If you're new to investing, start with Subscription businesses.
$NFLX, $SPOT, $COST & $HIMS
That's exactly what I did when I started. If you have no idea where to even begin looking, subscription businesses are the easiest place to start.
These are companies where the majority of the money comes from one single source, and that's what makes them so easy to understand. You don't have to untangle a dozen different things to figure out how they make money, because it all comes down to people paying every month.
Netflix is the perfect example.
Almost everything they earn comes from people paying a monthly fee to watch shows on their platform. Those same people pay again the next month, and the month after that, so the company already knows roughly what's coming in before the month even starts. That steadiness is the whole reason these businesses are so attractive, and once you understand it, a lot of investing starts to make more sense.
The most important thing to look at is how long they manage to keep their customers, because that's where the real money is. If Netflix can hold onto you for five years instead of one, that's five times as much money from the exact same person, without spending anything extra to get you. So when a company gets even slightly better at keeping people around, it makes a massive difference to how much they earn over the long run.
These companies also have room to raise their prices very gradually. You've probably watched your own monthly bill go up by a dollar or two over the years and barely thought twice about it, so you kept paying. Spread that small increase across millions of customers and it turns into a serious amount of money, and it works even better once the product has become something you use without thinking.
Another thing that makes them powerful is how much they can afford to spend to win you over in the first place. Since the company already expects you to stick around and pay for a long time, it makes sense for them to spend more upfront to get you signed up, knowing they'll earn it back over the months and years you stay. That gives the strongest companies a real edge, because they can keep pulling in new customers while still making money on each one.
There's also the habit side of it, which is easy to overlook. When you watch Netflix every night or put Spotify on every time you get in the car, the product quietly becomes part of your daily routine. Once it's woven into your day like that, most people just keep paying, because canceling feels like more effort than it's worth.
On top of all that, these businesses give you a really clear read on how they're actually doing. Because the payments come in steadily every month, you can easily tell how many people are using the product and whether that number is growing or shrinking, which makes your job as an investor a whole lot easier.
And once one of these companies gets big enough, it can start adding even more ways to make money. With millions of people already paying every month, it can introduce things like ads, cheaper plans, premium plans, or bundles, and it doesn't have to go find a brand new audience to do it, because everyone's already there.
So if you're just getting started, this is a great place to start. Pick a subscription business you already use yourself, pay attention to how well it keeps its customers, and watch how it grows over time. Once this clicks for you, you'll start spotting it everywhere you look.
As part of my portfolio work this week, I fully revisited the $IREN thesis. @Agrippa_Inv latest long form report (link at bottom of this post) was incredibly helpful in that regard. The following three paragraphs stood out most to me as did the attached charts - the combination of which spells out (i) just how significant the $NVDA partnership is, (ii) the strength of the fundraising execution over the last year in particular, and (iii) potential timeboxing of upcoming catalysts. Extremely excited for H2'26 - H1'27. And @Agrippa_Inv I know you encourage sharing snapshots but if I shared too much, apologies - it was genuinely S-tier work and I not only want to highlight it, I want these quotes in my X feed so I can reference them later as needed with Grok. Thank you so much for the continued excellent long form coverage.
"NVIDIA signed a $3.4 billion cloud services contract using IREN as the operator for their own internal AI workloads. This is one of the only cloud deals NVIDIA has ever signed as a customer, and it’s by far the largest of them. Trusting IREN and Mirantis with NVIDIA’s own R&D and AI workloads is an extraordinarily sensitive decision, and it reflects a depth of confidence in IREN’s ability to execute that no passive equity stake could ever convey. NVIDIA publicly designated Sweetwater as a flagship DSX deployment, tying their data center product strategy directly to IREN’s ability to execute at gigawatt scale. NVIDIA likely orchestrated the Mirantis acquisition to ensure IREN had the managed services capability needed to deliver against the partnership’s broader ambitions. Each of these commitments individually represents a significant operational and reputational bet on IREN. Stacked together, they constitute one of the deepest strategic alignments NVIDIA has formed with any infrastructure partner."
