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Selling a bit more $nvda and added some $tsla in last few weeks (@ $380 range before the dip). Still holding $avgo and haven't sold any $aapl RSU vesting since last 1 year as I have started to feel better about it
Selling $NVDA and building cash for attacking the AI application companies. Still like both $TSLA and $AVGO. Tesla is definitely going to rule the AI application layer (if Elon stays sane) while Broadcom will take over the crown for AI datacenter from Nvidia. However, finally inference will move to edge, i.e., AVs, humanoid robots.
$AVGO now becomes my 2nd largest holding overtaking $NVDA !
Sam 2.0: The dem version 🤣
People should always be in control of the future.
OpenAI is against the notion that it would be acceptable for people to be relegated to a role of doing things that “AI systems think makes sense to reward in humans”.
People should not cede control of the future to superintelligence, and that requirement should ultimately constrain AI progress.
Stock price is lagging earnings?
Best advice I ever received from someone who currently manages $280 billion?
Stocks follow earnings.
Occam’s razor mf 🔥
$TSLA earnings are about to explode.
Really?
Yup, watch revenue multiply while gross margins simultaneously track higher.
Osman Sarood retweeted
Never getting in a Lear 60 again
And with commercial being 10x cheaper and 10x safer, I’m only flying the big iron from the majors
What’s the point of saving two hours on average when you have starlink on 50% of @united flight already
See you in the lounge besties
Long post worth the read. I have a close friend who flies private jets. He flew Lear 60 for over 15 years and now flies a Gulfstream. This is a copy and paste of his response to me asking him if I thought Ice was the issue.
“We always fly in ridiculous cold temperatures.”
“Usually you get the bad ice when the temperatures are like 0 to negative 20. Believe it or not, there's a point where it gets too cold for ice. At negative 40, you pretty much can't get ice. Besides that, the airplane is equipped with hot wings and hot tail.”
“I flew the Lear 60 for like 15 years. It's a no joke airplane and probably the most dangerous airplane I've ever flown. It has a super critical wing. The airflow has to be perfect. When it gets into rough air and turbulence, it will easily stall. It has stalled on me at 41,000 feet just because we got into some turbulence. (On the way to Palm Beach as a matter of fact. ) we recovered and got her flying again around 30,000 ft. Scary
But here's the problem. This airplane has a terrible coffin corner. (At high altitudes) what that means is, you fly in a really narrow window where if you lose 20 knots, it stalls. And if you gain 20 knots, it goes into overspeed. The air goes supersonic over the wing and it goes into a high speed stall, or worse, a Mach tuck.
So if you stall, the normal recovery is to push the yoke forward to lower the nose and gain air speed again. At low altitude, you can push really hard and recover quickly. But in the 60... if you push hard, it will gain air speed and go into a high speed stall, it doesn't take much. It's very sensitive. The 60 has super short wings that don't make much lift. So then you high speed stall, and the computer is yelling at you... OVERSPEED! So then you pull back and enter a low speed stall. And you go back and forth trying to keep it in the air speed window.
This whole thing is pretty scary. And you should recover basically by using your finger tips using super small corrections. You can't over do it. If you try to muscle the recovery, she gets mad and will become unrecoverable. If she enters a mach tuck. You're done.”
“I taught the Lear 60 to other pilots and mentored them. I told them... this airplane has a soul and it's trying to kill you. Do not ever try to top the weather. Don't go over a thunderstorm. Go around it. If it means a half hour longer, then do it. Going over the thunderstorm will go into turbulence that you might not recover from.
These pilots went right over a thunderstorm. I think it stalled which caused them to drop down into the thunderstorm and ended up in mach tuck. They picked up so much speed that it ripped off the horizontal stabilizer. At that point... chuck Yeager can't fix it.
These same pilots did something similar a couple months ago. ATC got mad at them. They poked the bear one too many times.
This is not a beginner airplane. The Gulfstream would never do this. It has HUGE margins of error and won't stall like that. But then again... it's got HUGE wings. It's a pussy cat.
The Gulfstream is like driving a 4 wheeler. The Lear 60 is like riding a uni cycle.”
Thrilled to see another of my startups Fiddler AI getting acquired for $400M. Still remember the days where half dozen of us worked together to lay down the foundations of AI monitoring/observability .. we've come a LONG way .. Hoping Tesla to pay big soon 😅 $tsla
CROWDSTRIKE TO ACQUIRE TWO AI SECURITY STARTUPS FOR $495M
$CRWD has agreed to acquire Fiddler AI and Dreadnode as it expands its Falcon platform to secure AI agents throughout their lifecycle.
