Part 1 and 2 have already been released:

Part 3 focuses on:

• Uranium

• Brazil

• Application Layer

Uranium

The MMMT Uranium index is currently down 19% over the last year.

That makes it a slightly worse performing basket to hold than the likes of Global X Uranium ETF (URA) which is down 6% over the last year at the time of writing it.

As I try and make clear, the point of these baskets is to find a slightly higher beta way of holding the underlying theme rather than just buying the standard ETFs.

In Part 1 and Part 2, my baskets far outperformed the respective ETF’s so it’s no surprise that we have at least one or two baskets underperforming, especially in sectors that have been struggling over the last year.

Also, it’s worth nothing that my uranium basket is much higher beta than other ETFs because I have included SMR (a small modular reactor play) as a 15% holding.

This is also a play I own in my personal portfolio that I am down on a lot, but currently sized reasonably as to not materially affect the portfolio at all. I still have a lot of conviction in the SMR thesis…the time frame to start producing revenue is likely just a long time away which makes it a far riskier hold during market downturns like today.

Maybe the timing on this thesis has been slightly wrong, but the thesis I believe in.

Uranium Thesis

The supply-demand thesis for uranium is as clear as any commodity thesis I know.

Annual reactor demand globally runs ~200 million pounds of uranium.

Primary mine supply is 130 million pounds.

That’s a structural deficit ~50 million pounds per year that is currently getting filled from finite buffers like secondary supplies, enrichment underfeeding, and inventory drawdowns.

But here’s where it gets more clear cut:

Only ~65% of the uranium that reactors need annually is currently covered by long-term contracts. Utilities have been deliberately undercontracting for years…running down existing supply rather than committing to new supply at higher prices.

That ultimately worked when inventory was comfortable but it no longer works now with supply at record low and time between signing a contract and receiving delivery at record high of 2-3 years. That means it seems inevitable that there will be a buying wave upcoming and with that the price will move in unison.

The Basket

This basket in particular is quite concentrated amongst higher beta names, hence a reason why it’s underperforming vs the index.

We’ve got:

• Centrus Energy | LEU

• Cameco Corporation | CCJ

• Constellation Energy | CEG

• NuScale Power | SMR

• Denison Mines | DNN

Before we move on, a quick word about TrendSpider - the charting platform I personally use.

If you manage your own portfolio the way I do, here’s how TrendSpider fits into my process:

• Scanners for technical and fundamental setups

• Sidekick AI to dig through market data, filings, news, and the names I own or watch without bouncing between tabs

• Charting and automated technical analysis to track support, breakouts, and moving averages across my portfolio and watchlist

• Real-time options, sector rotation, market breadth, news, and sentiment to understand the wider context behind each position

TrendSpider brings the research, charting, and monitoring parts of my process into one place.

If this seems like a useful tool for automating your workflow, take advantage of this 50% discount offer.

Disclosure: I may receive a commission if you sign up or make a purchase through links in this post.

Brazil

The MMMT Brazil index is currently up 31% over the last year (in line with EWZ).

There a lot of valid lenses to look at the Brazil investment case through (Selic rate, politics, Ibovespa valuation etc) which can all lead to different conclusions on whether Brazil is investable today or not.

I’ll dive into them very briefly. But my main focus is on the fact that Brazil is becoming / has already become one of the most strategically important countries in the world.

The US has a critical mineral national security issue that is much bigger than news and headlines suggest. As we’ve known, China dominates the critical mineral supply chain. That doesn’t sound too damaging right now to most, but when you understand the critical minerals needed for technology for the next 10-20 years it becomes a national security issue:

• Humanoids: Rare earth permanent magnets (neodymium, terbium, dysprosium) power every joint actuator and motor.

• Quantum: High purity germanium and indium for qubit substrates, niobium for dilution refrigerator components.

• AI: Copper and fibre-optic rare earths (erbium and thulium) for data center interconnect, cobalt and lithium for power infrastructure.

The aim is therefore to “nearshore”. I.e. move dependence away from China by building supply chains domestically and building supply chains with allies closer to US borders. Outside of the US, Brazil and Venezuela are the key opportunities.

Venezuela has potential but it’s far less investable because of the infrastructure gap and the governance risk and whether this can be monetized at scale yet is still a big question mark.

Brazil on the other hand has:

1. Proximity

2. Scale

3. Relative political investability (italicised for a reason).

It’s rare earths are second only to China’s in terms of % of global reserves held. It holds the the largest niobium reserves and has huge deposits of lithium, graphite, nickel, copper, and phosphate.

