$MSTR @phongle & other director selling $15m worth of shares yesterday
This is who you are paying insane salaries to literally go blow your money up
You can buy bitcoin with $0 salary exposure, at better prices than the $MSTR retards and own your BTC
Or you can finance $100m+ in exec compensation for them to spend 11.5% to borrow more money and lose yours
With this $15m sale alone you could hire a small trading shop and run your own treasury company lmao
Wake
The
Fuck
Up
❄️ $WNTR Pays You Weekly To Bet Against $MSTR
Today's Price Action:
📉 $MSTR: -6.80%
📈 $WNTR: +4.15%
💰 $WNTR Latest Yield: 67.59%
With $MSTR selling Bitcoin for the first time since 2022, could $WNTR be just getting started?
When markets pull back, strategies can adapt. $WNTR, the YieldMax® MSTR Short Option Income Strategy ETF reflects an income approach built for downside moves.
Prospectus: https://t.co/Kd8JRI3wmx
View standardized performance at https://t.co/euZisVNUdt
Henry Nowak died the same way a civilization dies: abandoned, handcuffed by authorities who neither trusted nor cared for him, and accused of hate crimes he did not commit. His murder is as tragic as it is enraging. He should still be alive today, and he would be if the last few generations of European elites had stood their ground against the politics of self-hatred and the mass invasion of migrants, many of whom despise the West and the people who love it.
Henry was far from the first to so needlessly lose his life, and I fear he won’t be the last. Each time a life like his is lost, the proper response—the only response—is righteous anger. One of the most important things the Trump administration has proven to the world is that stopping the flow of mass migration and defending national sovereignty is a matter of political will and leadership. Anything else is an excuse.
It is because we love the West that we want to preserve it. We love our civilization. We love our country. We love our children. And nobody—nobody—should ever die the way that Henry Nowak died. May God comfort those who loved him, and may God rest his soul.
$MU just crossed $1 trillion, and $2 trillion could be next…
That sounds crazy, until you look at the numbers:
Revenue:
2023 → $15.5B
2024 → $25.1B
2025 → $37.4B
2026 estimate → $110B+
2027 estimate → $170B+
Micron's entire HBM memory supply is basically sold out through 2026.
That's why revenue and margins are exploding.
And that's why the stock has gone from under $100B to over $1T.
But… the CEO just sold $60M of stock.
And Micron plans to spend $20-25B building new factories that could eventually create oversupply.
I don't recommend buying companies at any price.
Valuation matters.
But if someone held a gun to my head and forced me to buy today’s prices and not touch the portfolio for the next 5 years, these would probably be my picks:
• $NBIS - AI Cloud
• $CRDO - AI Networking / Connectivity
• $OUST - Physical AI
• $LITE / $AAOI - Optical Infrastructure
• $DRAM - Memory growth exposure
The common theme is simple:
I'm trying to position around the areas I believe will benefit the most from the continued buildout of AI infrastructure and deployment over the coming years.
Will they be the best performers? No idea.
Will there be volatility? Absolutely.
But if my only option was to buy today and disappear for 5 years, these are the names I'd be most comfortable owning.
The Roundhill Memory ETF $DRAM is now approved for purchase in Japan by the FSA; Japan’s Financial Services Agency. The memory trade continues to be a global investing theme. Consider investing: https://t.co/lrirBeukdk
This is actually so bullish
Memory demand will 10x to 20x by 2030
$MU, SK Hynix, and Samsung will only 2x or 3x capacity
With the inputs we have, there’s no realistic scenario, at the moment, where memory prices decrease
Agentic AI is the most important investment theme of the next decade. So what does it actually take to win?
You cannot drop an AI agent into an organization and expect it to perform. It needs a stable platform underneath it. Clean data. Full context. Day one access to everything it needs to make decisions.
Think of it this way. You would not drop your five year old into the deep end and expect them to swim. You need a platform to stand on and someone to teach them how.
The bottleneck is not the LLM. Every company has access to a capable model. The bottleneck is context. What does the agent actually know about your business, your workflows, your data, your decision history?
$PLTR solved this with the Ontology. A living, structured representation of an entire organization's data, relationships, and operations. When you deploy an agent on top of Palantir, it does not start from zero. It starts with everything.
$MSFT has unmatched distribution but the context is largely confined to the Microsoft ecosystem. Excel, Teams, SharePoint. Powerful within those walls. Limited outside them. It will likely automate all mundane tasks within the ecosystem with its unmatched distribution power.
$NOW sits in a powerful position. ServiceNow already owns the workflow layer for 85% of the Fortune 500. Every approval process, every IT ticket, every employee onboarding flow runs through their platform. When you deploy an Agentic AI on top of that existing workflow infrastructure, the context problem is already partially solved. The agent knows the process because ServiceNow has been mapping it for years. The limitation is that ServiceNow's context is process driven, not intelligence driven. It knows what happens. It does not always know why.
$CRWD is a different angle entirely. CrowdStrike is the first place where Agentic AI is not just useful but genuinely necessary. Cybersecurity generates millions of signals per second. No human team can process that volume. An AI agent that can detect, assess, and respond to threats autonomously without waiting for human approval is not a nice to have. It is the only viable solution at scale. Charlotte AI, their Agentic security platform, is already operating in this space. The context here is threat intelligence built over years of endpoint data across millions of devices. That is a defensible and compounding data moat.
$RDDT is the most unconventional name on this list, a wild card. Reddit is not building agents. It is feeding them. Twenty years of unfiltered human conversation, debate, expertise, and opinion sitting in one database. Every major LLM trains on it. Every AI agent that needs to understand how humans actually think, speak, and decide benefits from Reddit's data. The moat is not the platform. It is the irreplaceable human context that no AI company can generate artificially. Reddit becomes the context layer the entire AI industry depends on without most people even realizing it.
The winner in Agentic AI is not the company with the best model. It is the company with the best platform for teaching agents what they need to know to operate autonomously, without a human in the loop, 24 hours a day.
I have positions in all of these names as I am watching the Agentic AI investment theme takes shape.
Research is ongoing. More names may emerge.
Also Context = Memory $MU $SNDK $DRAM
I've spoken.
We are short $SIVE.
A retail-driven pump built on speculative hyperscaler links, a fabricated bottleneck narrative, and a rumored volume ramp-up has driven a 1,800%+ rally in $SIVE.ST.
Insiders sold ~29M shares into it. Here's what they're not telling you.👇 Full report: https://t.co/4QEyuXQIQb
$MU $SNDK $DRAM
If one local AI Agent occupies 32GB of DRAM or HBM, then when one million agents deployed is 32GB Petabytes.
Now we have 8 billion people on earth and millions of companies that will deploy thousands of agents.
Cloud based advanced agents will use 64GB to 128GB VRAM.
Enterprise agents will use hundreds of GBs of HBM.
Unlike humans, AI agents run 24/7 on high stake tasks, putting much higher pressure on memory and higher context requirements to achieve higher accuracy and quality.
Imagine all the memory demand required to satisfy all this over the next 10 years.