"Issuing now, at terms that are great for IREN but still
leave buyers with real upside, keeps the door open for future raises and ensures continued access to what has become a deep and reliable funding channel. Putting all of this together, the “wait for re-rate” objection misunderstands what optimization actually looks like for a serial issuer in a capital-intensive business. The question is not what the single best moment to raise capital is, but rather how to lock in the best blended terms across cumulative raises over a multi-year funding curve. Waiting for any single re-rate event to maximize one deal almost always loses to executing systematically across favorable windows. IREN’s finance team is doing the latter, and the May 2026 offering is another data point in that ongoing pattern."
"On the contracting timeline, my base case is that the majority of the roughly 800 MW remaining across 2026 and 2027 gets inked over the coming months. The reasoning is that IREN has already started contracting portions of its 2027 pipeline through the NVIDIA agreement that landed on May 7, which signals that the broader commercial conversations are now actively converting into signed deals. Once an operator starts contracting future-year capacity, it usually means several other deals are in late-stage negotiation rather than just one. The pattern across the rest of the year should look like a steady cadence of contract announcements rather than a single dramatic catalyst, though I would not be surprised if one or more of those announcements ends up being a genuinely thesis-shifting hyperscaler or frontier-lab deal."
https://t.co/ncqRuQYXPi
TIN NÓNG: Liều lượng Ivermectin CHÍNH XÁC đã giúp bệnh nhân Ung thư chữa lành
12mg mỗi ngày trong 5 ngày, sau đó 12mg hai lần mỗi tuần để duy trì.
Big Pharma không muốn bạn biết điều này chỉ tốn 2 đô la mỗi viên thay vì 10.000 đô la các liệu pháp hóa trị.
Họ HOẢNG SỢ mất lợi nhuận trong khi bệnh nhân Ung thư cải thiện chỉ với vài đồng! 😃
Đây là điều họ tuyệt vọng muốn giữ kín.
Tôi đã thấy nó hiệu quả hết lần này đến lần khác.
Đừng để họ giữ bạn trong bóng tối.
New models are shipping every few weeks, each one needing more computing power than the last, and the models coming in 2, 5, and 10 years will need vastly more than anything running today.
Way to invest? Own the supply chain, layer by layer.
Layer 1 is the chips. These are the processors that actually run AI.
> $NVDA is the leader and sells the most AI chips in the world.
> $AMD is its biggest competitor and is selling more AI chips every quarter.
> $AVGO designs custom AI chips for companies like Google that want their own alternative to Nvidia.
> $TSM is the factory that physically manufactures nearly all of these chips.
> $MU makes the high speed memory that gets attached to every one of them.
Layer 2 is networking. Thousands of chips only become a supercomputer if they can talk to each other at extreme speed, and these companies make that possible.
> $MRVL makes the chips that connect everything together.
> $ANET sells the switches that direct traffic inside AI data centers.
> $ALAB connects the components inside each server rack.
> $CRDO makes the high speed cables and signal boosters between racks.
> $CSCO is an old networking giant that is now winning large AI orders.
Layer 3 is optics. This equipment moves huge amounts of data using light through fiber instead of electricity through copper, because light is faster over distance.
> $LITE and $COHR are the two biggest players in lasers and the transmitters that send data as light.
> $AAOI is a smaller company supplying these parts to the big cloud players.
> $FN manufactures the components inside many of these systems.
> $CIEN carries this traffic across long distance networks between cities.
> $SIVE is a speculative pick here, a small Swedish company working on light based chips for AI data centers with partners like GlobalFoundries. It is high risk.
Layer 4 is the data centers themselves, the actual buildings full of these chips.
> $NBIS, $CRWV and $IREN are building AI computing capacity at an incredible speed and rents out massive amounts of Nvidia chips to AI companies.
> $VRT supplies the power and cooling systems inside the buildings.
> $DELL and $SMCI assemble the server racks.
> $EQIX owns the real estate where much of this compute lives.
Layer 5 is power, which I believe becomes the biggest bottleneck of this decade. A large share of planned US data centers is being delayed because there are not enough transformers, electrical equipment, and grid connections to power them.
> $CEG and $VST own the nuclear and gas plants that the tech giants are signing decades long contracts with.
