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Legit check 👀

I will say that Ad revenue will be the first to go vs. GOV take rate as agentic commerce requires no UI interaction while take rate on orders --> 0% requires access to DASH distribution network (much harder). Surprised this wasn't brought up tbh.

ECON 101 First Class: economic profits i.e. DASH GOV take rate gets competed away. Incremental apps after this point won't be created. This applies to 80% SaaS GMs as well. Of all the critiques to Citrini's argument this isn't one of them.

@DeanTTraining Dumbest shit ever. This take assumes protein and carbs are competing, which they aren’t at normal calorie intakes. On 2k cals, 50% carbs = 250g. To begin to crowd out carbs you’d need protein > 250g. Bodybuilders/athletes? The 250g becomes 300-400g.

I’ve been going out of my way to LIMIT my Protein intake lately This is to help me build MORE muscle This may sound counterintuitive to some, so allow me to explain: - You only need a limited amount of protein before extra intake stops providing additional muscle-building benefit…realistically ~.75g per lb of bodyweight is probably good and ~1g per lb bodyweight is definitely plenty - You only have so many calories to allocate each day (cut, bulk, recomp doesn’t matter…the budget is the budget) - When you overshoot protein, those calories must come from somewhere…this means you’ll need to displace calories from carbs or fats - Carbs are what drive training performance - Better training performance = more robust stimulus = more growth - So, if you’re eating more protein than needed…this is BY DEFAULT going to result in you eating fewer carbs than is optimal which means poorer performance which means a less robust stimulus which means less growth The goal for building AS MUCH MUSCLE AS POSSIBLE is simple: - minimum necessary protein - minimum necessary fat - carbs comprise the rest of your calories This means the specific formula is: - Calories in line with goal - Protein ~.75-1x BW - Fats ~.25-.3x BW - Carbs fill in the rest This is why “more protein” isn’t always better….once you pass the threshold, every gram you add means a gram of carbs you lose! A few notes: - “Too much protein” is not an issue many people have…this post is for folks that are really looking to nail every little detail to get the best body comp results possible - This post is all about optimization for a very specific goal…it is discussing what’s best in general in theory, again, for a VERY SPECIFIC GOAL - Individuals should always keep ADHERENCE/COMPLIANCE top of mind when making any training/dietary decision - So, when one of you comes back to me and tells me you don’t feel as full on .75x BW (protein) as you do on 1.25x BW and it has caused dietary adherence issues in the past….just know that my advice to you would be to stick with the 1.25x then but be accepting of the trade offs on the training performance/muscle growth front!

@TMTLongShort …Priors converge, trades crowd, thesis decay accelerates. Whichever AI Lab is the first to the party will absolutely print.

@TMTLongShort More open-ended prompting/research means compute scales non-linearly with each degree of research freedom. More possible paths = more cost. Cost pressure forces models back to familiar angles in the training data…

Long rambling thread (sorry). A common pushback on the AI maxi view of knowledge work disruption is that AI is rate limited by human adoption. This assumes that existing businesses will be the primary customer of AI as opposed to new AI-natives and a baby AGI is at the mercy of the incumbents for adoption. And when you bring up the notion of AI-native businesses competing with incumbents you get the pushback that these AI-natives lack the deep expertise and process knowledge accumulated by decades of employees contributing and a business operating. How I think about it: Most humans are dumb. Most contributions are stupid. Whatever was contributed that is of value can be replicated by taking the raw inputs that the human contributors themselves ingested over the course of a career. But with a caveat that you need a sufficient level of model-intelligence. Let me put it in finance terms given the likely audience for this tweet. You want to build a “buyside analyst in a box”. You have three choices: A) go find a bunch of funds to partner with. Observe their analysts, tag along to mgmt meetings, watch them build models, watch them talk shit on fintwit and ultimately attempt to replicate the workflow of said analysts. Time consuming but not impossible. The problem is any fund worth observing probably is already doing great raking in performance fees and has no incentive to collab unless you as the AI partner are willing to cede a material portion of future economics to the fund. You have the benefit of a ready-to-buy customer base via the funds you partnered with but the scale of adoption is limited as you then have the Herculean task of convincing PMs at every other fund that your digital analyst is superior. PMs are your customer base and because the are slow distrusting customers PMs are also your bottleneck. 🛑 B) you decide that you have a pretty good sense of what an successful buyside analysts workflow looks like and decide that really the only major differential between a shitty analyst and a rockstar is depth of sector knowledge and communication style to their PM. You therefore look high and low to find repositories of priority data in the form of investment memos, sellside research, data feeds, and everything else that a typical analyst ingests. Less nuanced vs option A but it’s lighter weight and you don’t need to give up economics since your not riding someone’s proprietary data. But the bar for how good your digital analyst has to be has just increased substantially. Because it doesn’t have access to internal fund memos it has no clue how the PM operates or the characteristics of a good investment memo or process. In theory this analyst is better than their human counterpart… but only by the difference between the breadth of information this AI analyst can ingest and synthesize vs a human. This AI however is severely hobbled. It’s reliant on the same structured data sources we as analysts rely on. Sellside research still has a midwit human in the loop. Expert network transcripts still require the human to ask a question (or the inferior tegus bot). This digital analyst will have a hard time convincing PMs to adopt it…. And that will take time and require extensive trial periods. Now both insufficient data and slow PM adoption are bottlenecks 🛑 C) AI-first approach. This starts with a core premise: everything a human knowledge worker has ever done or contributed to is a distillation of prior data it has ingested somewhere else that it has then repurposed to address a specific use case. And that use-case is to convince a PM to buy or sell something without getting fired. But zoom out. That analysts recommendation is an input within a larger process. The PMs task is to generate superior returns by converting data ingested by his analysts into bets that are asymmetrically skewed to his benefit. (Continued below)

