Plutus Strategy

🧵 The Only Macro Event That Matters: AI Everyone is debating the next 18 months: Will the Fed cut rates? Will we get a recession? That short-term noise is irrelevant to the next decade of wealth creation. The only macro event that truly matters is AI & Automation. It's a structural reset of global corporate efficiency. 👇

The AI boom is not over. It has barely started. What happened in 2023 to now was infrastructure seeding. What is coming next is full-scale deployment across every industry on the planet. The companies that own the compute, the networking, the power, the software, and the data centers are going to compound for years. I want quality med-to-mega cap companies with real demand, and clear bottlenecks. AI compute NVDA: The leader in AI compute. AMD: Earlier in the cycle, with room to gain share. AVGO: Custom AI chips, networking, and infrastructure. ARM: Benefits across mobile, edge, and AI architecture. QCOM: Edge AI exposure in mobile and auto. INTC: Turnaround and foundry optionality. Semiconductor manufacturing ASML: The lithography bottleneck. TSM: The foundry backbone of AI hardware. AMAT: Essential wafer-fab equipment. LRCX: Etch and deposition. KLAC: Process control and inspection. TER: Chip testing. AI networking ANET: One of the most important AI networking names. MRVL: Data-center connectivity and custom silicon. CRDO: AI interconnect and serdes exposure. CIEN: Optical networking demand. CSCO: Slower growth, but still relevant. GLW: Fiber and materials demand. LITE: Optical components exposure. COHR: Optical components exposure. Servers and storage DELL: AI servers and enterprise systems. HPE: Enterprise infrastructure and supercomputing. MU: Memory bottleneck exposure. PSTG: High-performance storage. NTAP: Hybrid cloud storage. WDC: Cold storage at scale. STX: Cold storage at scale. Power and cooling VRT: Clean AI cooling and power exposure. ETN: Power management and electrical infrastructure. GEV: Grid and power equipment. CEG: Nuclear baseload power. VST: Data-center power demand. NEE: Grid and generation exposure. DUK: Grid and generation exposure. Enterprise AI MSFT: Core AI platform and enterprise distribution. GOOGL: Undervalued AI platform with search, cloud, and models. ORCL: Cloud infrastructure and database leverage. META: AI-enabled ad platform. SNOW: Data layer for AI. PLTR: Enterprise AI and government. NET: Edge infrastructure and inference. DDOG: Observability for AI-heavy systems. MDB: Application data infrastructure. NBIS: Higher-beta AI cloud name. Data centers EQIX: Premium interconnection and colocation. DLR: Hyperscale data-center infrastructure. AMT: Tower and data infrastructure. IRM: Data center and records management. APLD: AI-focused data center operator.. Defense and Space LMT: Defense prime with AI integration. RTX: Aerospace, defense, and autonomous systems. NOC: Defense tech, space, and cyber. GD: Defense platforms and systems. AVAV: Drones and autonomous systems. RKLB: Defense and launch systems. RKLB: Cleanest space name with revenue and launch activity. ASTS: High-upside, but execution-heavy. LUNR: More speculative, but interesting. Optics and fiber GLW: Fiber and materials leader. CIEN: Optical networking for AI clusters. LITE: Optical components. COHR: Optical components. Solar and clean energy FSLR: Cleanest solar name with utility-scale exposure. ENPH: Residential solar and more cyclical. RUN: Higher risk and financing-sensitive. SEDG: Turnaround name. NEE: Clean power and grid exposure. Nuclear and uranium CEG: Best nuclear utility-style name. VST: Generation exposure. NEE: Grid and baseload exposure. DUK: Grid and baseload exposure. CCJ: Uranium supplier exposure. OKLO: More speculative SMR name. Quantum IONQ: Optionality name. RGTI: Optionality name. QBTS: Optionality name. INFQ: NVIDIA-tied quantum name. QTUM: Cleaner ETF route Strategic materials MP: Rare earths and strategic materials. UUUU: Strategic materials and uranium. USAR: Rare earth exposure. CRML: Rare earth exposure. What this captures is simple: the AI trade is bigger than chips. It runs through compute, networking, power, storage, data centers, software, and the adjacent sectors that support the buildout. This is not a trading list. This is a positioning list. You do not need to own all of these. You need to understand all of these. Pick your conviction plays, size them correctly, and hold through the volatility. Take the long weekend to study them.

