whatstheofficerproblem

Haven't looked at Harrow. I am not a biotech specialist in that I don't have a PhD or depth on broader topics. Casting a wider net here when it's not your core competence and looking at more than the typical 3-4 names would imo work against you. The nature of this sector is that it's very hit or miss. You'd be risking 50% to gain 10% or even lose 10% more even on good data. You need to be a masochist to enjoy biotech and that is simply not my thing. Will likely start looking around when LQDA/INBX play out.

I have told myself this a lot of times over the last few years, didn't end well. I think I'm not alone in that boat, which is why a lot of folks have an aversion to SW now.

Leaving L.A. anyone? I just can't live here. The policy and everything are absolute shit, taxes are daylight robbery esp. capital gains. Can't ever buy a house and plant some roots. There are way too many cons and too little pros. I pay all this money in tax as a non-citizen and what do I get? Get treated like a second class human being, wait 70 more years for a green card? I don't know anymore.

No. They will fade semis or more so opticals to rotate into the CPU play now. See ARM, AMD & INTC. This is a zero sum flow game and software thus far has nothing to show for as to attract their capital. For them, easier ways to make money in AI verticals. The best activity you'll see here is likely these names being up on folks covering their shorts.

As 3Q26 edges closer, Tegridy is up ~25% as of today's close (5/6). I know not if this will last by end of the quarter, but who knew running our own play pretend fund could be so fun.

You nailed it. 109 alone is worth ~$10B, 106 would add onto that and I expect the data release to be this week or next. Don't have a line to management or analysts here, but guess would be in best interests to strike while iron is hot. Two successful drugs would imply they have a 'platform' and platforms esp in cancer trade at retarded premium even when the underlying drug is shit as you have seen with a few other names discussed on the forum.

Don't lose sleep over it. I could have got my contracts for a few cents cheaper had I not thought we would have gotten a ruling by end of March and rushed to buy the calls.

Depends on your conviction in the case AND timeline. If you think we get a favorable judgement before 2H26, then the Jan 27s have very juicy r/r assuming stock goes above $100. If you want less risk and more duration, say judge might not rule this year and might not rule favorably, then 28s will get you through the tougher times if they exist. I you want to say, I'm good and I don't need to worry about all that, then just buy the underlying and collect option premium like @lnofeisone. I personally think we get a favorable decision before August. Hence put all my money in Jan 27s. I also think we see a step function change i.e. acceleration in revenues for Yutrepia right about starting 1Q26 which will be reported next week as this was the timeline for organic DPI inflection at UTHR. Should help the stock break past where it is range bound right now. A bad UTHR print tomorrow morning will also certainly help.

I think they win. Lot of good posts in the LQDA thread.

Can COHR & SNDK go to $1000 & $3000 per share respectively? I'm skeptical but assuming they even go there, the factor swings in AI names would be very bad for my mental health and for the portfolio as a whole. LQDA for now is range bound given the drug is already executing. If left alone I think LQDA would be a $500/sh stock by 2028 which implies a 10 bagger from my cost basis. If suit goes our way then 5 bagger from here when MRK acquires them. On one hand I'm looking at a very 'safe' 5-10 bagger while on the other I'm putting more money 'at risk' with AI names for at best a 2x return from here. LQDA will be a career defining trade for most involved in the name, so I positioned it as such.

1) Would be terrible capital allocation from a portfolio management perspective. 2) Sharesight doesn't allow me to add options. This is also why I sell into the print instead of just buying puts to hedge. I hold in straight in the fund(s) and friends and family accounts. Degen behavior limited to my own life savings.

At an abstract level if you took the marginal price setters of stocks in aggregate (i.e. everyone ex passive/algo), I suspect looking-back on this moment, one would conclude this was the time of max uncertainty of business models and terminal value. Therefore, analogous to you holding a 30yr bond and increasingly uncertain about duration, you'd swap to a T-bill and near term certainty. At a meta level that's what's going on, and because a narrow sleeve of the market is putting up growth (any fundamental KPI growth) today a large amount capital needs to find a home there. Or cash. Sounds absurd to think its Semis or... Cash. But here we are.

Yes, it's not a pair trade anymore. It's the ONLY trade you're allowed to make at most platforms which make up most of the market flows.

Welcome to the new age. IGV will continue to go down more whenever a software co misses than go up whenever one beats. It's all just flows at this point, this money is funding semis and semicap. If software is getting bid up, just know that it is degrossing and regrossing from a risk standpoint as positioning in semis is very overextended.

