They’re built by recognizing a new disruptive theme before the market fully understands it.

Every major wealth-creation cycle follows the same pattern.

A new disruptive technology emerges.

Capital pours into the infrastructure supporting it.

The companies controlling the bottlenecks create the most value.

That’s happening today.

• AI is changing how intelligence is produced.

• Robotics is bringing AI into the physical world.

• Photonics is replacing copper as AI clusters demand faster data movement.

• Power is becoming the limiting factor for AI growth.

• Space is becoming communications, defense, and digital infrastructure.

• Rare earths sit inside the motors, magnets, and electronics powering the next industrial revolution.

By the time these shifts become obvious, much of the easy money has already been made.

The goal isn’t to chase headlines.

It’s to identify where capital must flow next.

Why Invest in Thematic ETFs?

Disruptive themes are larger than any single company.

AI needs chips, memory, networking, cooling, power, and grid infrastructure.

Robotics needs processors, sensors, motors, joints, power electronics, and rare earth magnets.

The theme can succeed while an individual company fails.

Thematic ETFs spread that risk across the supply chain while providing access to foreign leaders, overlooked suppliers, and multiple potential winners.

They are also useful research tools.

Even without buying the fund, its holdings can reveal which companies control the most important parts of the ecosystem.

The Seven ETFs Built for the Next Decade

The next decade will be shaped by seven critical systems:

AI infrastructure, photonics, space, robotics, energy, grid infrastructure, and rare earths.

Each ETF below provides exposure to one essential layer of that buildout.

They were selected for:

• Thematic purity

• Holdings quality

• Bottleneck exposure

• Research value

The goal is not to own every fund.

It is to understand what each ETF owns, which part of the ecosystem it captures, and whether it offers better risk-adjusted exposure than selecting individual stocks.

SMH - VanEck Semiconductor ETF

The Foundation of AI Infrastructure

Every AI breakthrough begins with a semiconductor.

The winning AI model may change.

The companies supplying the chips are far less likely to.

$SMH provides broad exposure to the companies building the foundation of AI compute:

• AI accelerators: Nvidia, AMD

• Foundries: TSMC

• Networking & custom silicon: Broadcom

• Memory: Micron

• Lithography: ASML

• Chipmaking equipment: Applied Materials, Lam Research, KLA

Whether AI demand comes from OpenAI, Google, Meta, Microsoft, Amazon, or xAI, the semiconductor supply chain benefits.

Expense ratio: 0.35%
Best for: Core exposure to AI compute infrastructure
Key risk: Semiconductor-cycle volatility and concentration

Verdict: If you only want to own one AI infrastructure ETF, SMH is the benchmark.

DRAM - Roundhill Memory ETF

The AI Memory Bottleneck

AI models need more than processors.

They need HBM, DRAM, and NAND to feed data into accelerators and store massive datasets.

GPUs provide the compute. Memory keeps them fed.

$DRAM focuses on the companies supplying that memory stack:

• HBM & DRAM: Micron, SK Hynix, Samsung

• NAND: SanDisk, Kioxia

• Enterprise storage: Western Digital, Seagate

As AI models become larger and inference scales, memory is becoming one of the industry’s most valuable bottlenecks.

Expense ratio: 0.65%
Best for: Focused exposure to AI memory and storage.
Main risk: Memory pricing cycles and short operating history.

DRAM is the purest ETF for investors who believe memory demand will continue to outpace traditional semiconductor growth.

LAZR - Tema Photonics & Optical ETF

The AI Data-Movement Bottleneck

GPUs create intelligence. Photonics moves it.

As AI clusters grow, copper is reaching its physical limits.

Optical networking delivers higher bandwidth with lower latency and lower power consumption.

$LAZR provides exposure across the optical ecosystem:

• Optical components: Lumentum, Applied Optoelectronics

• Compound semiconductors: AXT, Aixtron

• Silicon Photonics: Tower Semiconductor

• Fiber Infrastructure: Furukawa Electric

• Testing equipment: Aehr Test Systems

The fund is actively managed in partnership with SemiAnalysis, one of the leading AI infrastructure research firms.

Now the part almost nobody has noticed.

The fund’s second-largest position is a private stake in Anthropic, roughly 12% of the portfolio.

You cannot buy Anthropic on any exchange. This is one of the only public wrappers that owns it.

Expense ratio: 0.75%
Best for: Focused exposure to optical networking and silicon photonics.
Main risk: Short operating history, high concentration, low assets, and private-company exposure.

LAZR is one of the few ETFs providing focused exposure to one of AI’s fastest-growing infrastructure layers.

NASA - Tema Space Innovators ETF

The Commercial Space Economy

Space is no longer just exploration.

It has become communications, defense, launch, and digital infrastructure.

$NASA owns companies across the space stack:

• Launch: SpaceX, Rocket Lab, Firefly Aerospace

• Satellite communications: AST SpaceMobile, Viasat, EchoStar

• RF components: Filtronic

• Lunar infrastructure: Intuitive Machines

The SpaceX position deserves attention. It sits near the top of the fund at over 13% through a pre-IPO SPV.

