Sandeep Anand

Investor
App: 10X Stocks: How to Pick Multibaggers

[Sandeep Anand @SanCompounding]

🚨10X Stocks - My New Book Published worldwide on April 6th

Happy to share it’s already #1 New release and #9 Best seller in Business/Valuation on Amazon 😊

The book as the title says is about:
8 Frameworks on ‘How to Pick Multibaggers’

Order 👉 10X Stocks: How to Pick Multibaggers https://t.co/aZTJWnj7c2

[Sandeep Anand @SanCompounding]

🚨 Leopold fund went All-in on Neoclouds for same reason !!

“Compute through 2027 is sold out.” — OpenAI CFO confirmed on @theallinpod

“If you do not have compute, you do not have revenue.”
OpenAI is passing on opportunities RIGHT NOW because of the shortage.

📝Market prices AI infrastructure on a 2-year horizon.
OpenAI buys on 6 year conjecture 📈
Where she feels most SHORT: 2030, 2031, 2032.

⛔️A single GW-scale data center = $50B + 3 years to build.

The plays ?

The named proxies: $ORCL $CRWV $NVDA

But the real constraint? Power and land.
The neocloud stack I’m watching:
🔲 $CRWV — $99B backlog, OpenAI + Meta locked in, take-or-pay contracts
🔲 $NBIS — AI-native cloud, NVIDIA partnership, 5GW target by 2030
🔲 $IREN — Direct NVIDIA cloud-services contract, DSX partnership
🔲 $APLD — Power + campus execution play, CoreWeave as anchor tenant
🔲 $ORCL — Hyperscaler with long-dated AI contracts

The market is still pricing this on a 2-year lens.
The CFO of the most compute-hungry company on earth is buying on a 6-year lens.
💵 That gap is the trade !!

[Sandeep Anand @SanCompounding]

$MRVL Revenue Structure — Breakdown-
How they actually report it:

Officially, $MRVL reports 2 end markets:

1/ Data center = $6.1B (74% of total) for FY2026, vs $4.2B in FY2025 and $2.2B in FY2024

2/ Communications & Other = $2.1B (26%) for FY2026

So full-year FY2026 total = $8.2B, up 42% YoY 📈

Most recently, Q1 FY2027 data center hit $1.83B (76% of revenue), with comms & other at $585M (24%)

Within Data Center — the real breakdown you want:
The two pillars are:

1. Custom Silicon / XPU (ASIC)
This is the biggest and fastest-growing bucket — Google TPUs, Amazon Trainium, and Microsoft custom AI chips.

Custom silicon programs entered volume production in Q1 FY2026 and are the primary driver of the 76% YoY data center surge .
Analyst estimates put custom at roughly 55-65% of data center revenue in FY2026, likely approaching $ 3.5-4B for the year.

2. Electro-Optics (DSPs, TIAs, laser drivers, DCI modules)
$MRVL’s electro-optics portfolio — including high-speed PAM4 DSPs, TIAs, laser drivers, and datacenter interconnect modules — leads the market and contributes substantially to AI revenue .

The most recent Q1 FY2027 call specifically called out strength in 800G and 1.6T scale-out optics, scale-up optical solutions for NPO and CPO applications, and scale-across datacenter interconnect modules .

Optics is estimated at roughly 25-35% of data center revenue !!

3. Data Center Networking / Switching
Ethernet switches (51.2T), PCIe/CXL switches (via XConn). Smaller but growing.

The forward story:
Celestial AI (acquired Feb 2026) brings Photonic Fabric optical interconnect technology for scale-up connectivity, with Marvell expecting meaningful revenue starting H2 FY2028, targeting a $500M ARR by Q4 FY28, doubling to $1B by Q4 FY2029 .

So the optics bucket is about to get a major uplift layer on top of the existing DSP/transceiver business.

The ASIC/XPU side is what’s driving the valuation re-rate — it’s why $MRVL trades at a significant premium. Optics is the asymmetric upside kicker, especially post-Celestial AI.​​​​​​​​​​​​​​​​

Trading at life-time high P/S of 30 !!