The acquisitions, include:
1) Fiddler AI (~$400M) | Agent Observability: Monitors AI agents, tracks their decisions and tool usage, and explains why they took certain actions. It can also identify hallucinations, behavioral drift and unintended actions.
2) Dreadnode (~$95M) | AI Security Testing: Tests AI models, applications and agents for vulnerabilities before deployment, using more than 100 attack strategies, including jailbreaks, prompt injection and agent-specific attacks.
The deals come as companies increasingly deploy autonomous AI agents with access to corporate systems, often faster than security teams can establish proper controls.
One major challenge is that an AI agent can have valid credentials and authorized access but still make incorrect decisions, ignore instructions or take unintended actions without being hacked.
Separately, CrowdStrike also introduced an AI Kill Switch within Falcon Guardian, allowing security teams to terminate misbehaving agents, prevent them from restarting and revoke their network access.
The feature is available through the AI Gateway today, with endpoint-level termination planned.
CrowdStrike plans to integrate Fiddler as Falcon Observe, while Dreadnode will add automated AI security testing to Falcon. Both capabilities are expected to become generally available in Q4 FY27.
The broader strategy is to bring AI security testing, agent monitoring and real-time intervention into a single platform, covering what agents are allowed to do, what they actually do and how to stop them when something goes wrong.
Both acquisitions are expected to close in Q4 FY27, with payments primarily in cash and some stock.
That looks exponantial to me $tsla
Will the rockets become the Roadster of SpaceX? $spcx
A Sequoia partner says SpaceX will bring in $731 billion in 2028. That's more than Walmart or Amazon sold last year, from a company that made $18.7 billion in 2025.
It sounds made up until you check where his numbers came from. Almost every big one is straight off SpaceX's own earnings call, and a few are actually lower than what the company told investors.
Shaun Maguire's model has SpaceX doing $36.3 billion in the first quarter of 2027. On the October call, SpaceX's CFO guided to somewhere between $33 and $37 billion.
On computing power, SpaceX says it's aiming for about 13 gigawatts by the end of 2027, with a stretch plan above 20. Shaun only gave them 10.2, so he's assuming they build about 3 fewer gigawatts than they say they will.
Pricing works the same way. Back in August, Elon said a watt of AI compute is worth $30 to $50 a year in revenue, and Shaun picked $40, right down the middle.
Multiply those two together and you've got most of the model. Get to 21 gigawatts through 2028, charge $40 a watt, and that's $569 billion in compute revenue in one year. Starlink and everything else fill in the rest.
Wall Street is nowhere close. When SpaceX went public in June, Goldman and Morgan Stanley both had 2028 at roughly $160 billion. Morgan Stanley's September model assumed 4.9 gigawatts by the end of 2027, then knocked 50% off the AI business for execution risk.
So a $571 billion disagreement between a Sequoia partner and the banks that took SpaceX public comes down to one question, whether you believe SpaceX can build what it says it's building.
If I were going to poke at one number, it'd be price per watt. SpaceX did $7.56 billion of AI revenue last quarter on 1.7 gigawatts, which works out to about $18 a watt over a year. Shaun's model needs that to more than double while capacity grows twelvefold, and that's the line I'd watch every quarter.
What gets me is how small the rockets end up in this picture. In the model, the space business is 2.4% of 2028 revenue, Starlink is about 12%, and AI compute is around 85%. And the plan still has Starship flying 250 times that year, from a rocket that's flown fewer than 15 times so far.
If Shaun's model is wrong, SpaceX's own guidance is wrong first.
True, use stuff and do more
THIS. IS. NOT. A. DRILL. 🚨
I’m spending < $40k a year on tokens/subscriptions from Anthropic, Loveable, Grok Bot, 11labs and a long tail of other products—and getting $2m+ in value @launch and @twistartups
We’ve automated at least seven full-time jobs at this point while becoming 100% faster at the average task we do
If you haven’t used the last 90 days' worth of products for at least 30 hours a week you have no idea how profound this software is
The last 90 days, things have changed more than in the last two years
Many of the things i spent hours on last year now take minutes… and the results are mind blowing
Not sure what’s stopping SpaceX and Elon to just do this? Win for SpaceX on both Gork bot and SpaceX SI front $spcx
Elon is testing the waters to see the true value of AI to end users. He’s going to bump up the prices to see if people still subscribe.