Ultimately, this is all why the Brazilian Mining Institute expects the country to attract ~$21.3 billion in investment through to 2030.

However, there’s an obvious complication or two. But the main one is President Lula and it’s a key reason the Brazil trade isn’t working out just yet.

Lula is a big believer in not allowing foreign powers to exploit its countries mineral resources. The workaround so far has essentially been to bypass the federal government by making agreements with Goias and Minas Gerais (home to large rare earth and lithium deposits) but the federal Industry Minister keeps pushing back on these deals. Repeatedly it’s a one step forward one step backwards situation.

But it’s not all bad news amongst a big, unexploitable opportunity.

• The US Development Finance Corporation has backed Aclara Resources rare earths project in Brazil with a $5 million loan.

• The US Development Finance Corporation has backed Serra Verde with a $565 million grant.

  • After this grant, the US government took a 10% stake in USA Rare Earths (USAR), which is in the basket, which then acquired Serra Verde’s Pela Ema mine in a $2.8 billion deal.

  • It has begun letting its existing offtake contracts with Chinese buyers expire.

  • A 15 year set-price supply agreement has been signed with a consortium of private investors and the US government (mainly terbium and dysprosium).

The next significant catalyst is in October 2026 when Brazil’s elections happen. It’s probably the most important catalyst for this entire Brazil and rare earth trade in 2026.

Currently it’s quite even between Lula and Bolsonaro. For reference, Bolsonaro is positioning himself as the candidate that will turn Brazil into the solution for the West’s US mineral dependency on China and therefore likely open up those forecasted $21.3 billion investment opportunities through to 2030 that I mentioned above.

Risks are clear. Upside seems to me even clearer.

It’s one of the reasons NU is quite a substantial position in my portfolio. I personally think a lot of the bad news has been priced into Brazil (given all the metrics like Ibovespa valuation) so the downside just seems far less than than the potential upside.

Application Layer

The MMMT Application Layer index is currently down 2.5% over the last year.

I wrote about the application layer in a lot more detail here in June.

I’ve always been optimistic about the application layer because history has evidenced it time and time again as the place where capital accrues over the long-term.

Read more

1. All of investable biotech today is no more than $1.5 trillion relative to the semiconductor trade which is above $13.5 trillion. That means that even a small rotation out of the the semiconductor basket and into biotech could be very material. This last weeks price action is potentially early evidence of a slight rotation. Whether that is long term or not is a challenging prediction to make.

2. The potential for new drug discoveries using artificial intelligence is vastly under estimated by the market. Biology is becoming computational and that changes everything.

The wider healthcare industry has fought its way through some storms over the last few years. But we believe the above two catalysts are finally starting to converge at the right time today.

For the last 10+ years or so, healthcare has been innovating. It’s been chugging along with aging demographics, technological advances, and biological sciences advancements.

It may not seem like it in the stock market where everyone’s focus has been on the momentum trades of optics, robotics, and alike (until this week)…but if we zoom out a bit it’s clear the advancements here have been extremely material.

• Cancer mortality rate is now ~145 per 100,000 vs 215 per 100,000 in 1980.

• Reversal of prediabetes is now 51%.

• Cardiovascular plaque reversal is now entirely feasible when once considered a “one-way progression.”

• GLP-1s are increasingly viewed as the first longevity drugs.

AI is now permeating every stage of the healthcare cycle from diagnosis, to personalized care, to actual treatment. The gap between what is “biologically feasible” and what can realistically be done with capital, doctor skillsets, and the labour force is narrowing by the year.

The best part of this is that it’s a virtuous cycle that will keep accelerating.

New treatments unlock more new treatments.

Longer life expectancies lead to finding more diseases.

More diseases leads to more medical devices and more drug discovery.

Enormous value creation is set to take over the healthcare sector and I think we’re in the very early innings.

The AI Angle

Medicine is now moving from broader chemical intervention towards very precise biological programming.

The old drug discovery model was about designing a molecule, running a trial, and hoping it works.

It’s changing to something fundamentally different - closed loop systems where AI designs experiments, robots run them, data feeds back into the model, and the cycle repeats itself at a speed no human can match.

This means the bottleneck is changing from biology itself, to whoever controls the data, the infrastructure, and the discovery engine.

This shift creates three clear parts of the chain that are getting disrupted that make up the premise of this write-up.