[Sandeep Anand @SanCompounding]

@Rangfeng1117 Have to agree. But no body can predict the exponential growth curves

[Sandeep Anand @SanCompounding]

Jensen calls $MRVL As next Trillion dollar company .

So let’s brainstorm the next Trillion Dollar List :

$SPCX | $1.75T (IPO target) | Direct IPO
$WMT | $817B
$ORCL | $687B
$V | $650B
$MU | >$1T Already crossed
$AMD | ~$300B
$BABA | ~$310B
$TCEHY | ~$500B

OpenAI | TBD | $852B (private)
Anthropic | TBD | $965B (private)

[Sandeep Anand @SanCompounding]

$HPE $DELL are part of DSX Platform thesis and we can see why their earnings are exploding 📈

🚨NVIDIA’s DSX Platform is the operating system for the $10T AI infrastructure buildout — covering every layer:
compute, power, cooling, facilities, and construction.

This isn’t just an NVDA story. It’s a multi-sector thesis.

The picks & shovels winners 👇🧵

1. Power & Cooling
$GEV — GE Vernova is riding electrification + AI data center power demand. Backlog hit $44B+ with grid/gas turbine orders surging. DSX certification locks in multi-year procurement pipelines.

$ETN — Eaton’s electrical segment is printing. Power management for hyperscale data centers is its fastest-growing vertical. Order backlog up 30%+ YoY, pricing power intact.

$VRT — Vertiv is the thermal/cooling king of AI racks. Revenue growing 20%+ YoY, margins expanding. DSX puts Vertiv inside every NVIDIA-certified AI factory stack globally.

2. AI Cloud / Neocloud:
$CRWV — CoreWeave IPO’d in 2025 with a $20B+ RPO (remaining performance obligations). Pure-play NVIDIA GPU cloud — DSX makes CoreWeave a natural tier-1 deployment partner.

$NBIS — Nebius is building GPU clouds across. DSX gives it a certified playbook to scale faster. Early-stage but high-conviction AI factory buildout story.

$IREN — IREN pivoting to AI compute. Low-cost power assets + DSX certification = margin expansion runway ahead.

3. Compute Systems

$HPE — HPE’s GreenLake + Cray supercomputing arm positions it well for DSX-adjacent enterprise AI. Margins under pressure but AI server mix shift is a tailwind.

$DELL — Dell’s AI server backlog crossed $14B+ with PowerEdge GPU servers flying off shelves to hyperscalers and enterprises. DSX certification makes Dell a tier-1 compute systems partner for AI factory deployments globally.

Chase AI capex to win 💵

[Sandeep Anand @SanCompounding]

🚨 “Bought my ETF in Iran panic. Doubled in 7 weeks.” !!

My tweet on4/11 : Buy this AI Basket like an ETF

🚀Just see the returns since 4/11 (almost every stock has doubled) 👇

$MRVL +130%
$TSM +123%
$CIEN +165%
$COHR +120%
$LITE +114%
$CRDO +105%
$DRAM +36%
$AAOI +112%
$VIAV +100%
$CRWV +98%
$AVGO +59%
$AXTI +50%
$NBIS +128%
$ALAB +69%
$NET +62%

Portfolio avg: +98% (~2x) in 7 weeks

Entry: Apr 10, 2026 (Iran shock low) by
@SanCompounding 👇

How I could do this??

InvestwithAI App has inbuilt AI Claude and GPT Portfolios that’s updated real time. Try using it 👉 https://t.co/HC3cAIAMcA

[Sandeep Anand @SanCompounding]

🚀 Buying this AI basket like an ETF and forget next 2 years is a good idea

1 $MRVL $67B Optical Switch/Chips
2 $TSM $1.6T Fabless capacity
3 $CIEN $61B Optical Transceivers
4 $COHR $57B Optical Transceivers
5 $LITE $40B Optical Transceivers
6 $CRDO $19B Optical /AIBConnect
7 $DRAM NA Memory ETF
8 $AAOI $10B Optical Transceivers
9 $VIAV $8.3B Optics Test/MFG
10 $CRWV $53B Hyperscaler
11 $AVGO $1.7T ASIC Chips
12 $AXTI $3.5B Optical Materials
13 $NBIS $25B Neocloud
14 $ALAB $0.7B AI Interconnect
15 $NET $58B EDGE AI

[Sandeep Anand @SanCompounding]

@Steward4Him No another post

[Sandeep Anand @SanCompounding]

🚨 NVIDIA is making the biggest power architecture pivot in data center history.