Basically Bill walked people off a cliff. Guided Adj. Op Margin down. You should keep in mind that beating consensus numbers doesn't amount to jack shit these days. You need to beat buyside's bogeys or you're a funding short. Revenue growth seen as not organic as it had acquisition tailwinds of like almost 200bps, then said Iran war headwinds lmao. cRPO growing under 20% is not what people wanna see. Then you also add in the fact that he did an accelerated buyback at a much higher price when he knew the print was going to be bad, that has a lot of folks pissed and rightfully so. "Don't fall for this parlor trick that a single button will replace 20+ years of software excellence" he said on the call. Also should know that he quoted WEB & Ben Graham with the whole weighing machine and voting machine analogy. That is a contra indicator in my eyes. PTSD from Sardar Biglari & Gary at Restoration Hardware.

Congrats! Baby seems very healthy. They'll grow up fast.

@LC, I think we all know the guy in the office will make a deal with the devil if the devil was prepared to kiss his ring. There are no second order thoughts in the WH right now, but that will change. You're also severely underestimating "majoritarianism". A handful of executives won't stand a chance when the entirety of their workforce wants to push back. @Spekulatius, they already classified it as such which is why Dario has been trying his best to kiss the ring. Palantir covering for them is the only reason there isn't a complete meltdown. Interesting article. https://blog.mozilla.org/en/firefox/ai-security-zero-day-vulnerabilities/ "A gap between machine-discoverable and human-discoverable bugs favors the attacker, who can concentrate many months of costly human effort to find a single bug" "Encouragingly, we also haven’t seen any bugs that couldn’t have been found by an elite human researcher. Some commentators predict that future AI models will unearth entirely new forms of vulnerabilities that defy our current comprehension, but we don’t think so. Software like Firefox is designed in a modular way for humans to be able to reason about its correctness. It is complex, but not arbitrarily complex"

I am a 'techbro' myself. Which is why I find the whole "AI saar" debate all the more appalling. It's wall street making the most noise followed by folks with vested interested via the model providers. Most tech employees see right through this.

All good points. But FICO's power comes from the fact that Fannie Mae and Freddie Mac mandated its use for decades. It is literally a govt enforced monopoly. No model provider has anything close to that. Nobody is required by regulation to use Gemini or Claude. Every enterprise is choosing voluntarily, and can theoretically switch. That enforcement led to the entire financial system being calibrated to their specific scale. Replacing FICO means recalibrating everything but the outputs wrt LLMs are very different, they are variable and not standardized. If JPM switches its call center from Gemini to Claude, the customers get slightly different phrasing at best. The downstream systems don't need to be rewired and recalibrated. There's no equivalent of "the entire securitization chain is built around this specific number." When was the last time you used a wrench vs a swiss army knife? A wrench is harder to replace than a Swiss Army knife because the wrench fits the specific bolt perfectly. LLMs do everything, which paradoxically makes them more replaceable. The more general the tool, the more substitutes exist. FICO again had zero comp for decades while the model space already very crowded. Switching from one LLM to another requires updating an API endpoint, adjusting some prompts, and running regression tests. It's not trivial, but it's not anaconda vice kind of lock-in either. If I were to guess, these model providers would at best have more SaaS like pricing power i.e. 10-20% annual increases that annoy customers but don't trigger defection. Re: Labor math, I once again agree with you. But how many JPMs do you think exist in this world? There simply aren't enough enterprises that will spend the amount of money required to keep these monsters spending. Let's say there are and these guys replaced enough labor and helped cut tremendous costs. But the toad has now tasted swan meat! The pandora's box is open. Model providers will start raising prices by how much ever the labor-replacement math supports. Enterprises now used to their new lush margins will start screaming. The industry associations will lobby. And the model providers will keep raising prices because the switching cost is astronomical. Just like FICO. Then, five to ten years later, some combination of open-source models, regulatory intervention, and enterprise coalitions will force the door open to competition just like VantageScore is doing now. But by that point, the model providers will have extracted enormous value during the lock-in window. Sounds too good to be true. Again, if JPM could save $50-70 million & Google charges $30M, that math is visible to every model provider simultaneously. Anthropic sees the same opportunity and offers to do it for $20 million. Microsoft undercuts at $15 million. The pricing anchor isn't the labor cost for long. It migrates to the competitive price almost immediately, because unlike FICO, there are multiple credible providers from day one. Labor replacement, while it sets a theoretical maximum from day 1, competition sets the actual price, and there's nothing structural preventing competition here. Also, labor replacement is also a one-time event, not a recurring extraction. Once JPM fires 1,000 call center workers, they're gone. The model provider can't fire them again next year. The savings are captured once, and then the ongoing relationship is just an API contract that's subject to normal competitive dynamics. Google can't say "pay us more or we'll rehire your call center workers." The leverage disappears after the initial transition because the humans aren't coming back regardless of which model provider serves the contract. You would also risk demand destruction here. If every bank replaces its call center with AI, the quality of customer service becomes undifferentiated. In a world where every bank runs the same Gemini-powered call center, wouldn't the bank running human powered centers become differentiated and command the premium? Commoditized service delivery leads to commoditized willingness to pay for it, which is unironically why call centers are cheap in the first place. If we go into the philosophical side of the debate, this is principal-agent misalignment. The person making the AI purchasing decision isn't the person being replaced. It's the CFO or COO looking at headcount reduction & their incentive is to minimize the cost of the AI contract, not to maximize what they pay the model provider. Every dollar they don't pay Google flows to the bottom line as additional savings. So the enterprise buyer is highly motivated to play providers against each other, switch vendors, threaten open-source alternatives, and negotiate aggressively. This isn't a consumer market where people pay for convenience and enterprise procurement is the most ruthless buying environment in business. Then we go back to singularity. If everyone is being replaced, no one has the money to spend, so at the cost of their margins, the companies firing and replacing with AI agents destroy each others' and their own customers which will kill their revenue stream. The whole economy goes to zero.