@aleabitoreddit @TheLongInvest

I don't post dollar amounts because they don't matter. What matters is return %. Speaking of that... YTD: 3840.39%. I'm probably the only one in the world. Who called out multiple names that 10x'd in a short timeframe. Do you remember these thesis anon? 1. $AXTI 2. $SIVE 3. $AAOI 4. $LITE 5. $IQE 6. $AEHR 7. $CRCL 8. $EWY 9. Unimicron 10. Nitto Boseki 11. $OSS 12. $GDRZF 13. $RPI 14. $SOI 15. $ALRIB 16. $SNDK 17. $SIMO 18. $VPG 19. $TSEM 20. $ARM 21. $MRVL 22. $INTC 23. $LPK 24. $NBIS 25. $MU They're all up 100-1000%+, because... 1. I post a thesis. 2. People can see how the stock performs months later. 3. They turn out right (thesis validation) because they're up hundreds of percent + hold their returns. I really dislike the traditional X influencer who shows large dollar amounts or fancy watches/cars/private jets. Then use that to get more by selling expensive subscriptions rather than through market returns. So trying to set a new trend off pure information discovery/synthesis from free thesis posts and the results that follow in terms of return percentages. TLDR: Market returns in terms of percentages matter the most to validate a thesis. Not the dollar amount made.

UPDATED FIB LEVELS FOR POPULAR STOCKS Space • $RKLB $96 • $ASTS $89 • $PL $30 • $BKSY $34 Quantum • $IONQ $48 • $RGTI $25 • $QBTS $26 • $INFQ $13 Drones • $ONDS $6 • $AVAV $170 • $KTOS $52 • $UMAC $15 Nuclear • $OKLO $59 • $UUUU $14 • $GEV $906 • $LEU $168 Photonics • $AAOI $150 • $LITE $698 • $COHR $283 • $AEHR $71 CPU Bottleneck • $AMD $339 • $INTC $89 • $ARM $233 • $AMKR $56 AI Utilities • $IREN $51 • $NBIS $158 • $CIFR $17 • $CRWV $103 AI Power • $EOSE $7 • $BE $206 • $NVTS $20 • $VRT $273 AI Hardware • $NVDA $196 • $TSM $333 • $ASML $1,283 • $MU $541 AI Applications • $PLTR $132 • $NOW $99 • $CRWD $548 • $ZETA $17 AI Connectivity • $AVGO $360 • $ALAB $228 • $CRDO $158 • $MRVL $145 Physical AI • $TSLA $413 • $AMZN $247 • $GOOGL $314 • $ISRG $435

One AI Supercycle - 10 Layers. 10 Tickers. Layer 1 — Power | $BE A single AI data center can consume 100–500MW. The US grid wasn’t built for this. Bloom Energy sits at the intersection of distributed power generation and the insatiable energy appetite of hyperscalers. Power is the foundational constraint — before chips, before cooling, before anything else. Layer 2 — Substrates | $AXTI InP (Indium Phosphide) and GaAs (Gallium Arsenide) wafers are the raw material for photonic components — lasers, modulators, detectors. AXT Inc supplies these specialty substrates to the photonics supply chain. Demand is structurally rising as Co-Packaged Optics (CPO) and 1.6T transceivers scale. Tight supply, long qualification cycles, few alternatives. Layer 3 — Chips | $NVDA H100. H200. Blackwell. Each generation widens the moat rather than narrowing it. CUDA lock-in is one of the deepest competitive advantages in tech history. $NVDA isn’t just a chipmaker — it’s the operating system of the AI era. Layer 4 — Memory | $MU HBM3E (High Bandwidth Memory) is the bandwidth interface between the GPU and data. Without it, the most powerful chips in the world are throttled. Micron is one of only three companies globally that can produce HBM at scale — alongside SK Hynix and Samsung. Supply is tight. ASPs are rising. The AI upgrade cycle is a multi-year HBM demand wave. Layer 5 — Photonics | $AAOI As data centers scale from 400G to 800G to 1.6T optical speeds, the components inside transceivers — lasers, modulators, detectors — face an exponential demand surge. Applied Optoelectronics is a pure-play photonics manufacturer benefiting directly from this cycle. Margin expansion + volume ramp = a powerful setup. Layer 6 — Optics | $LITE If photonics makes the components, optics assembles them into the interconnect. Lumentum is a leader in optical networking — coherent transceivers, 3D sensing, EML lasers. The 800G → 1.6T transition is a hardware replacement cycle that touches every hyperscaler and co-lo data center globally. This isn’t incremental demand. It’s a full network overhaul. Layer 7 — Cooling | $VRT Vertiv designs and manufactures liquid cooling, immersion systems, and thermal management infrastructure for high-density AI racks. As GPU power density climbs past 1kW per chip, traditional air cooling fails. Vertiv is already embedded with the largest hyperscalers. Backlog is growing. Lead times are extending. Layer 8 — Networking | $ANET Arista Networks builds the high-speed Ethernet switching fabric that connects thousands of GPUs inside AI training clusters. Their software-defined architecture and 400G/800G switching platforms are designed for exactly the traffic patterns AI workloads generate. AI networking is a separate, incremental growth vector on top of their already dominant enterprise business. Layer 9 — Data Centers | $NBIS Nebius Group is building AI-native data centers — purpose-built for GPU density, liquid cooling, and low-latency networking. Unlike legacy co-los retrofitting old facilities, Nebius is starting from scratch for the AI era. Backed by Yandex’s original infrastructure DNA, they’re scaling fast in a market where capacity is chronically constrained. Layer 10 — Hyperscalers | $GOOG Google has committed $75B in capex for 2025 alone. Their TPU buildout, data center expansion, and AI product integration (Gemini, Search, Cloud) make them both a consumer and a builder across the stack. Every dollar they spend flows down through layers 1–9. The AI supercycle isn’t a software story — it’s a physical infrastructure buildout that rivals the railroad era. Every layer of this stack is capacity-constrained, capital-intensive, and structurally undersupplied relative to where demand is heading. Most investors own one or two names at the top of the stack. The opportunity is in understanding all 10 layers — and sizing accordingly. Not financial advice .