The shift to 800VDC for Rubin is NOT just a GPU upgrade.

It's a full supply chain reset — and most investors are watching the wrong ticker.

Here's the 4-layer opportunity map 🧵

Why 800VDC?

Rubin targets 200kW+ per rack.

At that density, 48V delivery creates catastrophic copper losses. You'd need busbars the size of an arm!

800VDC cuts current by ~16x at the same power level.

Thinner copper. Less heat. Smaller form factors. Higher efficiency.

This isn't a product cycle. It's an architecture RESET.

NVDA's 800VDC architecture for Rubin is the starting gun for a 4-layer power supply chain reset. Every hyperscaler building Rubin clusters must rebuild their power stack — from the grid to the GPU.

4 layers. Dozens of beneficiaries. Multi-year capex cycle locked in.

🔴 Layer 1 — SiC/GaN semiconductors
🔵 Layer 2 — Power management ICs
🟢 Layer 3 — Busbars & connectors
🟣 Layer 4 — Grid edge infrastructure

LAYER 1 🔴 — Wide Bandgap Semiconductors ($SiC / $GaN)

800V systems can't use silicon.

SiC/GaN are the ONLY materials that handle high-voltage switching at these frequencies.

Key names:
→ $NVTS — pure-play GaN/SiC fabless, highest beta
→ $ON — best-in-class EliteSiC platform
→ $STM — largest captive SiC fab in Europe
→ $WOLF — foundry economics, captures industry demand

LAYER 2 🔵 — Power Management, Gate Drivers & Protection

The GPU still runs at 0.8V–12V. Someone has to step down from 800V.

That's billions in VRM/PMIC content per Rubin cluster.

Key names:
→ $VICR — most direct 800VDC play. Factorized Power Architecture built for this
→ $MPWR — already in Blackwell. More content per Rubin socket
→ $ADI — isolated gate drivers, critical for 800V safety compliance
→ $TXN — volume play, every PSU uses their analog ICs

$VICR deserves its own separate tweet (I’ll write later).

Vicor's Factorized Power Architecture converts 800V bus → point-of-load in a single step with industry-leading efficiency.

They didn't pivot to 800VDC.

Already engaged with hyperscalers on Rubin deployments.

This is the most asymmetric bet in the entire supply chain map.

LAYER 3 🟢 — Busbars, Connectors & Power Modules

The physical copper architecture of the rack.

At 200kW per rack, connector ASP per system goes up massively.

Key names:
→ $APH — connector kingpin for AI infra, sticky design-wins
→ $TEL — certified 800V connectors = regulatory moat
→ $NVT — thermal + power distribution for high-density racks
→ $MEI — laminated busbars are core competency, deep value

LAYER 4 🟣 — Industrial Power Infrastructure

Grid edge → switchgear → transformers → DC distribution.

Long lead times. Large contracts. 10–20 year asset lives.

Key names:
→ $VRT — highest beta AI power play. Co-architected with NVDA on liquid-cooled racks
→ $ETN — PDUs + switchgear in nearly every hyperscaler globally. 800V-ready now
→ $GEV — transformer/switchgear backlog is multi-year. Grid electrification compounder
→ $SIEGY — medium-voltage DC infrastructure at scale

$VRT is the clearest pure-play on the 800VDC wave.

Vertiv's power + thermal systems are co-designed with NVIDIA for liquid-cooled, high-density deployments.

They're not chasing the market. They're co-architecting it with Jensen.

When Rubin ships at scale, VRT's order book goes vertical.

My 800VDC watchlist by conviction tier:

HIGH BETA (growth leverage):
$VICR · $VRT · $NVTS

QUALITY COMPOUNDERS (durable revenue):
$ETN · $APH · $MPWR

DEEP VALUE (overlooked):
$MEI · $AOSL

Watch procurement acceleration in H2 2026 as hyperscalers lock supply ahead of Rubin delivery.