@LC, the thesis drift was assuming they stole the data, anyways I'll indulge. Companies do find ways to launder data usage through anonymization, aggregation, and creative legal interpretation and I'm willing to bet Sama & Dario are already doing this. I'd reframe the initial drift as specificity. Lumping data is moat across the board with a blanket statement was a lazy way me trying to make the point, but moats still exist what I was trying to say. For Bloomberg it really is the data, Verisk it's the cooperative structure, Epic it's the workflow integration etc etc. To your point on actuarials and so on, I mean sure, but again how will they get the data? Occam's razor, I don't think the companies using these models are actually foolish enough to not confine it to a sandbox and limit access. The lock-in aspect of your counter argument is something in the back of mind constantly as of late. But once again, I'd think companies are not foolish given what AWS did to them. In AWS' case lock-in worked because they had a 5 year or so headstart and there were only three credible providers. The model space already has a ton of comps though. OpenAI, Anthropic, Google, Meta's open-source, DeepSeek, Mistral etc. Just head to Ollama and you'll be assaulted by a large selection of models. Open-source here is viable in a way that open-source cloud infrastructure never was. If you fear lock-in, you can just run your choice of model locally. The oligopoly pricing scenario requires the open-source gap to remain large enough that enterprises can't credibly threaten to switch. From my point of view that gap is closing and enterprises retain leverage. Google can build a better insurance pricing model. Google cannot get licensed to write insurance in 50 states, build relationships with 30,000 independent agents, and earn an AM Best rating overnight is my thinking. Re: your point on the come to jesus moment for these old companies, I agree. But some individual companies within that category will still get destroyed by their own incompetence. That's always been true, with or without AI.

I alluded to this in my initial post. By the time start-ups gain the ability to rapidly catch up to the incumbents, the model providers won't stay solvent. Then again, Cloud computing was supposed to disrupt Workday & SAP, the mobile was supposed to disrupt Salesforce and open-source was supposed to disrupt Oracle. I think in each case startups did emerge and built a few incredible products at a higher velocity, but in every case the incumbents always adapted the same technology and extended their lead. If you want to build another workday today, you'd be compiling compliance across 50 states, ERISA regulations, ACA reporting, multi-entity consolidation, and union contract variations where AI has no edge. What AI helps accel was never the hard part to begin with is my point. Some things have to take time and decades of customer feedback to correct course, there is not shortcut for that. Your second argument actually predates AI. Large enterprises have always had the theoretical ability to build their own HR, CRM, and ERP systems. Google infamously uses myriad of internal tools. Think the reason most don't do it isn't the technical burden but opportunity cost. If we take Bank of America as example, their best engineers should be working on trading systems, fraud detection, quant strats and customer-facing products that generate revenue & not re-inventing payroll processing software. This equation doesn't really change if SaaS vendors are similarly using AI to make their products better and cheaper, while building custom means your internal team now also needs to maintain, update, and secure an AI-augmented system indefinitely. Not to mention the amount of "mess" AI creates when using it to code. I think there is a middle ground there in terms of AI enabling a new category of lightweight, purpose-built tools that don't try to replace SaaS incumbents entirely but pick off specific workflows where the incumbent is bloated or overpriced. So maybe we will see more of a death by thousand cuts instead of bullet to the head type of damage from AI. Then again, I am skeptical because "Time" is of the essence. In the short term, AI helps incumbents more than challengers because incumbents have the data, the customers, and the integration depth to deploy AI meaningfully imo. In the medium term start-ups, or challengers will use AI to attack the edges and we don't really know what happens long-term. I'd say the model providers might not stay solvent starting medium term.