> $GEV builds the turbines and grid equipment. > $ETN supplies the electrical gear inside every facility.
> $PWR is the contractor physically building out the grid.
Then there is the layer almost nobody connects to AI, and this is where the most interesting opportunities hide.
$CAT is a perfect example. Most people see a construction equipment company, yet its generator business is booming because every data center needs backup power on site, and management now brings up data centers on every earnings call.
$FCX mines copper, and this entire buildout consumes enormous amounts of it. $MP mines rare earths, which go into the magnets inside motors, turbines, and cooling systems. $UAMY is a more speculative one in antimony, a critical mineral used in batteries and electrical equipment.
The common thread is that the AI buildout reaches much further into the economy than most investors realize.
This is a buildout that will run for years. Own the companies supplying every layer and give the thesis time to work.
NFA
If you’ve ever wondered how to support your body against lingering spike proteins - listen up 👇 Dr. Barbara O’Neil points to 3 natural protectors that may help block the spike from binding and replicating: 🌿 Zinc - Helps stop viral replication. 🌿 Dandelion - Research shows
🚨 OFTALMÓLOGO revela el ejercicio de 30 segundos que puede MEJORAR tu vista...
- Sin gafas
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Solo necesitas tu pulgar y 1 minuto al día.
El 90% de las personas descubren que un ojo es MÁS DÉBIL al hacer esto 👇
I have one simple goal by being here:
Become a multi MILLIONAIRE.
If that’s your goal too, keep reading.
Here's the honest version of "escaping the matrix."
You don't quit your job and suddenly become free. That's not how it works.
You build a portfolio that generates enough passive income that the job becomes optional, not mandatory.
That transition takes years, not months.
For most people that means:
Not touching the invested capital for 5-7 years minimum.
Adding consistently even in down markets, especially in down markets.
Learning to hold through volatility without selling at the bottom.
Having a day job that doesn't drain you so completely that you can't think clearly after hours.
The matrix is a system that requires your time in exchange for enough money to survive but not enough to get out.
The escape is building a parallel system that doesn't require your time.
I share every position publicly.
I share every move. No gate keeping.
I haven’t reached my goal yet.
But I will.
And when I do, you’ll have watched the whole thing. From the beginning.
Let’s build this together.
—BP.
$IREN $NBIS $RKLB $ASTS $AAOI $CIFR $ONDS $PNG.V $OUST $NOK $PL
Not financial advice.
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$TEM v $HIMS
Just wanted to share this nugget from interview w/ CEO of $TEM
it explains one of the potential problems / differences between the two businesses.
btw - i havent made a position in $TEM, it certainly is a great biz tho.
Anyway - here is my understanding as I see it + one of the problems $TEM (may) have & how $HIMS, existing outside of the healthcare paradigm, may be long term advantaged.
👇
The more I think about the Tempus versus HIMS comparison, the more I think the key issue is incentives.
This is directly what Eric Lefkofsky, the CEO of Tempus, is describing.
Tempus clearly has an extraordinary data asset. They have deep clinical data, oncology data, molecular data, imaging data, pathology data, and relationships with hospitals, physicians, and pharma companies. In complex medicine, especially oncology, that is incredibly valuable.
But the problem is that Tempus still operates largely inside the existing healthcare system.
That matters because the existing healthcare system only generates diagnostic data at scale when there is a clear economic reason to do so.
Oncology is the perfect example.
Lefkofsky says that in oncology, precision medicine is already well advanced. His words were:
“In oncology or in cancer, I think we're a six or seven heading to a 9 or 10. It's a function of time and money. It'll happen. There's nothing structural that needs to happen.”
That is a hugely important quote.
He is saying that in oncology, the system already works. It is not perfect, but the flywheel exists. The research exists. The drugs exist. The biomarkers exist. The testing exists. The reimbursement exists. The data is being generated.
That is why Tempus is so strong in oncology.
The reason oncology is ahead is that the industry has already built the full chain.