All in MMMT’s personal portfolio (sizing differs):

1. Discovery: ABCL

2. Data & Infrastructure Layer: TEM

3. Blend of the Above & Commercialisation: LLY

I’ll be diving into them all below this as very mini deep dives but the wider thematic is the most important part I want to convey in this article and I think I’ve covered it above.

To sum it up quite nicely here I’ll say this:

The healthcare market over the next few years wins by:

1. Capital finally rotating to an undervalued theme and away from anything pure AI infrastructure.

2. Capital continuing to rotate into pure AI but the market starting to realize healthcare (especially ABCL, TEM, and LLY) is an AI trade now.

AbCellera Biologics | ABCL

ABCL operates the abLighter platform - an AI driven system that finds therapeutic candidates in 45 days. It’s attempting to change the industry from essentially a numbers game (screen enough candidates and hope something works) to a precision game.

Here’s the core premise for ABCL: Your immune system already knows how to fight disease.

When it encounters a threat, it produces antibodies. Some of these antibodies lock onto and neutralize the threat and therefore have powerful properties within them that can make powerful drugs.

ABCL’s finds these antibodies rather than building them from scratch in a lab.

Partners (LLY, ABBV, BIIB, NVS etc) bring the end target - the protein involved in a disease that they want to treat. ABCL then runs the discovery using AbLighter. From there, if successful, the partner takes it through trials and ABCL earns as those trials progress.

That’s business model #1.

Business model #2 is the more exciting model with more upside (though riskier). It’s the proprietary pipeline and it’s where ABCL owns the asset itself and the economics flow entirely back to ABCL rather than through royalty payments.

ABCL635 is targeting NK3 for menopausal symptoms. It has Phase 1/2 topline data expected in Q3 which, if positive, will reframe the entire narrative on ABCL to a TechBio firm with its own drug pipeline.

The downside risk with ABCL is more cushioned that perhaps it may feel for a small-cap biotech company. It’s currently sitting at $1.8 billion MC with $504 million in cash and committed government funding. So that’s ~30% of the entire MC sitting in cash with over three years runway at the current burn rate with a management team that has delivered so far on all timelines they have publicly projected.

Poor data on Phase II would most definitely threaten the stock in the near term, but the company would not be threatened too materially in the short term. The royalty stream from the 40+ partners continues and as long as these programs keep advancing, the $1.8B MC seems closer to a floor. It feels like a free call option on ABCL365 to an extent.

Tempus AI | TEM

In a sentence, TEM is the data infrastructure that makes AI driven drug development possible.

The whole premise of AI in drug discovery is pretty straightforward: train a model on enough high-quality data and it can identify patterns that would take humans decades to find, right?

The main issue is that the data required to do this well (real patient records, treatment histories, pathology slides etc) is very difficult to assemble and very expensive to get a hold off.

TEM has this data because they invested huge amounts in their foundational years before anyone knew how valuable it would be.

And this data essentially is changing what is possible for pharma. TEM uses this data to actively tell drug companies things they couldn’t otherwise know before committing hundreds of millions of dollars to a trial. CEO, Lefkofsky, explained this pretty neatly:

He said that a pharma company came forward with 25-30 clinical trials to work through TEM’s network. TEM only took 13 of them because they estimated the other 17 would likely fail before generating any meaningful results.

It’s ultimately all about the data they own.

Here’s how the flywheel actually works in practice for TEM (I’ll make this section fairly concise compared to the complexity of it…feel free to skim over it. I’ll go into a bit more detail on the valuation section).

TEM’s different business segments are ultimately built on the data foundation. They have access to the data and the clinical context behind all of that data.

1. TEM sequences patients. I.e. they run genetic tests on cancer patients, reading the DNA, RNA of their tumours.

2. TEM pulls in connected clinical data. I.e. TEM pulls in patients medical history (treatment records, doctors notes, lab results, scans etc).

3. TEM generates molecular and diagnostic insights. I.e. TEM combines the genetic results with clinical history to produce data with background evidence.

4. TEM pushes those insights back to physicians. I.e. The treating doctor gets a smarter report, not just a list of mutations…actual guidance.

5. TEM gets more data. I.e. Every new test adds another patients genetic and clinical data to the database.

6. TEM’s models improve. I.e. More data makes the AI predictions more accurate.

7. Pharma pays to access the data. I.e. Drug companies then pay TEM to interrogate this dataset to understand why drugs work in some patients and not in other patients.

8. This revenue funds more patient sequencing. I.e. The pharma licensing money subsidises the cost of running more genetic tests.