Expense ratio: 0.75%
Best for: Concentrated exposure to commercial space infrastructure
Main risk: High concentration, private-asset valuation risk, and space-company volatility.

NASA is one of the few ETFs offering great exposure to the rapidly expanding commercial space economy.

KOID - KraneShares Global Humanoid Robotics and Physical AI ETF

The Physical AI Supply Chain

Most investors focus on the robot makers. The bigger opportunity may be the companies supplying every robot.

$KOID provides exposure across the humanoid robotics supply chain:

• AI and control: Nvidia, Monolithic Power Systems, Texas Instruments

• Sensors and perception: Cognex, Sensata, Teledyne

• Motors and actuation: Allient, Regal Rexnord, Nidec

• Precision motion: THK, Harmonic Drive Systems, RBC Bearings

• Rare earth materials: MP Materials, Lynas Rare Earths

• Robot makers and integrators: UBTech, Symbotic

The fund tracks the full physical AI ecosystem rather than betting only on the company assembling the final robot.

It holds around 50 names, equal weighted, so no single winner dominates and no single failure sinks it.

Expense ratio: 0.69% net (0.79% gross)
Best for: Exposure to the complete humanoid robotics supply chain
Main risk: Early-stage industry and international exposure

KOID is the strongest ETF for investors who want exposure to the robotics supply chain instead of trying to predict the winning robot manufacturer.

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Genomics is one of the few industries where biology, AI, and computing are converging at scale.

Many investors lost interest after the biotech selloff in 2021. Capital moved to AI, and genomics faded from the headlines.

The technology didn’t stop.

Sequencing costs continued to fall. The first CRISPR therapy reached the market. AI began transforming drug discovery, diagnostics, and biological research.

Today, genomics sits at the intersection of biology, artificial intelligence, and computing. That convergence has the potential to reshape healthcare over the next decade.

In this report, we’ll break down genomics in simple terms, explores the companies building the ecosystem, and concludes with the six genomics stocks I believe are best positioned to benefit from this long-term trend.

What Is Genomics?

Every cell in your body contains DNA.

Think of DNA as the instruction manual for building and maintaining life. It determines everything from eye color to how your body functions.

A genome is the complete set of DNA instructions inside an organism.

Genomics is the study of those instructions. Scientists sequence DNA to identify mutations, understand diseases, develop targeted therapies, and improve how medicine is practiced.

Just as software engineers read and write computer code, scientists are learning to read, analyze, and increasingly edit the genetic code of life.

The better we can understand that code, the better we can diagnose diseases, develop new drugs, and personalize treatments for individual patients.

Why Genomics Matters

Medicine has traditionally treated disease after symptoms appear.

Genomics makes it possible to identify genetic risk earlier, diagnose diseases sooner, and tailor treatments to an individual’s DNA.

This shift is already underway.

Doctors are using genomic testing to match cancer patients with targeted therapies, screen for inherited diseases, and improve treatment decisions.

The investment opportunity extends beyond healthcare.

Every genome sequenced generates new biological data. That data improves AI models, accelerates drug discovery, and advances precision medicine.

More sequencing creates more data.

More data leads to better insights.

Better insights improve medicine.

That cycle is one of the strongest long-term drivers behind genomics.

Why Now?

Genomics has existed for decades.

The difference today is that the technology has reached an inflection point.

Three forces are converging at the same time: cheaper sequencing, better AI, and exponentially more computing power.

Sequencing Costs

The cost of sequencing a human genome has fallen from nearly $100 million in 2001 to under $200 today.

Lower costs are driving more sequencing, creating larger datasets for research, diagnostics, and drug discovery.

Artificial Intelligence

AI is making genomic data far more valuable.

Researchers can now analyze millions of DNA sequences, identify disease-causing mutations, predict protein structures, and accelerate drug discovery at a scale that wasn’t previously possible.

Dario Amodei, CEO of Anthropic, believes biology could become AI’s most important application. In Machines of Loving Grace, he argues that advanced AI could compress decades of biological research into just a few years.

If that vision proves even partially correct, genomics could become one of the largest beneficiaries of the AI revolution.

Better Computing

Cloud computing and GPUs can process genomic datasets at a scale that was impractical just a few years ago, enabling faster analysis and more complex AI models.

Clinical Adoption

Genomics is becoming part of routine healthcare.

Doctors increasingly use genomic information to:

• Diagnose rare diseases

• Match patients with targeted therapies

• Improve drug development

• Personalize treatment

The Flywheel

Every new genome strengthens the ecosystem.

This flywheel is one of the strongest reasons genomics is evolving from a healthcare niche into a long-term technology platform.

It becomes more valuable as more data is generated, analyzed, and applied to patient care.

The Genomics Ecosystem

Genomics isn’t a single business.

It’s an ecosystem where each company plays a different role. Some build the machines that read DNA. Others analyze the data, develop diagnostic tests, or create new medicines.

Understanding where a company fits is the first step in evaluating its long-term potential.

1. Sequencing

These companies build the platforms that read DNA.