[Sandeep Anand @SanCompounding]

@adelbucetta Valid point

[Sandeep Anand @SanCompounding]

🚨 $MU just joined the $1 Trillion club.
And this is just the beginning 📈

📈HBM memory is the bottleneck of the AI age

Why $MU wins from here:
→ HBM3E shipments ramping to $NVDA Blackwell GPUs at record ASPs
→ HBM content per GPU up 3x vs last gen — more memory per chip, every cycle
→ Data center revenue now majority of sales for first time in company history

They all need HBM. And demand is about to go parabolic. 🧵

The ecosystem that feeds $MU 👇
⚙️ $ASML — EUV lithography machines. No ASML, no leading-edge DRAM. Pure chokepoint.

🔧 $LRCX — Etch & deposition equipment. Critical for HBM stacking layers.

🧪 $AMAT — Materials engineering at atomic scale. Every memory layer runs through Applied.

🏭 $KLAC — Process control & inspection. Catches defects before they kill yields.

Nobody talks about $JBL.

Jabil is the silent backbone of the entire AI hardware supply chain — and it’s still flying under the radar.

What does Jabil actually do?
They build the physical infrastructure that houses all of it.
→ AI server enclosures & rack systems
→ Data center cooling hardware
→ Networking & optical module assemblies
→ Power management systems for GPU clusters.

[Sandeep Anand @SanCompounding]

@70Polygon It’s a France based LLM and it’s nothin else but Mistral.. but I cud be wrong

[Sandeep Anand @SanCompounding]

🚨BREAKING: $WYFI: $100 Million Facility Secured To Support AI Infrastructure Growth 📈

WhiteFiber recently had signed an AI Compute Agreement with Total Contract Value in Excess of $160 Million with Mistral AI (France)

According to Grand View Horizon, the AI market in France is expected to reach a projected revenue of US$ 130 billion by 2033 at a Compounded Annual Growth Rate (CAGR) of 30.9 percent.

[Sandeep Anand @SanCompounding]

@burrytracker Leopold is the poster child of AI https://t.co/W0A7xpZQs5

[Sandeep Anand @SanCompounding]

🚨 My APP InvestwithAI shows Leopold as #1 Fund and $DRAM as #2 based on popularity, flows and performance (returns)

LEOPOLD SITUATIONAL AWARENESS JUST DISCLOSED A 5.6% STAKE IN NEBIUS $NBIS.

Find All Leopold and all star funds Holdings here 👉 https://t.co/faPHMtacJW

[Sandeep Anand @SanCompounding]

🚨 The token economy is already here 💵
Most boardrooms just haven’t noticed yet!!
They’re measuring it in seats. Licenses.

💵The real unit of AI at scale is the token.
And once you understand tokens, the next 5 years look completely different.

🚀 $GOOG Token explosion—
2024 usage 9.7 Trillion tokens / month
2026 usage 480 Trillion tokens / month

What is a token, really?
A token is a chunk of text — roughly ¾ of a word.
Every time your AI system reads a document, writes a report, calls an API, or reasons through a decision — it’s consuming tokens.

🤖A single agentic workflow can consume 50x to 100x more tokens than a simple chatbot interaction.

Multiply that across your entire org. Every department. Every workflow. Running 24/7.

Thinking in Tokens 🧠 :
Goldman Sachs just dropped a number that should stop every tech investor in their tracks.
120 quadrillion tokens per month by 2030.
That’s 24x the token volume we’re generating today — and it’s not coming from chatbots.
It’s coming from AI agents.

Enterprise agents aren’t just answering questions. They’re planning, reasoning, using tools, calling APIs, looping back on their own outputs — generating 10x more tokens per task than a simple prompt.

Here’s what most people miss:
Yes, inference cost per token is falling 60–70% per year.
But that’s actually the accelerant, not the brake.
Cheaper tokens = more agents deployed = more tasks per agent = exponentially more tokens consumed 📈
This is ‘Jevons Paradox’ playing out in real-time inside data centers.

Why compute + memory demand will explode 👇
Every token generated needs to pass through GPU compute. At scale, that’s not just more GPUs — it’s more HBM memory to hold KV cache, more optical interconnects to move data between chips, and more power infrastructure to run it all.