@TaimurH67009511 No clear story in SW to drive revisions vs infra/semis. “Claude can’t code enterprise SaaS” doesn’t fix pricing + seat pressure esp. at high valuations ex. SBC. IMO LOs won’t step in without a clearer narrative, and pods would rather put long exposure elsewhere. Thoughts?

All I see is the same, standard defense of saas. Makes me wonder why such a difference between apparent sentiment and stock performance?

@ContrarianCurse Your average bloated cursor app with high architectural entropy means OSS becomes difficult/unreliable requiring more engineering manpower. Flexible pricing and full pane solutions i.e. ddog wins. DT is still too enterprise focused to benefit here imo

Am I a smooth brain for thinking that if we are going to be generating metric shit loads of code that DevOps and Observability win? Don't you need a way to organize and iterate and then see if its fucking things up?

@TradexWhisperer @DividendDude_X I know you did not straight line 52% revenue growth in your DCF… How did you end up with that valuation???

Yup. Everyone, repeat after me $HIMS is not a GLP-1 drug company $HIMS foundation was not built on Semaglutide There is a huge misunderstanding of $HIMS core business by the Market. This time around, I do believe the market inefficient where it does not understand. It's almost baffling. Look at $LLY, it's is down -6.5% on weigh-loss drug sales miss while $HIMS is down 15% on the same new and HIMS core business was NOT built upon Semaglutide, it was only 5% of their revenue last quarter. By contrast, $LLY's directly competitor is up by 1%. Me No Comprendo. Hims and Hers is a health and wellness platform with telehealth, prescription medications, and wellness products/services While $LLY earnings miss might be a concern for the weight-loss drug market, it doesn't directly impact HIMS's diverse product offerings and overall financial health. Rather, Market should focus on HIMS's strong revenue growth and expanding subscriber base indicate a solid performance and potential for future growth. I have never seen such an undervalued company even by DFC Model standard. It's 73% undervalued as of yesterday's price. That's how much growth they are seeing. Today's valuation? Even cheaper. In Q2 2024, HIMS reported $315.6 million in revenue, a 52% year-over-year increase. Do your math. Be like HIM (DD) and buy the dip.

Hims & Hers $HIMS under $19 is literally a PEG of around 1 this is stupidly cheap… Hims & Hers doesn’t need GLP-1 to succeed it’s just a bonus, them falling 15% due to GLP-1s is just dumb. This is a buying opportunity in my opinion. 🤷‍♂️

@0xUmbreon 👀

@holisticnicola @rektdiomedes @Derek_Fitness

Did you know polyester underwear was studied as a contraceptive? 14 men wore a polyester sling on their balls for a year. All became azoospermatic (infertile) within an average of 150 days. All of their balls got smaller. Interestingly, after they stopped wearing the polyester sling, their sperm count returned and their ball size returned to their previous levels. The study concluded that wearing polyester underwear is an acceptable form of contraception in men. Keep this in mind when buying underwear.

People who locked in mortgages at 2% in 2021.

@heysxri i just put night shift settings on max on my phone, works pretty well

One thing for sure it's easier to flip shitcoins than discussing geopolitical shitshow.

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@frank_capital ty

@frank_capital what’s the indicator called?

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