Without sequencing, the rest of the ecosystem doesn’t exist.

• $ILMN - Illumina. ~80% global market share. The dominant short-read sequencing platform.

• $PACB - Pacific Biosciences. Long-read sequencing pure-play. Best-in-class accuracy for clinical applications.

• $TMO - Thermo Fisher Scientific. Diversified life sciences giant with significant sequencing exposure.

• $A - Agilent Technologies. Instruments, tools, and consumables across life sciences research.

2. Tools, Reagents & Synthetic Biology

These companies make the inputs every experiment runs on.

If sequencing reads DNA, this category writes it, preps it, and supplies the chemistry.

• $TWST - Twist Bioscience. Silicon-based synthetic DNA platform. The picks-and-shovels of the entire R&D ecosystem.

• $DHR - Danaher. Diversified life sciences conglomerate. Beckman Coulter, Cytiva, and other operating companies.

• $QGEN - Qiagen. Sample preparation and molecular diagnostics. Essential infrastructure for every research lab.

• $TECH - Bio-Techne. Reagents and instruments across research workflows. Steady compounder.

3. Diagnostics

These companies use genetic information to detect disease, guide treatment decisions, and monitor patients.

• $NTRA - Natera. Signatera test for cancer recurrence. Profitable trajectory with growing reimbursement.

• $GH - Guardant Health. Liquid biopsy specialist with deep oncology relationships.

• $EXAS - Exact Sciences. Cologuard at-home colon cancer screening, plus Oncotype DX cancer recurrence portfolio.

4. AI & Bioinformatics

These companies turn biological data into useful insights.

Their software helps researchers identify patterns, discover drug targets, and accelerate scientific research.

• $TEM - Tempus AI. AI platform matching cancer patients to therapies based on genetic profiles. Deployed in major US cancer centers.

• $RXRX - Recursion Pharmaceuticals. AI-native drug discovery platform, strengthened by the Exscientia acquisition.

• $ABCL - AbCellera. AI-powered antibody discovery platform with broad pharma partnerships.

5. Gene Editing

These companies develop technologies that modify DNA to treat or potentially cure genetic diseases.

The category just received major validation: Eli Lilly acquired Verve Therapeutics for up to $1.3 billion in June 2025, signaling that big pharma is willing to pay real money for gene editing platforms.

• $CRSP - CRISPR Therapeutics. Co-developer of Casgevy, the first FDA-approved CRISPR therapy. Real revenue today.

• $NTLA - Intellia Therapeutics. In-vivo CRISPR editing leader.

• $BEAM - Beam Therapeutics. Base editing pioneer. More precise than standard CRISPR.

• $PRME - Prime Medicine. Prime editing with “search and replace” precision.

• $QURE - uniQure. Established gene therapy company with rare disease focus.

6. Drug Discovery & Precision Medicine

These companies use genomic data to develop the next generation of medicines.

Pharmaceuticals & Therapeutics

• $LLY - Eli Lilly. Aggressive acquirer in genetic medicine. Bought Verve in 2025. Mega-cap with the cash flow to fund the buildout.

• $REGN - Regeneron. Genetic Medicines unit applying genomics to drug development.

• $VRTX - Vertex. Cystic fibrosis franchise plus the commercial partner on Casgevy. Strong cash flow funding genomic medicine bets.

• $MRNA - Moderna. mRNA platform proven at scale during COVID. Pipeline expanding into oncology and rare disease.

• $BNTX - BioNTech. mRNA pioneer with deep oncology pipeline.

• $BMRN - BioMarin. Specialty rare disease focus with strong genomic tilt.

Visual Summary

My 6 High-Conviction Genomics Stocks

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They watch CNBC. They check X and Stocktwits.

They have alerts on 20 tickers.

Their watchlist is a graveyard of names they bought, ones their friends mentioned, and ones some podcast hyped six months ago.

This is how you lose.

Wealth doesn’t get built by tracking more. It gets built by tracking less, and tracking the right things.

I track nine disruptive themes. Every day.

Everything else is noise.

1. AI Infrastructure.

The GPU compute build-out.

The most obvious theme on the board. Also the most underestimated.

Every AI model needs compute. Every compute cluster needs data centers.

Every data center needs power.

The companies building, leasing, and operating that infrastructure are absorbing capital faster than they can deploy it.

Hyperscalers spent $364 billion on data center buildouts in 2025.

They’re spending more in 2026. The neocloud operators are booked two years forward.

$NBIS (Nebius) – Microsoft-backed neocloud with a $19.4B Microsoft commitment.

$CIFR (Cipher Mining) – Bitcoin miner pivoting to AI compute. Cash-flowing transition story.

$IREN (IREN Limited) – $9.7B Microsoft cloud deal. $9.7B Microsoft cloud deal. 150,000 GPU fleet target by end-2026, GB300 Blackwell systems deploying through Childress.

Simple way to think about it: Sell the picks during the gold rush. Each of these names is selling a different kind of pick.

2. Photonics

AI's bandwidth bottleneck.

Compute scales. Bandwidth doesn’t.