9. Repeat endlessly.

This is the foundation that Tempus is built on. They’ve now done this so much to the extent they have 500 petabytes of data across 45 million patients.

Take a second to truly appreciate this foundation. I know the path from here isn’t straightforward but just understand how far ahead they are from any companies now that are trying to replicate this business model.

It’s years/decades.

Data will be the moat for years to come. The companies that invested heavily at the right time (i.e. 10 years ago) will be the ones that truly reap the rewards over the next 10 years.

Valuation:

Of course it all comes back to valuation at the end of the day.

Aim #1 is always to own a quality business. Aim #2 is about owning a quality business at the right price.

If one of those isn’t investment worthy, there is no trade.

Here’s why I think TEM is so undervalued:

At ~6.5x sales, the market still prices TEM like a diagnostics lab for the most part… i.e. Guardant Health (GH) trades at 15.9x NTM sales today.

The way to think about TEM’s valuation is to split it out into two separate businesses.

Diagnostics: I think $2.4 billion in revenue by 2028 for diagnostics is feasible if volume continues to steadily compound and ASP moves closer to $2,000. That assumes ~26% CAGR from 2025.

At a 22% operating margin (already operating at 65% gross margins), that’s ~$530 billion in operating profit which means operating profit for that business would be growing at ~25% CAGR. Put it at 1x PEG (25x multiple) and we have a $13.25 billion business there.

Data & Applications: This is where it gets slightly more interesting for me here. My estimates put us at $820 million in FY28 revenue. This is a SaaS like business so +30% margins are very likely (and perhaps still conservative).

As a SaaS like business with +30% margins, I think a 30x NTM PE isn’t overly bullish at all. 30x PE on that gets us a $7.4 billion business which I think is an absolute base case.

Combined that’s an EV of +$20 billion vs $10.3 billion today.

Eli Lilly | LLY

LLY was once (and still is) a GLP-1 story.

Read more

Part 1 was released on Sunday:

Part 2 focuses on:

• Robotics

• Optics

• Solar

Three themes that have been hit hard by the recent market sell off.

Robotics

I think many people appreciate that robotics is a huge megatrend coming up.

But few people realize how much of a national security issue for the US right now it is…which is central to the investment thesis today.

China is currently way ahead of the US. Their 2026 humanoid output is +100,000 vs the US which is ~14,000.

That issue stems because of a few different reasons, but ultimately gaps this visible do attract policy, urgency, and capital into the theme.

The most obvious issue today is the rare earth supply chain. The US isn’t doing anywhere near enough to prioritize this issue right now but that can’t remain which is why USAR to me is a clear thematic opportunity.

But zooming out, the robotics megatrend is so vast.

I wrote about it in depth in the article attached above but a simple summary would go along these lines:

• Backbone

  • Actuation/Bearings: Without actuators robots are just an intelligent statue. There’s only a few key players here.

  • Sensory & Perception: LiDAR, IMU, tactile and force sensing, analog and semiconductor sensor components. There’s many angles to play this.

  • Software/AI Integration: This is where the US leads now. The AI foundations are strong but the physical components that make up the robots is where the US is behind quite significantly.

  • Motion Control: The sophisticated chips that orchestrates a robots every move calculating how much each joint must rotate and at what speed.

  • Communication: The invisible layer that keeps everything connected.

• Frontier:

  • Medical Robotics: More than just a few niche surgical aids now. It’s set to transform healthcare from surgical systems to diagnostics, to rehabilitation exoskeletons, to pharmacy automation and logistics bots.

  • Defense Robotics: Low cost robotic systems are now destroying high value manned assets forcing this shift towards unmanned drones.

  • Logistics Robotics: This will likely be the first large industry to be fully automated. AMZN alone already has over 1 million humanoids deployed.

  • Humanoids: Once quite an un-investable segment of robotics until CCXI went public.

  • Professional Robotics: The smaller, specialized, task-specific machines optimized for professional applications.

The current basket includes 13 names with 40% of the basket allocated purely to OUST and NVDA.

OUST is in my personal core portfolio as my 2nd largest position so I’m very bullish there.

You can see my prediction with OUST here:

The rest of the basket is made up of some frontier and some backbone plays like OII, DGII, AIT, MBLY, PRCT and FLS.

I’ve weighted all those plays quite small but the two that have my most attention at the moment to increase weighting for are:

1. PROCEPT BioRobotics | PRCT: PRCT is a surgical robotics company with one product that treats enlarged prostates. The numbers are very interesting on this one if they execute and if they can scale. Most MedTechs like this really struggle for the initial years because operating and gross margins are so thin. It’s only when scale hits that numbers start to look quite interesting. PRCT appears to be at that inflection point now.