@aleabitoreddit oh

$IREN back down -34% from $70 to $46. I wonder if one of the dumbest communities on X finally learned to read? $NBIS is objectively the better Neocloud, with actual financing. -> Nvidia didn’t fund $IREN at all. They got a free purchase agreement to let IREN use their logos and dilute for GPUS. $NVDA actually gave $NBIS capital. -> $IREN is facing endless dilution like $BKKT, $ASST, $SLNH as retail wealth transfers capital over from $6,000,000,000 ATMs, on a dwindling “5 GW capacity” moat. $NBIS actually uses equity appreciating financing structures. And this is reflected in the YTD differences between them both. I’ve said the same thing last year too. One is up ~100%. The other is flat, and even negative depending on entry points. IREN is literally a marketing company at this point by how they manage to convince retail to wealth transfer over capital.

@StockSavvyShay @LeverageShares well it no longer Warren buffet making the moves.... so...

Still wild to me that Warren Buffett’s Berkshire Hathaway no longer owns $V or $MA. Top 5 positions: 1. $AAPL ~$58B (22% of portfolio) 2. $AXP ~$46B (17% of portfolio) 3. $KO ~$30B (12% of portfolio) 4. $BAC ~$25B (10% of portfolio) 5. $CVX ~$18B (9% of portfolio) $BRK.B kept the classic consumer, financial and energy compounders but exited two of the cleanest global payment toll roads in the market.

10 WAYS TO BUILD AN AI POWER PORTFOLIO 1. $OKLO effectively building the “local nuclear plant” the AI economy will require by placing reactors directly next to data center campuses for 24/7 onsite generation. 2. $BE fuel-cell onsite power play helping data centers bypass the grid with dedicated energy for AI clusters with product backlog up 250% YoY to $6B. 3. $CEG nuclear baseload backbone of the AI era with a 20-year $MSFT PPA tied to the Three Mile Island restart to supply the 24/7 carbon-free power. 4. $VST hybrid power engine of AI combining nuclear, gas & storage with a 20-year $META agreement covering 2,600+ MW across three nuclear plants. 5. $GEV industrial supplier rebuilding the U.S. grid providing the turbines, transformers & hardware every AI-driven upgrade cycle depends on with $163B in backlog. 6. $VRT infrastructure gatekeeper for AI compute controlling the cooling & power systems that $NVDA class clusters cannot run without with Q1 backlog up 80% YoY to ~$12.5B. 7. $EOSE long-duration storage solution for a grid under strain helping utilities smooth volatility as AI demand overtakes supply. 8. $NEE clean-energy arm of the AI buildout with largest renewable development pipeline in the country positioned directly into data center load growth. 9. $LEU only U.S. source of HALEU fuel making it essential for powering the modular reactors needed around future AI campuses backed by ~3B DOE contract. 10. $UUUU secures the domestic uranium supply chain by turning nuclear fuel into a national-security asset for the AI age.

