MountainTimeInvestor

Publishing quick hits and deep dives on stocks and tech trends as fast as I can write them. $ABCL $PANW $FIGR $ZM $RDDT mountaintimeinvestor.substack.com

@anni_sen It makes no sense to buy $CBRS at these prices. Best case scenario is beyond priced in. This is how we enter bubble territory, unlike the AI-bubble narrative from last year.

Investment banks using retail for exit liquidity. $CBRS Two customers only.

$DRTS seems to be truly groundbreaking in its early GBS study data release, according to Dr. Joshua Palmer at Ohio State University: “No, the only other time, like I mentioned, the only other time I’ve ever seen a recurrent glioblastoma show a complete response is CAR T-cell therapy, which obviously caused, like, a huge uproar, was published in the New England Journal…Outside of those initial kind of, you know, responses that, like I mentioned also, were not sustained, so they don’t go the tumor went away, but then comes back because of a currently immune sort of response and how the GBM is working. Outside of that, there really haven’t been trials that show complete responses.” “That’s why I think this therapy, because of, like you saw the preclinical data and how this mechanism works, I think just tells us this is an exciting area that’s causing responses that we otherwise have never seen.” “This is one of the few times we’re actually seeing true responses in the lesion, leading to, so far a sustained response, so I think that’s the exciting thing about it.” Alpha Tau Medical Study Result webcast, 5/11/26

$ABCL CEO Carl Hansen highlighted a competitive advantange at the very end of the BoA call coming from owning their manufacturing facility, which has been alluded to in prior calls. $ABCL has more flexibility to manage its pipeline and targets before filing patents to protect IP as they do not need to share any data with third parties until IND-enabling studies. This is a subtle point that could compound into a larger advantage over time, accelerating to First-to-Market opportunities and clinical trials. "Now that we control manufacturing, we don't even need to file patents until we get close to the clinic. And we are, I think, routinely going to be trying to fly under the radar as long as possible so that we get a really substantial lead in moving programs that we have conviction in." - Carl Hansen, 5/13/26

@EndicottInvests Congrats on the pick! Curious what made $NBIS stand out as a winner over $CRWV ?

Congrats to retail for getting $NBIS right and being early. Some of you are up 10x, many of you are up 3-5x. The best part about this run is we’re just getting started. $NBIS is a $58B company. That will be peanuts to where we are in 3 years. Just my 2 cents

$FIG has a huge opportunity to dispel SaaSpocalype narrative this afternoon. If they grow 40% and show improving Net Income, tough to argue Claude Code is eating $FIG’s role in the enterprise.

I used to think so, but I watched $RIVN , $FIG , and $FIGR all rip past their IPO prices only to crash and end up trading well below their IPO prices. Nobody wants to be stuck holding the bag when that happens. IPO’s are meant to price at a fair value, then the free market is going to do its thing. There will never be enough shares for all investors that want them at the IPO price. I remember $RIVN having similar hype to Cerebras, it priced at $78 per share in 2021 and now trades comfortably in the $14-18 range leaving then institutions that held their IPO shares far in the red.

This is so dumb and EXACTLY why the IPO market is broken. $CRBS is going to open $165 ABOVE the listing price which has already been moved up multiple times. Way too many people are going to be left holding bags. Need a much more efficient way of doing this.

“The market I think rightly does not want you to talk about a platform. They want to see what is the outcome of the platform. So for the last two years we have been setting that up.” - Carl Hansen Only a leader who values execution would say something like this. Outcomes are what matters. Despite the share price volatility, the long-term $ABCL thesis has largely remained unchanged, and it’s the “show me” culture that provides confidence this company can deliver. $ABCL is not going to exaggerate or over-promise, but I believe they are positioned to over-deliver with 635. Phase 1 data provided the evidence. Thanks @JackPrescottX for the posts!

This very much aligns with my AI experiences

$PANW is just over 5% of my equity portfolio and has been on a nice run over past 3 months as the market slowly learns that @AnthropicAI is not able to replace enterprise identity, cloud and network security stacks. $PANW was an easy buy below $180 as they are positioned to become the largest pure-play cyber platform available to large enterprises. AI adoption drives enterprise cyber spend, and $PANW platformization strategy creates a strong a moat in a growing market. All signs show they are on track to double revenues by 2030 as this company has shown unbelievable execution under Nikesh Arora. Here's what I wrote on Reddit and Substack earlier in the year: March 2026: Why is the market sleeping on PANW reddit.com/r/ValueInvesti… Feb 2026: PANW Q2 FY26 Earnings: you can't vibe-code cybersecurity software mountaintimeinvestor.substack.com/p/panw-q2-fy26… Jan 2026: PANW: Largest and best-in-class pure-play cyber platform plans to double revenue through 2030 mountaintimeinvestor.substack.com/p/panw-largest…

@ScrooogeUncle @CapitalOne @SoFi And just bought Brex, which I thought was actually a very interesting deal.