As AI clusters grow, the wiring between GPUs becomes the bottleneck.

Photonics solves that.

Optical interconnects are the only way to move data fast enough inside modern AI training racks.

$LITE (Lumentum) – Largest pure-play optical components company.

$AAOI (Applied Optoelectronics) – Hyperscaler optical transceivers. The AI tailwind hit them hardest in 2025.

$AXTI (AXT Inc) – Indium phosphide substrates. Every optical chip starts here.

$CIEN (Ciena) – The networking layer that connects data centers across geographies.

Simple way to think about it: Without photonics, there’s no AI cluster. These companies make the wires that light moves through.

3. Space

The launch and satellite broadband economy.

Launch costs have dropped 95% in the last decade.

Satellite broadband is becoming the new global utility.

Government contracts are exploding. The space economy is real, not science fiction.

$RKLB (Rocket Lab) – The next SpaceX. Neutron launch vehicle plus growing space systems business.

$ASTS (AST SpaceMobile) – Direct-to-cell satellite broadband. AT&T and Verizon partnerships.

$PL (Planet Labs) – Earth observation. The Google Maps of satellite imagery.

$LUNR (Intuitive Machines) – Lunar economy infrastructure. NASA partnership.

Simple way to think about it: The next economy isn’t only on Earth. A growing chunk of it sits 200 miles above the surface.

4. Robotics

The physical AI sensing layer.

AI is moving out of the data center and into the physical world.

Humanoid robots. Autonomous vehicles. Industrial automation. All of them need to see and feel.

The sensing layer is where the asymmetric upside lives, not the headline-grabbing robot company.

$OUST (Ouster) – LiDAR pure-play. Solid-state digital LiDAR. The cheapest scale-ready sensor.

$AMBA (Ambarella) – Edge AI vision processors. The brain behind every smart camera.

$VPG (Vishay Precision Group) – Force sensing for cobots. The least-known, most asymmetric robotics name.

Simple way to think about it: Every robot needs to see and feel. These companies build the eyes and the skin.

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The Drone Supercycle Has Started.

A $500 drone can now destroy a $10 million tank.

That single fact is quietly rewriting which drone stocks win the next decade.

History has a pattern. The tools of dominance always get cheaper.

Castles became obsolete against gunpowder artillery.

Multi-million dollar battleships were neutralized by cheap torpedo bombers in WWII.

The pattern is repeating. Faster this time.

Cheap autonomous systems are changing the economics of war.

And defense budgets are shifting accordingly.

The defense tech companies building the cheap, smart machines are about to capture a generational wave of spending.

The Battlefield Already Proved It

Every major military has watched the same thing play out on modern battlefields.

FPV drones costing a few hundred dollars taking out tanks worth millions.

The lesson was obvious:

Modern warfare is becoming:

• Autonomous

• Software-defined

• Cost-efficient

• Mass-deployable

Governments reacted quickly.

The US proposed roughly $1 trillion in defense funding for 2026, including major increases tied to autonomous systems and missile defense.

At the same time, the Pentagon accelerated procurement reforms around NDAA-compliant drone suppliers.

This is no longer experimental technology.

This is active procurement.

The Bottleneck

Demand is not the bottleneck.

Supply is.

For years, most drone manufacturing and components were concentrated overseas.

Now Western militaries want:

• Domestically made drones

• Secure, traceable components

• NDAA-compliant systems

• Resilient supply chains

• Combat-proven platforms

That creates a narrow supplier base.

The old defense model favored giant contractors building billion-dollar systems over decades.

The new model favors:

• Autonomous systems

• AI-enabled targeting

• Rapid iteration

• Software-defined warfare

That shift is already pulling capital toward newer defense-tech companies like Palantir Technologies and Anduril Industries.

The suppliers enabling this shift may capture the largest upside.

The Two Sides of the Drone War

Every drone war has two sides:

The systems that attack. And the systems that stop them.

The attack layer includes:

• FPV drones

• ISR systems

• Loitering munitions

• Autonomous combat aircraft

The defense layer includes:

• Counter-UAS systems

• Electronic warfare

• Radar systems

• Drone interceptors

• Signal jamming

Both markets are growing rapidly.

My Top 3 High-Conviction Drone Stocks

I focus on three things:

Real revenue. Real contracts. Real moats, especially the kind reinforced by regulation and national security.

I screened the whole sector. 3 companies stood out.

• One builds combat-proven drones, profitable, with over a billion in contracts.

• One owns the counter-drone side, profitable, with a massive cash war chest.

• One builds combat aircraft at scale, with a record backlog few have noticed.

The Drone Supercycle may create generational wealth for early investors.

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Most investors think the AI infrastructure story is about chips.

It isn’t.

It’s about how those chips communicate.

And the best photonics stocks of 2026 are sitting at the center of that shift.

You can build the most powerful AI chip in the world, but if data cannot move fast enough between GPUs, the entire system becomes constrained.

That is the bottleneck hyperscalers are trying to solve right now.

As AI clusters scale, thousands of GPUs need to communicate in real time.