@TheLongInvest looooool

Sell $UNH Buy $DAL Sell $MA Buy $M Sell $DPZ Buy $NYT BERKSHIRES Biggest moves this Q1 were a drastic shift from their legacy approach And to be honest Concerning

@MMatters22596 $SYM depending on Walmart is not a good thing

Our eyes are already focused on the FUTURE. Right now, we’re looking for the most promising ROBOTICS stocks to invest in — and two names stand out to us: $SYM & $OUST. 1. Symbotic ($SYM) An AI-powered warehouse automation giant with a record backlog of ~$22.7B and a transformative long-term partnership with Walmart as its anchor customer. 2. Ouster ($OUST) The “eyes factory” for robots and physical AI — producing digital LiDAR sensors that help autonomous machines navigate warehouses, factories, and the real world. Both offer tremendous asymmetric upside potential. Especially $SYM looks extremely promising to me. What’s your take on the robotics sector? What’s your highest-conviction pick?

This is Trump's personal portfolio: $AVGO Broadcom $DELL Dell $TXN Texas Instruments $DVA DaVita $JBL Jabil $KLAC KLA $COMT GSCI Commodity ETF $FFIV F5 $GOOGL Alphabet $ETN Eaton $NVDA NVIDIA $XLK Technology Select Sector ETF $TT Trane Technologies $COST Costco $IEMG MSCI Emerging Markets ETF $IEX IDEX $AMZN Amazon $XLI Industrial Select Sector SPDR ETF $CDNS Cadence Design Systems $AAPL Apple $VOO Vanguard S&P 500 ETF $VTI Vanguard Total Stock Market ETF $WST West Pharmaceutical $IWB Russell 1000 ETF $XEL Xcel Energy $EFA MSCI EAFE ETF $SNPS Synopsys $RSP S&P 500 Equal Weight ETF $BA Boeing $MSI Motorola $NWSA News Corp $MSTR Microstrategy $ORCL Oracle $WM Waste Management $GOVT U.S. Treasury Bond ETF $ICE Intercontinental Exchange $MARA MARA $NFLX Netflix $UBER Uber $KRMN Karman Space $HD Home Depot $TDG TransDigm $MSFT Microsoft $CVNA Carvana $COIN Coinbase $AXON Axon $ADBE Adobe $CRM Salesforce $NOW ServiceNow $WDAY Workday

@DeepIceValue LOOOOOOOL

Stocks that will drop 50% or more in next 24 months..👇 $PLTR $MU $HIMS $AMD $INTC $AMAT $TSLA $IREN $NBIS

@FeeFiFoFumDeDon @TheInverseTimes loool you are so retarded

@TheInverseTimes Until seeing Shane's lame set today, I liked him. Now he's moved to Texas? Has Shane gone MAGA? I thought he was smarter than that. Very disappointing

Chelsea Handler takes shot at Tony Hinchcliffe during the Kevin Hart Roast.

@theylove_ml sensitive lool

I don’t like this Kevin hart roast why so racist, and disrespectful or am I sensitive #theroastofkevinhart

@FullOfGraceUS you are so retarded lool

Pete Davidson just made a hilarious Charlie Kirk death joke at the Kevin Hart roast on Netflix. See, when you push for anti-wokeness you get jokes like this. Be careful what you ask for MAGA. I'm loving seeing you all cry about it.

@Polymarket well it's Oakland so. .

JUST IN: Oakland home values hit their lowest level in roughly a decade after falling 11.4% in a year.

@JBPritzker LOOOL YOU ARE ABOUT TO BE VOTED OUT FAT FUCK LOOOL

Donald Trump said his White House ballroom wouldn't cost taxpayers a dime. Now Republicans want you to pay $1 billion for it. They lied to your face, then left you the bill.

@mmpadellan fucking faggot LOOOL

So the Virginia Supreme Court is as full of shit as the US Supreme Court I'm so fucking mad right now

@TheDemocrats LOOOOL

BREAKING: The Virginia Supreme Court has voted to overturn the results of the state’s special election. This decision silences the voices of Virginians who approved an updated congressional map that levels the playing field ahead of the midterms. The fight continues.

@GavinNewsom LOOOOL

No vote in Tennessee (+1 GOP) No vote in Florida (+4 GOP) No vote in Missouri (+1 GOP) No vote in North Carolina (+2 GOP) No vote in Texas (+5 GOP) Virginia’s voter-approved maps thrown out. MAGA has rigged the system.

@Justinjpearson thats segregation my guy.

My speech on the Tennessee House Floor today as our state voted to eliminate Memphis's only majority Black congressional district.