1. First, lots of cancer research happened.
2. Second, that research created targeted cancer drugs.
3. Third, many of those drugs only work if the patient has a specific mutation or biomarker.
4. Fourth, because the drug requires the biomarker, doctors need to run the diagnostic test.
5. Fifth, because the diagnostic test clearly affects treatment, insurers are more willing to pay for it.
6. Sixth, because insurers pay for it, the test gets used at scale.
7. Seventh, because the test gets used at scale, companies collect more data.
= And because more data gets collected, precision medicine improves.
So in oncology, the flywheel works:
1. Research creates targeted drugs.
2. Targeted drugs require biomarkers.
3. Biomarkers require diagnostic tests.
4. Diagnostic tests get reimbursed.
5. Testing creates data.
6. Data improves precision medicine.
That is why oncology is ahead.
But outside oncology, Lefkofsky says the situation is completely different.
His exact words were:
“Outside of oncology, we're a zero to one everywhere. Cardiology, zero to one. Neurology zero to one.”
That is the key point.
In cardiology, neurology, Alzheimer’s, depression, inflammatory disease, and other non-cancer categories, the issue is not that diagnostic tests are technically impossible.
The issue is that there are often not enough approved treatments that require a specific biomarker test before prescribing.
That is where the incentive problem appears.
In oncology, a doctor can say:
“Before I give this patient this cancer drug, I need to know whether their tumor has this mutation.”
That is a very clear reason to test.
But outside oncology, there are fewer situations where a doctor can say:
“Before I give this patient this heart drug, neurology drug, depression drug, or inflammatory disease drug, I absolutely must run this molecular diagnostic test.”
So the insurer asks:
“Why should we pay for this test?”
And if the insurer does not pay for the test, the test does not get ordered at scale.
If the test does not get ordered at scale, the data does not get generated.
And if the data does not get generated, precision medicine does not improve quickly.
That is the chicken and egg problem.
Lefkofsky says this directly:
“The challenge outside of oncology is that when Nixon declared a war on cancer and when we set up the NCI as a branch of NIH, we began funding a bunch of cancer research. And so when we began sequencing patients, one of the first outlets was in cancer.”
Then he explains why that matters:
“You just have a couple of decades now of all these drugs that have shown up that treat eGFR or ALK or Entra or whatever. You don't have that in other disease areas.”
That is the incentive problem.
Oncology had decades of research that created drugs that needed biomarkers.
Other disease areas often do not have that yet.
Then Lefkofsky says:
“So we're in this weird kind of chicken and an egg. We didn't fund those disease areas with lots of research that turned into lots of drugs that needed a biioarker that mandated the need for sequencing which someone would pay for to usher in precision medicine. We just were stuck.”
That quote is extremely important.
He is basically saying that oncology had the right sequence of events:
Research.
Drugs.
Biomarkers.
Testing.
Reimbursement.
Data.
Precision medicine.
Most other disease areas do not yet have that sequence.
And that creates a structural issue for Tempus.
Tempus is incredibly powerful where the clinical system already supports diagnostic testing. In oncology, the physician needs the test, the insurer often pays for the test, the test generates data, and Tempus gets stronger.
But outside oncology, Tempus is more constrained by the existing system.
If insurers do not believe a diagnostic test is necessary, they may not pay for it.
If insurers do not pay for it, doctors are less likely to order it.
If doctors do not order it, Tempus does not get the same volume of diagnostic data.
If Tempus does not get the data, it is harder to build precision medicine in that category.
So Tempus has a data advantage, but it also has an incentive problem.
It is trying to build precision medicine through the existing healthcare system, and that system often only moves when reimbursement, clinical guidelines, drug labels, physicians, hospitals, and insurers all line up.
That is where HIMS becomes interesting.
HIMS attacks the problem from the opposite direction.
HIMS does not begin with hospitals, insurers, oncology centres, pharma research, or reimbursement codes.
HIMS begins with the consumer.
The consumer wants care.
The consumer pays cash.
HIMS provides access.
HIMS collects data.
HIMS adjusts treatment.
HIMS learns over time.
That means HIMS can bypass part of the traditional healthcare incentive problem.
Instead of waiting for an insurer to decide whether a test or treatment pathway is worth paying for, HIMS can go directly to the patient.
That gives HIMS a major advantage in consumer healthcare.