Traditional copper interconnects struggle to keep up without creating major power, heat, and latency issues.

The AI industry is now being forced toward photonics - using light instead of electrical signals to move data across AI infrastructure.

The biggest AI fortunes may come from infrastructure. Photonics sits right in that path.

The names below are the hidden gems, small caps, and leaders quietly setting up before Wall Street fully prices the shift.

The Signal the Market Just Got

One of the clearest signals about how important this layer has become came from Nvidia.

The company recently committed billions to photonics suppliers like Lumentum ($LITE) and Coherent ($COHR) while securing long-term laser supply agreements.

That move tells you something important.

Nvidia already solved the compute problem with GPUs. Now, the bottleneck is moving data between those GPUs.

As AI systems grow larger, the amount of data moving between chips increases exponentially.

Photonics is becoming the only practical way to move massive amounts of AI data efficiently.

The Upgrade Cycle Most Investors Don’t See

AI networking advances in major bandwidth jumps.

The industry recently transitioned from 400G to 800G optical networking, and the next upgrade cycle is already approaching.

1.6T networking is expected to begin rolling out later this year.

Each transition significantly increases the bandwidth required inside AI clusters, driving demand for faster optical interconnects and infrastructure.

The Layer Most Investors Ignore

Most people simplify the AI stack to:

GPU → Data center → AI model

But the real infrastructure stack is far more complex:

Compute chips → Transceivers → Optical engines → Fiber networks → AI clusters

Photonics sits at the center of that system.

It’s the infrastructure layer that allows thousands of GPUs to communicate fast enough to function as a single AI cluster.

Once you understand the bottleneck, the ecosystem starts to make sense.

Photonics Ecosystem:

• Optical Hardware: $COHR $LITE $AAOI $LASR $SIVE

• Optical Networking: $CIEN

• Advanced Packaging: $ASX $AMKR $FN

• Silicon Photonics Foundries: $TSM $INTC $GFS $STM $TSEM

• High-Speed Optical Connectivity: $AVGO $MRVL $CRDO $ALAB $POET $MTSI $SMTC

• Optical Materials & Substrates: $AXTI $GLW $IPGP $ALMU $LWLG

• Test & Measurement: $AEHR

My Top 5 High-Conviction Photonics Stocks

The AI infrastructure shift is creating new winners. But not every photonics company will win equally.

These are the 5 photonics stocks I believe have the strongest risk/reward for the next phase of the AI buildout.

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The best small cap stocks of 2026 won't look obvious today.

Most investors think big returns come from finding the next Nvidia.

Usually, that means they’re already late.

By the time a winner feels obvious, institutions are already positioned, analysts are upgrading it and much of the easy upside is gone.

Peter Lynch used a different playbook:

Find smaller companies tied to real demand before Wall Street fully notices.

That still works.

My framework is simple:

1. Find the disruptive theme

2. Find the bottleneck

3. Find the small company solving it

4. Buy at the right price

Right now, I’m focused on 5 small caps positioned in AI infrastructure, robotics, defense tech, and next-gen power.

Get my Best Stock Ideas

A quick note before we start

Good investing means updating your view when the facts change.

POET Technologies was an original pick in this report. Then Marvell canceled orders. That introduces enough uncertainty to pull the thesis. I’d rather explain the change than pretend it didn’t happen.

Capital should follow clarity, not attachment. POET is out. Cleveland-Cliffs is in.

1. Ouster ($OUST)

The Eyes of Machines | Theme: Robotics

Ouster builds lidar sensors, the technology that lets robots and self-driving vehicles perceive the world in 3D.

If a machine needs to navigate the physical world, it probably needs what Ouster makes.

Why It Matters

We’re in the early innings of a physical AI buildout. Factories automating. Roads mapped for autonomous vehicles. Cities getting smarter.

All of it requires machines that can perceive and navigate the real world.

Potential Drivers

• One of the only pure-play robotics perception stocks you can actually buy as a retail investor

• Exposure across robotics, autonomy, and smart infrastructure

• Acquired Stereolabs, moving from selling sensors to selling the intelligence layer above them

The Real Play

Robots can’t move without knowing where the world is. Ouster sells that knowledge and is one of the clearest ways for individual investors to own that bet.

Best Entry Zone: $26–$28

2. Alpha and Omega Semiconductor ($AOSL)

AI Power Bet | Theme: Power Infrastructure

AOSL makes power semiconductors, the components that regulate and convert electricity inside servers, GPU clusters, EVs, and industrial systems.

They built the world’s first power controller for Nvidia’s Blackwell GPUs and are already embedded in the supply chain most investors aren’t watching.

Why It Matters

The AI buildout needs GPUs. But every GPU needs stable, precise power delivery to run at full capacity.

AOSL built the world’s first power controller for Nvidia’s Blackwell GPUs. They solved that problem before anyone else.

Potential drivers

• First mover on Nvidia’s Blackwell GPU power controller , already in the supply chain

• The 800V data center transition creates a new design cycle, new contracts, new market share

• Rising AI demand increases power needs

Best Entry zone: $34–$36

Get my Best Stock Ideas

3. Cleveland-Cliffs Inc. ($CLF)

AI Grid Bottleneck Bet | Theme: Grid Modernization

CLF is the only domestic U.S. producer of Grain-Oriented Electrical Steel (GOES), the critical material inside every transformer core.