Makes sense to do the due diligence before spending $400B to build the 10GW next year. Problem is, if these users end up going to others. Maybe we’ll see similar price increases by others $spcx
I care about the future but I care more about both companies shareholders getting their due share. Do it or leave it but no compromises
SpaceX Special Committee, are you listening?
Here we go:
1. Custom AI chips and the real-world data loop are the core. We designed the silicon, we own the fleet data, and no one else has that closed system.
2. Dojo is our own training stack. It lets us iterate on our data without waiting in line for someone else’s GPUs.
3. Optimus uses the same models. If it works on Earth it generates cash and tech we can use elsewhere.
4. Energy storage is already real infrastructure. Megapacks power grids today; the same systems matter for launch sites and Starlink.
5. We know how to manufacture at volume and drive costs down. That learning curve is hard to buy.
6. Robotaxi turns the existing cars into a software business with almost no extra capital once autonomy is unsupervised.
7. The car and energy businesses throw off cash now. That cash de-risks the longer bets.
8. Shared AI talent and compute across the companies avoids doing the same work twice.
9. Our shareholder mix gives liquidity and a retail base SpaceX does not yet have. Useful when you need to raise or when you want multiples.
10. Elon's voting rights. Do I need to say more? He deserves the key to the empire, which comes at a price.
Bottom line: Tesla is an AI, energy, and robotics platform with its own silicon and data. Combined with you, it is a more complete company than either one alone.
Let's do it, don't look at the pennies. Look at the future.
Good one. Strongly resonate with the risk part. True for investing in general and not just options.
Here’s the catch though. Risk has VERY different meaning. Something that looks insanely risky to the outside world might seem fairly low risk to the one taking it. Checkout @AlexHonnold ‘d Taipei 101 interview and you’ll know what I mean 🙂
6 years of options trading taught me this…
•the hole in the hull: why my best year was the one i spent looking for my flaw
last year i made ridiculous life changing money. the kind of year that makes you feel bulletproof
and that's exactly the problem!
this year i didn't try to top it. i spent it hunting for the one flaw that could sink the whole ship
•the number that lied to me
3,151 trades this year. 2,818 winners. that's an 89% win rate
on paper that's an A student. size your bets evenly, win 9 out of 10 and it looks like a recipe for success
but a win rate isn't a p&l. the ratio means nothing if a black swan shows up on the one day i'm carrying too much risk. one bad trade sized wrong can erase hundreds of good ones
•the flaw wasn't emotional, it was systemic
a friend who builds algo trading bots told me to put my strategy into code because code has no emotions. he's right about code. but my problem wasn't emotion
i shared my trades with my wife and parents in real time. the wins got the spotlight. the losers showed up on the statement a week later, quietly, buried in a good month
without realizing it i built a system that rewarded not losing instead of managing risk. i wanted to stay a 90% student so badly that i wouldn't close a trade while it was red
the frustrating part is that it usually worked. a lot of red trades came back because my direction was right. but the vast majority of my real losses weren't small cuts. they were positions i let ride all the way to zero
•learning to sit on my hands
when tsla fell to 300 after q2 earnings, i stepped away for 2 months. no forcing trades, no revenge. i waited for it to recover and then went back to selling covered calls
that break showed me something important. i still had the patience to sit on my hands and pick my spots. discipline isn't only about what you do, it's about what you're willing not to do
•becoming a better loser
this week a tsla put went bad. the old me lets it expire worthless and tells himself it might come back
the new me sold it for 3 cents
3 cents sounds like nothing. it isn't about the money. it's about breaking the habit of waiting for zero. it's the first rep of learning to take the L early once it's clear i'm wrong
i still closed that day up about huge. one bad trade, managed instead of ignored, and the day was still green
•why i'm not coding it yet
i could build an algo or teach an ai how i trade. but if i automate my strategy before i fix this flaw, i'm just automating the flaw
this lesson has to be learned in my own process first. then the code can carry it
•stay the student
success is the most dangerous teacher because it hides the cracks. the better your results, the easier it is to get cocky and stop looking
so here's my takeaway
- your win rate is not your scoreboard, your risk is
- study your losses harder than your wins
- sitting out is a position
- cut the trade when you know you're wrong, not when it hits zero
- be a student more than a teacher, especially after a great year
i'm still learning. always will be 🫶🏻 and thanks grok @bot for helping share my learnings in an efficient manner