And this also fits with Lefkofsky’s broader point about where healthcare is going.
He says the old model was patient to physician, but the future will be different:
“Historically was patient direct to physician. It's 100% going to be like literally 100% of the time patient to technology to physician or it's going to be a triad now.”
That is exactly why HIMS matters.
HIMS already owns part of that “patient to technology” relationship.
It owns the consumer interface. It owns the onboarding flow. It owns the subscription. It owns the direct relationship. It owns (some of) the longitudinal behaviour.
Lefkofsky even acknowledges that healthcare has historically been terrible at consumer, but that HIMS is one of the few companies that has broken through:
“Historically healthcare has been horrible at consumer. There's a few companies that have broken through HIMS to their credit.”
That quote is important because it shows that even the CEO of Tempus recognises HIMS has done something unusual.
HIMS has made healthcare consumer-native.
That means HIMS can collect data from patient intake forms, symptoms, labs, medication history, side effects, adherence, refill behaviour, weight loss progress, dosage changes, treatment response, and long-term outcomes.
That data may not be as deep as Tempus’s oncology data (yet), but it is still extremely valuable.
And more importantly, HIMS can generate it directly through the consumer relationship (by-passing the incentive problem outlined above).
Tempus has to work within the existing paradigm: hospitals, physicians, insurance, reimbursement, FDA pathways, and clinical adoption.
HIMS can subvert part of that paradigm by going direct to consumer, using cash pay, and building its own longitudinal data flywheel.
David Sinclair says he’s been reversing plaque in his arteries with nattokinase.
On Peter Diamandis’ podcast, Sinclair shared that he’s been taking it for years and mentioned a Chinese study with 1,086 people that showed up to 95% plaque reduction in one year at sufficient doses (at least 12 fibrinolytic units daily). He also checks his own carotid arteries with ultrasound and says there’s no buildup.
Nattokinase is an enzyme from fermented soybeans that breaks down fibrin. Some human studies show it can help reduce arterial plaque and improve blood flow, but results vary. Larger, high-quality trials are still limited, so it’s considered promising but not definitive.
Cardiovascular disease is still the #1 killer. If there are accessible tools that support artery health beyond statins and lifestyle, it’s worth paying attention.
Have you heard about nattokinase or tried anything similar for heart health?
NEW ARTICLE: IVERMECTIN and FENBENDAZOLE Testimonial - 53 year old man from Connecticut with Stage 4 Prostate Cancer to bones reports after 6 months: PSA drops 99.9%!
Ivermectin revolutionizing Prostate Cancer 😃
STORY:
53 year old man from Connecticut with Stage 4 Prostate Cancer to bone
In August 2025 he started:
Ivermectin 48mg (increased it to 96mg)
Fenbendazole 444mg (increased it to 1500mg)
Results after 6 months:
PSA 948 to 1.13 = 99.9% drop (!!)
PSMA scan (Oct.24, after 3 months) showed 50% less disease!
"Oncologist says he's "responding well" which we think is a massive understatement! Oncologist does not know he's on the Ivermectin or Fenbendazole"
"PSA 99.9% drop in six months!"
How does Ivermectin and Fenbendazole fit into the treatment picture here?
Aside from the dozen mechanisms of action, each contributes to treatment synergy.
Treatment synergy means you get more cancer cell killing in combination than with any of the components by themselves.
This is the cutting edge of Cancer Care.
Competent Oncologists should be taking advantage of treatment synergy to give the patient the best treatment option.
They're not doing it. But we are going to change that! 😉
I have helped over 9000 Cancer patients with Ivermectin, Mebendazole, Fenbendazole in the largest Ivermectin Cancer Project in the world!
This project is moving to Florida, but please be patient while the move is being finalized.
Repurposed drugs are the future of Cancer Care and Florida is going to be the global hub of repurposed drug research and innovation! 🔬
We are working on:
Ivermectin and Mebendazole Clinical Trials
Cancer Clinics ("Right to Try")
Patents (will shake up the world)
Publications (over 600 cases being prepared) Repurposed Drug Access (lower cost)
and so much more!
Article link is located in first photo at the top to avoid shadowbanning on X, just retype the URL into your browser to access