   1. PRCT trades at 2.3x NTM sales whilst set to grow revenue at 29% in FY26 and 24% in FY27.

   2. If PRCT reach EBITDA profitability next year (which is expected), then we should expect ~$170M in EBITDA in FY29 based on $680M in revenue and a 24% EBITDA margin.

   3. At $170M in EBITDA and a 20x EBITDA multiple (TMDX today trades very cheaply at 14x), we could expect an EV ~$3.4B which is 3x from today.

2. MobilEye Global | MBLY: MBLY is building the perception and decision making systems for autonomous vehicles and humanoid robots. It funds its frontier R&D through a highly profitable ADAS chip business. It recently acquired Mentee which is targeting commercialisation in 2027.

   1. Revenue growth has been slow in FY23, FY24, FY25 and likely FY26. But FY27 is when the company is likely to ramp up again to +22% estimated growth which would mean a 3.3x sales multiple would be cheap.

   2. If MBLY meets estimates of $3.8B in revenues in FY29, then they’d be growing revenues at 25% CAGR.

   3. Compare that to a partial competitor like NXPI which is growing ~7.9% CAGR for 5.2x sales, and we start to see the re-rating potential for MBLY down the road.

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Get 38% off + $98 in free upgrades if you sign up by July 8th at midnight — once it’s gone, it’s gone.

TrendSpider is the charting platform I personally use, which has helped me spot the most in my investing.

If you manage your own portfolio the way I do, here’s what TrendSpider provides:

- Scanners that surface technical and fundamental setups before they’re obvious - the kind of early entries that turned OUST and NBIS into two of my biggest winners this year.

- Sidekick AI to dig into market data and portfolio holdings without jumping between five different tabs.

- Charting and automated technical analysis to track support levels, breakouts, and moving averages on every name you hold or are watching.

- Real-time options, sector rotation, market breadth, news, and sentiment to understand the broader market context behind any single trade.

This is one of TrendSpider’s biggest sales of the year. If you’ve been thinking about trying it, this is a good opportunity to sign up with a discount.

Optics

Copper can’t handle AI-scale bandwidth at 800G and 1.6T speeds which is why photonics is the solution.

The optics theme was obviously one of the biggest winners in the entire market over the last year with the MMMT index of just 5 stocks now returning 303.1% vs the SPY at 20.2%.

This recent pullback with the likes of AAOI down ~42% in the last month is nothing more than a correction in what I deem to be a long term buildout.

The major inflection point we’ll likely see as per most earnings calls is mid 2027 as 1.6T scales and as CPO broadens past NVDA and AVGO.

Markets will likely price this ramp up before it actually arrives, which is what has happened to an extent so far, but looking at individual valuations I am of the opinion we are far from being priced in.

Here’s my optics piece from December 2025…nicely before all optics plays surged in January and February.

My core photonics play is AAOI. It’s a stock I am down ~21% on in my core portfolio, but it’s one of my highest conviction plays right now that I’ll personally keep building out sub $130.

A few reasons for this:

1. If AAOI hits projections, it’s ~12x in revenue growth from $455M in 2025 to $5.6B in 2028 (that’s being conservative on management assumptions because of the timeline). There’s no other company in the market forecast to grow that quickly especially at 6.5x NTM sales today.

2. All hyperscaler customers want to buy all transceivers AAOI can possibly supply. It’s a supply constraint and not a demand constraint.

3. If you have partial trust in management, then looking at current financials for AAOI actually makes no sense. This is a 2027/2028 ramp up story likely like no other in the market. We saw it with NBIS earlier in the year and I personally believe AAOI is in the same boat, if not even more bullish than NBIS was before the recent run from $92 to $300.

Solar

Solar is an interesting, and very underappreciated trend. The MMMT Solar index is up 69.9% in the last year vs SPY at 20.2% but it’s been a very volatile ride.

Read more

Part 1 is looking at the following baskets:

• Critical Minerals

• Grid Infrastructure

• Miners

Here’s a snippet from my web-app:

Critical Minerals

YTD the MMMT Critical Minerals Index has returned 54.6% vs SPY at 9.0%.

It’s been a volatile basket to hold with stocks like MP surging to $100 last summer before falling back to the mid $50s today. USAR has been another volatile play (which we hold in the core portfolio) jumping from $14 to $44 and back to $19 in the space of 8 months.

