prices right off the bat. So, you gave them what they wanted right away. MB: Yes. But as you think about the business going forward, I mentioned before the fundamental tension does still exist. We don’t have smartphones growing at the rate they were, where you’re basically surfing this secular wave. You are delivering ongoing value, every time these games are run, 80% of games or whatever it is, they’re running on a Unity Runtime, which you’re not benefiting from. At the same time, it is zero marginal cost software, it’s not like it’s costing you for it to run. That’s running on the phone, on someone else’s power and whatever it might be. So what’s the solution going forward? What was the confidence that Unity was lacking that you think they can deliver, that they weren’t previously? MB: It is my view and I think it’s now really the whole company’s view, that there are other areas of massive upside in our business, and I’ll give you a few examples. The first and most important one is our advertising business. So, the real challenge coming into Unity, by the way, coming in, and this also goes back to the runtime fee, is nobody can figure out how the advertising business and the game creation business were connected to one another. Beyond the fact that you had the customer like, “Hey, click this button over here and sign up for ads”. MB: Yeah, but there were often different people inside the same customers. So, there’s the developer and then the person buying an ad, maybe they’re not even the same person. And by the way, we had done an acquisition and so we had two different groups of people doing this and when I first started, the investors would always ask me, “Shouldn’t you just split these things up? What do they even have to do with one another?”, and in many ways that core question was also one of the drivers of the runtime idea, because the idea was no, no, no, the connection is going to be in the business model, not in the product. So because what we’re going to do is we’re going to raise prices so substantially, but we’re going to say, “Hey, you don’t have to pay that if you buy advertising from us”. Yep, that’s right. MB: So, actually we’re like, “Hey, we’re going to make sense of this acquisition we’ve done”, we’re going to make sense of these business units that aren’t integrated, by creating a business model which unites them. But also, sadly flies in the face of what customers want and articulates no additional product value so that’s just a bundling, which just feels like you’re jamming something down my throat that I don’t want. If our advertising product was more effective and more efficient, people would use it on their own. What did AppLovin get right? Because this is sort of the period ATT comes along, Unity laughs at it, “Not a big deal, doesn’t impact our business” — turns out it did impact your business. Meanwhile, AppLovin comes along, acquires MoPub, just starts really crushing it, obliterating you in particular. What did they figure out that you didn’t? And how are you going to compete with them going forward? MB: Yeah, we missed a cycle of technology investment. While we were integrating acquisitions, while we were thinking about business models and ways of getting folks to buy more advertising by bundling products, they were building a completely new machine learning stack that was fundamentally more effective and efficient than the one we were operating on. We were on a old style algorithmic ML, really not even a deeply ML stack. Much more deterministic. MB: Yeah, they were moving to neural nets and into the future. Which was the way you had to deal with ATT, was you were losing that deterministic signal, so you had to be in a probabilistic world. MB: That’s correct. And so, that’s the thing you should be up all day and night thinking about. Not movie effects. MB: Yeah, exactly. Or, “Hey, my ad business is fundamentally uncompetitive, how can I strong arm customers into buying more of it?”, the answer is the product’s uncompetitive. How do I make the product competitive? Once the product is competitive, we have all sorts of opportunities and that’s what I mean about getting out of the box. And so, what we did was we built a modern self-learning neural net system from scratch, with some of the best engineers in the world, called Vector AI, and we launched it and it had an immediate, and market positive, impact in our business. You’ve talked about using Vector AI to basically incorporate gameplay into understanding the target. How does that work? MB: Yeah. So, the part one of this was, “Hey, let’s be fundamentally more competitive on our ad business”. Part two is, how do you think through, as you mentioned, those real connections between advertising, game creation, and the runtime? What actually connects those things? And what connects those things is the need to have a really deep and clear understanding of the gaming consumer, because that sits inside how you succeed in all phases of the game business. Whether you’re prototyping a new game, and want to understand how people are behaving in that game, and what’s engaging them, and what’s causing them to transact, and what’s causing them to quit, and what’s causing them to make friends, all that is a data challenge. How do I interpret data which we can have access to through the runtime, as a way of better understanding how to build a game? And then when I’m operating in live service, how do I use that same connection to consumer understanding to optimize my live service?