The math is brutal:
∙120 quadrillion tokens/month
∙Each inference pass = memory reads + matrix multiplications
∙Agentic loops = multiple passes per task, not one

This is why $NVDA, $MU, $DRAM, $MRVL, $ALAB, $CRDO , $NBIS, $LITE , $AAOI, $INTC aren’t infrastructure plays on AI today — they’re infrastructure plays on agents at scale, which is a completely different magnitude of demand.

📣The token economy is just getting started.

[Sandeep Anand @SanCompounding]

🇺🇸 The US DOE just signed MOUs with 24 companies to advance the Genesis Mission — a national AI platform across 17 national labs to 2x American science productivity.

📈 $NVDA, $DELL, $GOOGL, $MSFT, $AMD, $ORCL, $PLTR and more just got a government-backed revenue pipeline.

💵 This isn’t a grant. It’s a procurement funnel :
$DELL already printing — $64B in AI server orders in FY26, $43B backlog. Genesis Mission is more fuel.

🧬 Science. 🔒 National security. ⚡ Energy dominance. Uncle Sam is spending. Own the picks & shovels.

$NVDA $DELL $GOOGL $MSFT $AMD $ORCL $PLTR $CRWV $INTC $IBM

[Sandeep Anand @SanCompounding]

@aleabitoreddit Yes here are $DELL upstream suppliers https://t.co/ynbEcGj573

[Sandeep Anand @SanCompounding]

🚨 $DELL just dropped a NUCLEAR earnings report 📈

📊 Revenue: $43.8B vs $34.81B est (+88% YoY) ✅
📊 Adj. EPS: $4.86 vs $2.88 est (+214% YoY) ✅
📊 AI Server Revenue: $16.1B (+757% YoY)
📊 AI Orders: $24.4B

The AI infrastructure supercycle is REAL.
But here’s who benefits even more than $DELL itself 👇

🔹 $TSSI — Dell’s primary AI rack integration partner. 99% of revenue tied to Dell, and Dell just printed $16B in AI servers. New Georgetown facility just came online with 3x capacity for liquid-cooled rack testing — exactly what Dell’s next-gen AI servers need. Pure leverage play on Dell’s backlog.

🔹 $BRUN — NVIDIA Preferred Cloud Partner with $940M in contracted revenue and $375M+ ARR target by year-end. Delivers GPU compute, managed Kubernetes, and HPC workloads — the demand side of everything Dell is building out.

[Sandeep Anand @SanCompounding]

@jukan05 Makes sense. Precisely why $DRAM ETF is #2 with surging flows per my App InvestwithAI https://t.co/faPHMtacJW

[Sandeep Anand @SanCompounding]

🚨 $DELL just dropped a NUCLEAR earnings report 📈

📊 Revenue: $43.8B vs $34.81B est (+88% YoY) ✅
📊 Adj. EPS: $4.86 vs $2.88 est (+214% YoY) ✅
📊 AI Server Revenue: $16.1B (+757% YoY)
📊 AI Orders: $24.4B

The AI infrastructure supercycle is REAL.
But here’s who benefits even more than $DELL itself 👇

🔹 $TSSI — Dell’s primary AI rack integration partner. 99% of revenue tied to Dell, and Dell just printed $16B in AI servers. New Georgetown facility just came online with 3x capacity for liquid-cooled rack testing — exactly what Dell’s next-gen AI servers need. Pure leverage play on Dell’s backlog.

🔹 $BRUN — NVIDIA Preferred Cloud Partner with $940M in contracted revenue and $375M+ ARR target by year-end. Delivers GPU compute, managed Kubernetes, and HPC workloads — the demand side of everything Dell is building out.

[Sandeep Anand @SanCompounding]

@SaiseiInvesting @joedab12 I added more $AAOI , $LITE too 📈

[Sandeep Anand @SanCompounding]

$SNOW UP 35%

It’s in Top 5 holdings of Altimeter capital, which is nominated as a top performing fund in my App InvestwithAI

Try the App to see Top Funds, their holdings and rationale : https://t.co/HC3cAIAMcA

You can also have Claude and ChatGPT create stock portfolios for you 📈 👇