We’re now ~12 months on from China’s restrictions on rare-earths and permanent magnets which sent the likes of USAR and MP soaring. However, the market so far in 2026 has seemingly forgotten about the technological revolutions ahead in AI, physical AI, and even quantum and the rare earth requirements for this.

Valuing these plays at the moment is a challenge. It’s likely why USAR and MP and LYC have struggled recently.

But despite what the stocks are doing the underlying thesis remains clear:

Brazil remains the big opportunity which is one of the main reasons I am building my USAR position. It’s by far the most “nearshore” ally to the US and depending on the presidency ballot in October this year, the outlook for Brazil as an ally could be extremely advantageous.

Flavio Bolsonaro has already attempted to position Brazil as this ally to the US and the US’s solution for mineral dependency.

This is one reason why I hold USAR in my core portfolio.

USAR acquired Serra Verde which owns the Pela Ema mine. Pela Ema is the first large scale producer or rare earths outside China. It’s also signed a 15 year supply agreement with the US government making it quite a clear bet on this rare earth thesis.

I also have Sunrise Energy Metals (SREMF) in the critical minerals basket. It currently trades at $12.49. Here’s what I sent to paid subscribers back in March when SREMF traded at $5.50.

TLDR Summary for critical minerals:

Markets are not pricing in the physical bottlenecks of the AI buildout. Huge amounts of copper, gallium, silver, gold, platinum, scandium, and niobium are needed for the continued data centre buildout, and the physical AI world we are entering into.

It appears today that the US is technologically superior to China in models but China owns over 70% of the worlds critical minerals supply chain. That’s not a strong position for the US to be in.

Last chance to grab TrendSpider at a steep discount.

Get 38% off + $98 in free upgrades if you sign up by July 8th at midnight — once it’s gone, it’s gone.

TrendSpider is the charting platform I personally use, which has helped me spot the most in my investing.

If you manage your own portfolio the way I do, here’s what TrendSpider provides:

- Scanners that surface technical and fundamental setups before they’re obvious - the kind of early entries that turned OUST and NBIS into two of my biggest winners this year.

- Sidekick AI to dig into market data and portfolio holdings without jumping between five different tabs.

- Charting and automated technical analysis to track support levels, breakouts, and moving averages on every name you hold or are watching.

- Real-time options, sector rotation, market breadth, news, and sentiment to understand the broader market context behind any single trade.

This is one of TrendSpider’s biggest sales of the year. If you’ve been thinking about trying it, this is a good opportunity to sign up with a discount.

Grid Infrastructure

Grid resilience is one of the most underappreciated levers for technological dominance over the next decade.

Forget just AI - think technology in general (robotics, quantum, everything). The most developed economies today are massively constrained by a very outdated grid that is in need of a complete rebuild.

So much so, that the White House invoked the Defense Production Act (Section 303) in April 2026 which specifically focuses on transformers, substations, high voltage breakers. It’s evidence that the domestic capacity is now not sufficient to meet the baseline demands moving forward.

IEA (International Energy Agency) projects are spending ~$550 billion in 2026 alone (that’s a 20% increase YoY).

Total (add in all end-use electrification like EVs, electrified industrial processes etc) electricity investment is now nearing $2 trillion per year.

Now let’s get into the specifics of what this means from an investment angle.

The wider theme is obvious, but how quickly this is actually achievable is a completely different story.

With how fast technology is moving, and how large the demands are for electricity, the grid buildout appears structurally far too slow to keep pace with the demand. In the US alone, data center buildout is projected to go from 21GW in 2026 to 84GW annually by 2030.

Given that grid interconnect is the constraint here, perhaps the bigger opportunity therefore lies in the companies enabling buyers to generate or access power on their own timeline, and not to do with the companies selling generation to the utilities.

Capacity simply isn’t growing fast enough to cover the 21GW to 84GW of US data center demand so there needs to be an alternative.

The biggest winners will be those that allows a buyer to generate power without relying on the utility. The answer today is Behind-The-Meter fuel cells…i.e. Bloom Energy (BE) or gas engine names like Innio (INIO).

The other angle is SMRs but the target for them is likely a 2028-2030 story…perhaps even later. I put SMRs in the Uranium basket and also as a long duration hedge on the grid problem. I haven’t included it in the power grid upgrade basket yet.