@MtnTimeInvestor @CapitalOne @SoFi Also, look at P/S and forward PE It’s currently trading at book value $COF

Guys, you should be thankful that I give you all this information and advice for free. 😀 @CapitalOne is a much better investment over long term than @SoFi or any other fintech or banking stock Read all the screenshots below and you’ll realize why. $SOFI $COF $PLTR $ABCL

I agree, and think incumbent SaaS has an opportunity to make AI work for enterprise customers. Tokenmaxxing is just wasted spend if it doesn’t help to achieve a specific outcome. Not sure how many strong earnings it will take for the market to realize this, but we learned from the rise of cloud infra companies that just because you’re the worlds biggest company doesn’t mean you can eat Software. Otherwise all software would be owned by AWS, Azure, GCP and Oracle and few other vendors would exist. LLM’s are already becoming a critical layer to the enterprise tech stack (just like cloud), but you still need software (and agents) to make it work.

Interesting saas bull case: current uneconomic spend on tokens/tokenmaxxing = LT saas cos better positioned to build workflows from tokens + resell - cheaper vs for enterprises to build from scratch as saas can amortize across customer base (expertise/contributory customer data, as well as infra costs)

@PythiaR Token usage in an enterprise environment is just wasted spend if it doesn’t help achieve an outcome.

Tokens are not the same as eyeballs because tokens directly monetize where eyeballs don't necessarily. HOWEVER, tokens become a corrupt measure when companies incentivize their consumption with no real ROI. Till now I think token usage etc. was a useful indicator, but with more companies putting their thumbs on the scale I think it's more suspect.

@MitchMartan98 What are your thoughts on $CRWV here? Maybe they’re included in the etc.?

BTW if this $NBIS did anything, it confirmed that the need for power and compute is still insatiable. Nebius is clearly the #1 Neocloud but the whole stack will continue to do well -> $CIFR $GLXY $IREN $WULF $RIOT etc.

The AI-infrastructure trade is trying to identify companies that will benefit from the massive capex dollars being spent today, not necessarily expected future revenues. This trade crashes if demand for AI slows down somehow. Cybersecurity risk and AI slop are the two biggest factors I've observed that could slow down demand for AI. $MU $AMD $NVDA If you think @AnthropicAI will take over the world, data centers are a critical input.

@realroseceline $SHOP $HOOD

One thing investors miss in the short term is separating deterioration in business quality from temporary investment cycle pressure. Margin compression gets treated as if the moat suddenly disappeared overnight, when in reality what is happening is that a dominant platform is deliberately reinvesting to strengthen the ecosystem and expand market share. 🌹

@petergyang Well said. It’s a tool that can accelerate a goal or outcome, and your choice how to use it.

I feel like AI gets people to average quickly but if you really know your shit (or you actually care enough to go the extra mile) you’ll be more in demand than ever because people will long for craft in a sea of slop

@tech_bag_ @levie Def agree. I think attempts to replicate the FDE model will ultimately show how exceptional $PLTR is, but it makes sense for others to try.

@MtnTimeInvestor @levie And it’s not just technically complex to deploy value add agents, but the true complexity actually lies in the particular enterprise and particular process. Which makes me curious how effective the FDE model will actually be.

Forward deployed engineers, or equivalent, are about to become one of the most in-demand jobs in tech. And one of the most important functions for AI rollouts. Deploying agents is far more technical of a task than most people realize, often far more involved than deploying software. Software generally works the same way every time, and generally for the past few decades has been updated versions of an existing technology or concept (which basically means easier for the enterprise to update their workflows on a newer system). With agents, you’re actually deploying the equivalent of work output within the enterprise. The customer is effectively using you as a professional services provider for a task, which they expect to get solved nearly end-to-end now. This means you need to actually deeply understand the business process as a vendor, and get the customer from the current to the end state seamlessly. Companies need help figuring out which models will work best for their workflows, they need extensive evals setup often, they need change management support for workflows, they need to get their data setup for the agents, and constant tuning of the agentic system for their process. Massive role in tech now. And another example of the kind of highly technical work that AI is creating.

Bull case / bear case on the AI infrastructure trade: I own $MU , $AMD, $NVDA $HUT and $CRWV because I believe we are in the early stages of an massive buildout to bring AI to knowledge and phyiscal work. I think we're going to need a lot of infrastructure in the future. Whether you want to own these names or others at today's high prices depends on how durable AI demand will be. Bull case: Owning these names is a hedge against Anthropic taking over the world and becoming civilizaions largets monopoly. As long as the data centers are built, $MU, $AMD and $NVDA will massively benefit. If the data centers are built and used, $HUT and $CRWV will also massively benefit. Bear case: Somehow, todays demand for AI in the enterprise will slow, or compute will become so efficient that the hyperscaler and neocloud spending will slow down. The data centers we thought we needed won't actually be used for a while. One way for this to happen is that companies realize building agentic systems are more difficult than spinning up a web app on Claude Code. Or the cyber risks of agentic systems are too daunting. The slowdown won't be because what's possible with AI isn't valuable, it will be because its more difficult and costly to achieve outcomes than we anticipated. In the .com era, everyone thought that just because you had a website you were in the future. Today is about simply using agents, and nobody seems to be that interested (aside from $PLTR) about what outcomes those agents can achieve.