Without it, electricity cannot be efficiently stepped up or down across the grid. They’re also building a new transformer manufacturing plant expected to come online in 2026.

Why It Matters

Everyone is focused on compute capacity. Nobody is talking about grid capacity.

The U.S. is facing a transformer shortage with lead times stretching years. CLF is the only American company that makes the steel that goes inside them.

Now, CLF is moving downstream to build the transformers itself.

Potential drivers

• Only U.S. producer of GOES - Domestic supply chain advantage that tariffs and reshoring policy only strengthen

• Transformer lead times stretching 3–5 years nationally, creating rare pricing power for a domestic supplier

• New transformer plant adds a downstream revenue stream on top of the existing steel business

The Real Play:

Large power transformer lead times have stretched to 24–48 months. A shortage this deep doesn’t resolve quickly, and CLF sits at the chokepoint.

Best Entry Zone:

$9.50–$10.75

Deep value industrial name. Better risk/reward near support zones rather than chasing rallies.

4. Red Cat Holdings ($RCAT)

Defense Drone Bet | Theme: Defense Tech

Red Cat builds tactical drone systems for the U.S. military and allied forces.

Its Black Widow drone, made in America and NDAA-compliant, is the sole winner of U.S. Army’s primary small drone contract.

Why it matters

Modern warfare is being rewritten around cheap, autonomous, expendable drones.

RCAT’s revenue surged in 2025, driven by military adoption and expanded manufacturing to meet U.S. and NATO demand

Potential drivers

• The Army’s SRR program covers 5,880 Black Widow drones over five years, up to $260 million in total contract value

• NATO approval and Foreign Military Sales open international demand beyond the U.S. Army

• Domestic manufacturing may matter

The real play:

The U.S. military decided drones are the future of frontline warfare. Red Cat won the Army’s primary small drone contract. At a small-cap valuation, you’re buying in before the volume ramp

Best zone: $10.20–$11.00

Get my Best Stock Ideas

5. Navitas Semiconductor ($NVTS)

Power Efficiency Bet | Theme: Power Semiconductors

Navitas makes GaN and SiC power semiconductors, the next generation of chips that move electricity faster, run cooler, and waste less energy than traditional silicon.

They go inside AI data centers, EV chargers, solar inverters, and industrial systems anywhere that power efficiency has a dollar value attached to it.

Why it matters

As AI racks get denser and power demands climb, the cost of inefficiency compounds.

Navitas estimates GaN and SiC technologies can support a 100x increase in server rack power capacity for AI data centers, representing a $2.6 billion market potential by 2030.

Nvidia selected Navitas as a power semiconductor partner for its next-generation 800V DC architecture in AI factory computing.

Potential drivers

• Nvidia collaboration spans three power conversion stages inside 800V data centers, with volume production targeted for 2027

• Customer pipeline grew 92% in one year to $2.4 billion, with the data center segment more than doubling year-over-year

• Rising power demand rewards efficiency

The real play

Silicon runs hot and wastes power. GaN and SiC don’t.

Every AI rack that gets built is an argument for switching. Navitas has the Nvidia relationship, the technology, and a $2.4 billion pipeline.

Best Entry Zone: $12–$14

Final Thought

Most investors chase what is already visible. By the time a theme makes headlines, the stocks have already moved.

The five names in this report sit one layer below the headlines. They supply the perception, the power, the steel, the drones, and the efficiency that the AI era runs on.

Nobody is writing cover stories about them yet.

That is the point.

Disclosure: For informational purposes only. Not investment advice. It reflects my personal opinions for research and discussion purposes only. I may hold positions mentioned and may change positions at any time without notice. Do your own research.

A few months ago, these disruptive themes were everywhere. They dominated headlines, timelines, and investor attention.

Then they pulled back.

And attention disappeared.

But the fundamentals didn’t change.

That’s where real opportunities form.

Right now, three disruptive themes are starting to turn again.

AI Energy

AI demand is not compute-limited anymore. It’s getting power-limited.

Hyperscalers are racing to secure long-term energy contracts before they scale further.

The bottleneck has shifted upstream.

Why now:

• Data center power demand is inflecting faster than grid expansion

• Long-term contracts are being locked in now, not later

AI Energy Watchlist

AI Energy Leaders

• BE (Bloom Energy) → On-site power generation addressing data center energy constraints

• CEG (Constellation Energy) → Nuclear generation with exposure to large-scale energy demand

• VRT (Vertiv) → Data center infrastructure (cooling and power systems)

AI Energy Asymmetric Stocks (High Upside with risk)

• NVTS (Navitas Semiconductor) → Power efficiency technologies for higher-density compute

• OKLO (Oklo) → Advanced nuclear with optionality tied to future energy demand

• FLNC (Fluence Energy) → Energy storage exposure as grid variability increases

Quantum Computing

Quantum computing uses quantum physics to solve certain complex problems much

faster than regular computers.