Miners

As you’ll know, I’m fairly aggressively building my positions in silver, copper, and scandium miners and I continue to believe this is:

1. One of the most important divergences in the market today.

2. One of the safer ways to expose yourself to the technological revolution without investing in the tech directly.

Read more

I wanted to do a H1 recap, and a look through to H2. It’ll be a short punchy article with the following contents:

Contents

1. What my service is going to look like in H2 26.

2. H1 Results

   1. Overall Performance

   2. Biggest Winners & Biggest Losers

   3. Portfolio at H1 Close

3. What I am thinking into H2 and where I see my portfolio ending the year.

4. Opportunities I see at the moment not in the current portfolio.

What my service is looking like for H2 2026

Just a quick note here:

I want to share a few plans I have for the rest of the year.

I’ve been working very hard on a web-app as you all know so far. You can see the link to the app here.

This is only a beta version that is going through rigorous testing and upgrades. Here’s a couple of the upgrades I’m working hard on right now:

• Guided Valuation Model (EV/Sales, EV/EBITDA, P/E, or MMMT Valuation Model) for every stock in my universe - see screenshot above.

  • This allows you to input your assumptions (or follow my assumptions) and come out with a target price.

• Stock Baskets: As well as showing my personal portfolio as evidence of my track record, I’ll be showing you concentrated stock baskets of the best themes in the markets.

  • These aren’t ETFs. These are 5-10 stock baskets for all themes in the market with individual stocks and weightings.

  • I think of it as a way of introducing you to other high conviction plays I have that I don’t necessarily personally own due to capital. I also think it’s a great way to increase your exposure to a theme that you may like more than I do.

• This is all on top of daily notes, live portfolio, technical screens, and research notes.

Subscribe now

H1 Results

H1 results were really good at 25.4% YTD.

Considering we were down YTD in the March dip, we’ve come back nicely with some quite material wins to bring me up to 25.4% YTD so far meaning if these kinds of returns continue I’ll come out somewhere near my 2024 and 2025 returns of 47% and 48% respectively.

I will be adding a live tracker of my YTD on the next version of my beta web-app release. I’m fully aware it’s not there yet but the calculation to track it live isn’t that easy with the way I invest.

Biggest Winners & Biggest Losers

My biggest winners have been:

1. Ouster | OUST: We’re now +115% at the time of writing this with a $23 average price and a first buy in January ~$24. Early to the game on this one.

2. Nebius | NBIS: Still up +135% even despite this weeks dip post META announcement.

3. Solaris Energy Infrastructure | SEI: Currently +80% on SEI with an average cost of $37.

4. Credo Technology | CRDO: Frustratingly my average cost on CRDO wasn’t as good as it could’ve been, but I still am up 71% in a few months on this.

5. AbCellera Biologics | ABCL: This has been a long term position for me over the last year that has been range bound until the recent biotech breakout. I’m now up 76% on the position.

Those winners are all unrealized / i.e. stocks I still hold.

Some of my realized gains are here (see screenshot):

You’ll note there’s some losers in there which I’ll touch on in the section below, but notice how the winners far outweigh the losers in terms of size (and win rate):

• Ondas Holdings | ONDS: A very quick move for a swing trade that nearly got 200%. I sold in the end for 171%.

• Albermarle | ALB: ALB turned out to be a great trade for me. I managed to get 119% on the investment and perhaps sold too late as it broke the $150 support level. I was up nearly 200% on ALB at one point. A clear thematic trade.

• Silvercorp Metals | SVM: This was my original higher risk play on the silver market with an average cost ~$3.50 and nearly a 3x move.

• AXT Industries | AXTI: I rode the initial hype around this name but only for a 42% gain. In hindsight, one I regret selling so early.

• SES AI | SES: You’ll see more on this below.

• Redwire | RDW: RDW is also there but didn’t fit into the screenshot. That was a 112% winner though.

• Sanmina | SANM: I bought SANM at $125 when it traded at ~0.5x sales and 7x EBITDA which for one of the few PCB players in the market seemed too cheap.

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My biggest losers have been:

I’m only going to include stocks here with a weighting above 1% in my portfolio.

• Upstart | UPST: UPST has been a poor investment for me, but I still see the opportunity in the lending market for disruption. If I’m right about capital rotation into the AI appliers, I do believe UPST will re-rate above a 14x NTM EBITDA.

• Transmedics | TMDX: TMDX has always been a volatile stock but the underlying company is still performing well. Management continue to reiterate their longer term targets of 20k transplants by 2030. If that is the case, I don’t see how TMDX can continue to trade at 3.5x NTM sales or 13x NTM EBITDA based on those growth assumptions. It’s one of the stocks I continue to DCA into.