Supply and demand issue. If every kid the US was say 180 IQ super genius then what would the value of that intelligence be in the country? It would just be the norm no? The reason AI has this wow factor today is because it looks smart and gets stuff done fast (allegedly). So all the enterprise clients and everyone else is forking over API fees to try and use it and get as far ahead in their own competitive race as possible. If every enterprise on the world has access to intelligence, i.e. the abundance of intelligence, what is the value of this intelligence? You're back to square one no? NOW will still be the same, ADBE will still be the same, WDAY will still be the same in terms of company and their prowess because they have access to same things all over again. It's like all of them hiring the same 1000 smart engineers, no piece on the chess board has moved.

LC, c'mon, they're obviously not that stupid. Enterprise contracts explicitly prohibit training on customer data, all the model providers have been forced to explicitly offer zero data retention options. While in no way do I trust them, if it ever leaked that they were secretly stealing that enterprise data, end result would be an extinction level event where you lose all of your enterprise revenue. Let's say these clowns try anyways right. Ok, if we take VRSK for example, their ISO division collects claims data from virtually every property and casualty insurer in the United States so they have like decades of granular claims history from fire to cars to house to everything which is reported by the insurer into their pool of data. No single insurer has the full picture, only VRSK does as they are the trusted aggregators, they have become the central nervous system of the insurance industry effectively. So assume the model providers somehow get access to the raw data here, which would be next to impossible, but let's assume. Ok, you have the data, now monetize it. But how will they monetize it? You'd be missing the actuarial models, rating algorithms, loss cost calculations, and statistical plans built on top of decades of cross-referenced data. Insurance pricing in America literally runs through Verisk's statistical agents. State regulators approve rate filings based on Verisk's loss cost analyses. There is a whole regulatory infrastructure aspect to the pricing of insurance. The co-operative structure they have going on, along with the data is the moat. Insurers contribute their data to Verisk because they get back something none of them could build alone in the form of industry-wide statistical credibility. A small regional insurer writing 5,000 home policies can't price wildfire risk accurately from their own experience. But Verisk aggregates across the entire market, giving that small insurer actuarial credibility it could never achieve independently. The more insurers contribute, the better the models get, which attracts more insurers. OpenAI can't replicate this by being smart. It would need every insurer in America to voluntarily send them claims data, and there's zero reason for them to do so when the Verisk relationship already works. I can much deeper into the Verisk context, but that is a post for the VRSK thread at a later date. Your question is a game theory problem imo. Let's say OpenAI secretly trains on Goldman Sachs' data flowing through their API. What have they gained? A model that's slightly better at Goldman's specific use cases. But Goldman is one customer. JPMorgan's data is different. Citadel's data is different. The proprietary value is in each firm's specific, unique dataset i.e. their positions, their strategies, their client relationships. Aggregating across customers gives you generic industry knowledge, which is already in the training data from public sources. The alpha is in the specific, and you can't use firm-specific data without revealing to everyone that you're doing it. These providers are competing with each other at the end of the day. The moment one provider is even suspected of training on customer data, the others will use it as a sales weapon and that competitive pressure creates a race to the bottom on data usage. Each provider is incentivized to be more restrictive than the others to win trust. If not it's very easy to just run the LLM locally for much of it's capability without risking your data getting stolen. This is already happening imo. Companies are fine-tuning models on their own proprietary data and keeping the resulting weights in-house. Bloomberg built AskB which is very good actually, Epic is building AI into its own platform using its own data. They're using the foundation models as a base and adding their data as the differentiation layer on top. The value flows to the data owner, not to the model provider. The model provider gets the API fee. The data owner gets the competitive advantage. So your argument has teeth in consumer data, but think enterprise data safe.

No. I need to outlive Judge Andrews. Not going to do anything that contains tail risk of an early afterlife.

Sure, where will they steal it from?