It could impact areas like drug discovery, cybersecurity, and optimization.

Still early and speculative, but the upside is significant if it scales

Why now

• Government capital accelerating development cycles

• Strategic pressure (defense, cryptography) forcing progress

Quantum Computing Watchlist

Quantum Computing Leaders

• IONQ (IONQ Inc) → builds trapped-ion quantum computers for commercial and government use

Quantum Computing Asymmetric Stocks (High Upside with risk)

• INFQ (Infleqtion inc) → develops software and algorithms to make quantum computers useful for real-world applications

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eVTOL

eVTOL are electric flying vehicles for short city travel. They can also be used in

defense for logistics, surveillance, and rapid troop movement.

If adopted at scale, they can reshape both urban transport and military operations.

Why now:

• Certification milestones approaching

• Defense partnerships accelerating validation

eVTOL Watchlist

eVTOL Leaders

• ACHR (Archer Aviation) → Develops electric air taxis with defense ties (including Anduril Industries) and commercial airline partnerships

• JOBY (Joby Aviation) → Builds electric vertical aircraft with leading certification progress and partnerships with Delta Air Lines and the U.S. Department of Defense

Disclosure: For informational purposes only. Not investment advice. It reflects my personal opinions for research and discussion purposes only. I may hold positions mentioned and may change positions at any time without notice. Do your own research.

The Physics of Wealth: Why I Bet on Systems, Not Stocks

Wealth is not found by picking a winning stock.

Wealth is found by owning the transition.

Most investors are looking for a needle in the haystack.

I am looking for the haystack that is about to catch fire.

When an industry reaches an inflection point, it doesn’t lift one company.
It lifts the entire system.

I call this Structural Compounding.

Right now, five distinct layers are merging into a single, massive infrastructure play.

1. Photonics

AI has a physics problem.
Copper wires can only move data so fast before they overheat and fail.
The “brain” is ready, but the “nervous system” is lagging.

The shift to Photonics is mandatory.
If we want faster AI, we must move from electricity to light.

Stocks to watch:
$AAOI $LITE $COHR $POET $LWLG $IQE

2. Space Infrastructure

Every major wealth cycle adds a new layer to the planet.

The internet added a digital layer. The cloud added a storage layer.
Now, Space is adding the connectivity layer.

Satellites are no longer experiments; they are the backbone of global data.

Stocks to watch:
$RKLB $ASTS $PL $SATL $BKSY

3. Robotics & Physical AI

Software was the first wave.

Now it’s moving into the real world.

Robots now can see, understand and act in physical environments:

Warehouses
Manufacturing
Logistics
Defense

This is where AI becomes tangible.

And once it works, adoption compounds fast.

Stocks to watch:
$TSLA $SYM $PATH $TER $ROK

4. Energy

AI and robotics both need power.

A lot of it.

And that demand doesn’t negotiate.

More compute → More energy
More automation → More energy

So money flows into:

• Nuclear

• Grid expansion

• Storage

Because it has to.

Stocks to watch:
$SMR $OKLO $CEG $BE $VST

5. Defense Tech

Defense doesn’t move loudly. But it moves consistently.

And it’s shifting toward:

• Drones

• Autonomous systems

• AI-driven decisions

Spending isn’t going away.
It’s evolving.

Stocks to watch:
$AVAV $KTOS $ONDS

Final Thought

These five themes are not separate bets.
They are one singular, interlocking machine.

AI creates demand
Photonics moves the data
Robotics applies the intelligence
Energy powers the entire operation
Space and defense expand the reach

When you own the system, you aren't gambling on a CEO's personality.
You are betting on the inevitable direction of human progress.

Build your system. Trust the physics.

Everyone knows the obvious space stocks.

$RKLB, $ASTS.

And soon, possibly:

SpaceX IPO.

That changes everything.

Because when SpaceX goes public, it doesn’t just attract capital to one company.

It pulls global attention, liquidity, and narrative into the entire space economy.

Satellites. Launch. Earth observation. Defense.

That’s how cycles work.

The leader gets the spotlight. The ecosystem gets repriced.

But attention is not where asymmetric returns come from.

The real money is made in the small-cap space stocks sitting in the supply chain before everyone notices.

The Real Opportunity

Space is a stack:

Launch → Satellites → Data → Intelligence → Applications

Most investors chase the last layer.

The money is usually made earlier.

And a few small cap companies are positioned right in this layer with massive upside.

5 Small-Cap Space Stocks with Huge Upside

1. $SATL - The Platform Layer

Satellogic is not a single product. It’s an integrated space data platform.

They combine:

• Earth observation satellites
• Geospatial data analytics
• Scalable imaging infrastructure

Into one system.

Instead of selling hardware, they sell data at scale.

Simple way to think:
A vertically integrated data engine for Earth intelligence.

Why asymmetric:
If demand for real-time geospatial data explodes, the value shifts to platforms that own both capture and distribution.
They scale by expanding constellation density and monetizing data layers.

