To The Moon

As always, these posts are more of a brain dump of “what I’m thinking” about…And lately I’ve been thinking about a pattern that keeps showing up when I study the biggest infrastructure winners of the cloud era, and what it means for AI companies today. Here’s the general idea: the biggest infrastructure winners of the cloud era monetized the core consumption primitive of the platform. In the cloud era, that primitive was compute, storage, and network I/O. In the AI era, it increasingly looks like tokens. Let’s unpack. When cloud computing first started taking off, the core primitive of the platform was very clear: compute. Everything that happened in the cloud ultimately boiled down to compute cycles running somewhere inside a data center. Storage, networking, and databases all mattered of

By now I’m sure everyone has seen Jack Dorsey’s tweet. For those who haven’t seen it (or don’t care to read it), he announced a ~40% headcount reduction at $Block, Inc.(XYZ)$ (formerly Square). This is a massive move… You rarely see headcount reductions this large. Throughout the post he used the word “intelligence” - which really can be replaced with “AI.” “we're already seeing that the intelligence tools we’re creating and using, paired with smaller and flatter teams, are enabling a new way of working which fundamentally changes what it means to build and run a company. and that's accelerating rapidly” and later: “we're going to build this company with intelligence at the core of everything we do.” I’ve broadly seen two different reactions to thi

Memory stocks have taken over recently. If the early AI “trade” was compute, the current trade is memory! Over the last year: $SK Hynix, Inc.(HXSCF)$ is up >300% $Samsung Electronics Co., Ltd.(SSNLF)$ is up >200% $KIOXIA HLDGS CORP(KXHCF)$ is up ~1,000% $SanDisk Corp.(SNDK)$ is up >1,200% $Micron Technology(MU)$ is up >300% $Western Digital(WDC)$ is up >400% This is by no means an exhaustive list of memory related stocks, but it should give you a flavor of what’s happening in the stock market for memory related companies.

Another week and software continues to grind lower. However, despite all of the carnage, there was another big winner this week! $Fastly, Inc.(FSLY)$ is up ~100% over the last week. The week prior, $8x8(EGHT)$ had the big week (they were up ~70% in a week). Always an opportunity somewhere… I thought I was done talking about “is software dead” after the last couple weeks Clouded Judgement posts, but I just had more thoughts I wanted to share… I think two things are true. I think people are simultaneously under and over estimating the impact AI will have on the existing software complex. The difference is the timing. Overestimating in the short term, and underestimating in the long term. I see a lot of argu

Another week and software continues to grind lower. However, despite all of the carnage, there was another big winner this week! Fastly is up ~100% over the last week. The week prior, 8x8 had the big week (they were up ~70% in a week). Always an opportunity somewhere… I thought I was done talking about “is software dead” after the last couple weeks Clouded Judgement posts, but I just had more thoughts I wanted to share… I think two things are true. I think people are simultaneously under and over estimating the impact AI will have on the existing software complex. The difference is the timing. Overestimating in the short term, and underestimating in the long term. I see a lot of arguments claiming software is dead because everyone will just vibe code their own software. I don’t buy this at

Last week I wrote a post titled “Software is Dead…Again.” Since then, $iShares Expanded Tech-Software Sector ETF(IGV)$ is down ~20% (in just 1 week!). If software was dead a week ago what is it now, down an incremental 20%?! First - some fun stats The median NTM revenue multiple (cue all the comments “he’s still talking about revenue multiples?!?”) is 3.6x. This is the lowest it’s been in the last 10+ years. For the revenue multiple haters, the median FCF multiple is 16x NTM FCF, for median growth rate of ~20% (alas, once again, cue another set of haters, saying none of the FCF is real and it’s all sitting in SBC). Can’t escape it, maybe software is a zero with no valuation support. Was good while it lasted. 39% of my software index is trading <

Well, software is dead again! At least investor confidence is dead… The median NTM revenue multiple for the cloud software universe is 4.1x. That’s the lowest it’s been in 10 years (it was about the same very briefly in 2016, when the fed started hiking rates for the first time after the GFC ZIRP period). The current median FCF multiple is 18.9x. The previous low in the last 10 years was ~26x! However, the “narrative violation” metric here is the growth adjusted revenue multiple median is still 0.35x vs the pre covid average of 0.28x (you can see the graph below, I post it every week). So while multiples are at historical lows, so are growth rates. The FCF multiple is the most telling, however. With the current median ~30% lower than the prior low point in 2016 So what’s going on?! I think

I have a growing conviction that 2026 will be the year of multi modal AI. There are a handful of trends all coming together at the same time that are set to converge. Multi-modal models get good enough. Inference is getting cheaper and faster (cost curve is important). And the real world starts showing up as first class input. I really believe AI will stop predominantly living in text boxes and instead in places humans actually are. For the last few years, AI has been overwhelmingly text first, and for good reason. Text was the fastest path to usefulness. It was easy to collect, easy to tokenize, relatively cheap to serve, and generally didn’t have the same latency requirements. If you were building an AI product in 2023 or 2024, starting with text was the rational choice. But text always

As always, these posts are more of a brain dump of “what I’m thinking” about…And lately I have been thinking a lot about “legacy SaaS",” systems of record, etc. I wanted to write another post today in a similar vein.When I think about how people and companies interact with software today (and for this post when I say software I’m talking about legacy SaaS systems of record) the pattern is generally pretty simple. The system of record is a single, organized place where a human goes to look something up, understand the state of the world, and then take some sort of action based on the information they gathered from the system of record. Like opening Salesforce to check pipeline before updating a forecast, or pulling up NetSuite to reconcile numbers before approving a close. And more often th

I have been thinking a lot lately about education in AI. More often than not, I am seeing education as a core go to market problem (but sometimes an advantage) in AI. The companies that are best able to educate the world and their prospects are winning. Part of the reason for this is that everything in enterprise AI is still so new. Many people, teams, and organizations are facing what I think of as a blank canvas problem. They know AI is powerful, but they don’t even know where to start. Where to use it, where to augment existing workflows, where to create net new workflows, etc.What surprises me the most - even when teams think they know what functionality they want build, it’s not obvious to them how to build it. Build versus buy is just where it starts. Even inside “build,” there are d