2. $SPIR - The Data Layer

Market Cap: 375M

Spire owns satellites. But that’s not the business.

The real product is data.

They track:

• Global weather patterns
• Ships in oceans
• Aircraft movement

Then sell that data to:

• Logistics companies
• Governments
• Insurance firms

Simple way to think:
Like Bloomberg, but for Earth data.

Customers don’t care about satellites.

They care about the information.

Why asymmetric:
Once customers depend on the data, it becomes recurring.
High-margin, scalable business on a small base.

3. $BKSY - The Intelligence Layer

BlackSky also uses satellites. But goes one step further.

They don’t just collect images.

They analyze them in real time.

Example:

Instead of showing a satellite photo of a port, they tell you:

• Ships arriving
• Activity changes
• Potential disruptions

Used by:

• Defense agencies
• Governments
• Intelligence teams

Simple way to think:
Google Maps + AI + military intelligence.

Why asymmetric:
Shifts from selling images → selling decisions.
Higher value → higher pricing → higher multiples.

4. $LUNR - The Lunar Layer

Intuitive Machines focuses on one thing:

The Moon.

They already:

• Built lunar landers
• Completed a successful moon mission
• Work with NASA contracts

This is not theory anymore.

It’s execution.

NASA is outsourcing lunar missions to private companies.

LUNR is one of the few that has proven it can deliver.

Simple way to think:
Like FedEx, but for the Moon.

Why asymmetric:
If lunar missions scale, they become default infrastructure.
Early positioning in a market that didn’t exist before.

5. $RDW - The Infrastructure Layer

Market Cap: 1.94B

Redwire builds the physical parts that go into space.

Think:

• Solar panels that power satellites
• Structures that unfold in orbit
• Hardware used in NASA missions

Every satellite needs components before it launches.

Redwire supplies those components.

They’ve worked on:

• ISS systems
• NASA Artemis missions
• Commercial satellites

Simple way to think:
They are like the “Intel Inside” of space hardware.

You don’t see them.

But everything depends on them.

Why asymmetric:
More launches means more components needed.
They benefit from industry growth without picking a winner.

The Peter Lynch Lens

Peter Lynch focused on:

• Simple businesses
• Real demand
• Long-term trends

Each of these companies fits that:

They solve real problems.
They sit inside growing demand.
They are early enough to be mispriced.

Final Thought

$RKLB and $ASTS brought attention to space.

But attention flows to the top first.

Capital flows to the bottlenecks later.

That’s where these 5 companies ($SATL, $RDW, $BKSY, $LUNR, $SPIR) sit.

Disclaimer

© 10x Disruptive Stocks. All rights reserved.

This is for informational purposes only. Not investment advice or a recommendation to buy, sell, or hold any security. You are responsible for your own decisions.

Most investors discover great stocks after the move is over.

They buy when the story is obvious. When the revenue is exploding. When the chart already went vertical.

Small cap photonics stocks are the same story. Quiet today, obvious tomorrow.

But the biggest returns usually come earlier when a small company sits quietly inside a technology bottleneck.

Photonics is becoming one of those bottlenecks.

Silicon photonics, optical networking, and the supply chain quietly powering AI.

And a few micro-cap names are positioned right in the middle of it.

Get my Best Stock Ideas

3 Highest Asymmetric Photonics Plays

$LWLG

Lightwave Logic | Market Cap: 730M | Current price: $5.02

Lightwave Logic is developing electro-optic polymer modulators.

These materials convert electrical signals into optical signals faster and with lower power.

Modulators sit at the heart of optical communication systems.

If LWLG’s polymer technology reaches commercial adoption, it could unlock faster and more efficient photonic devices.

$IQE

IQE Plc | Market Cap: 237M | Current Price: $0.34

IQE produces epitaxial wafers used to manufacture compound semiconductor devices.

These wafers are used in:

• Lasers
• Photonic chips
• Optical communication components

In simple terms, IQE sits at the materials foundation of the photonics stack.

When demand for photonic components rises, demand for these wafers often rises first.

That upstream position makes IQE an interesting asymmetric infrastructure play.

Get my Best Stock Ideas

$POET -

POET Technologies inc | Market cap: 1.14 B | Curent Price: $7.44

POET is developing integrated optical engines designed to simplify how photonic components are assembled inside networking hardware.

Instead of multiple separate parts, the platform integrates key optical functions into a single architecture.

If adopted widely in high-speed networking systems, the impact could be significant.

Small market cap.
Early technology.

High risk but extremely asymmetric upside.

Final Thought

Every technology boom creates a visible layer investors chase. In AI, that layer is GPUs.

But the real leverage often sits deeper in the stack like photonics.

Small companies solving infrastructure bottlenecks can sometimes see the biggest repricing when adoption arrives.

POET.
LWLG.
IQE.

High risk but Huge Upside

But the kind of setup that occasionally produces 10x outcomes when a technology wave accelerates.

Disclosure: For informational purposes only. Not investment advice. It reflects my personal opinions for research and discussion purposes only. I may hold positions mentioned and may change positions at any time without notice. Do your own research.