• USA Rare Earths | USAR: This is my higher risk bet on the rare earth supply chain that will challenge US for the next few years. It’s currently a small position that I am holding happily as long as this $19 support level is held. If that support level is broken and we fall below the 200D MA, I’ll rethink the thesis.

• UiPath | PATH: If there’s one thing to say about PATH, it’s that this $10 level has held extremely well for the time being and the last week has looked strong. I am currently down 20% on PATH with a 2.05% position.

Here’s my portfolio at H1 close:

I can’t screenshot the entire portfolio as it won’t fit…but I will screenshot as much as I can of the top half of the portfolio.

You’ll see my 7 largest positions there making up 52.6% of my portfolio as of today.

NU and DLO are both up less than 20%, OUST and NBIS are up more than 100%, and AMZN and ZETA are up more than 20%.

Here’s the rest of the portfolio:

Read more

I’ve tracked quantum for ~4 years now. I wrote my quantum ecosystem deep dive here where I first introduced LAES.

I’ve been very back and forth on the topic over that time jumping from it being a distant reality to what I now deem it to be on the verge of potential, and material, breakthroughs.

Over the last few months, we’ve seen more and more news come out on quantum and all of that news has labelled quantum to me as now being a serious technology that is being battled out between US and China.

Governments are now doubling down their quantum investments by committing huge sums of money into labs and foundries. 2026 alone has seen:

1. May 21 Commerce CHIPS package

2. China’s accelerated funding

3. France’s accelerated funding

4. Trump’s June 22nd Executive Orders

5. Migration to post-quantum cryptography

If we take a step back, I think it’s important to understand the following:

Peter Lynch: “In stocks, the upside is always greater than the downside. A stock can only go down 100% but it can go up 1000%.”

I don’t always have this exact mindset with stocks. But it’s the mindset I have taken with LAES.

Big picture here’s where quantum is right now:

1. McKinsey is estimating quantum could create between $1.3 to $2.7 trillion in economic value over the next 10 years.

2. Quantum is rapidly becoming a national security priority. We’ve seen $2 billion investments into quantum companies in 2026 across a range of different quantum architectures.

3. Now China and US are arguably on a level playing field technologically now…the next big win could come from quantum?

   1. China are currently investing ~$17 billion into quantum (more than the US) and so far it’s paying off. They’ve announced the Hanyuan-2 (world's first dual-core quantum computer) and Jiuzhang 4.0 (most powerful photonic quantum computer) in 2026.

4. Investment in Europe is also growing with France committing $1 billion in 2026 alone, the UK investing $500 million through to 2030, and Germany investing ~$3.5 billion through to 2032.

5. The economic value created by quantum will be seen most across chemistry, materials science, and drug discovery. I wrote about the drug discovery angle in my recent article.

In short, it’s one of those very early stage technologies, but out of everything, I think the upside is the most substantial relative to today’s levels (maybe biotech is the other sector with similar upside).

A huge number of challenges remain though. The technology is extremely complex, investment is still very early, supply chains are already struggling, and there’s a clear shortage of critical materials.

But if you’re a high growth investor looking for a higher risk bet, then the quantum market should be on your radar.

Company Name: SealSq

Ticker: LAES

Market Cap: $692M

Headquarters: Geneva, Switzerland

CEO: Carlos Moreira

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LAES Introduction

LAES spun out from WISeKey (WKEY) which is a Swiss cybersecurity firm. Today, it’s doing something that very very companies in the world can do:

It has built a chip with post-quantum encryption and it’s further along the path to getting certified than any of its competitors have publicly disclosed.

The timing of what LAES is building is key to everything. On June 22nd 2026, Trump signed two executive orders (EOs) mandating that all federal civilian agencies and their contractors migrate post-quantum cryptography by 2030. The previous deadline was 2035 so the whole narrative around post-quantum cryptography changed in an instance and stocks like LAES became far more important overnight.

Post Quantum Cryptography Market

What does “Q-Day” even mean?

Nearly all encryption securing everything on the internet relies on maths. It relies on a math problem that is ultimately too hard to solve in a reasonable timeframe.

Quantum computers break this bet entirely because they can use Shor’s algorithm to solve these math problems in enough time. That makes the encryption secure against classical computers but not secure against a quantum computer running Shor’s algorithm.

“Q-Day” is the term for the date at which a quantum computer that is powerful enough to execute Shor’s algorithm in sufficient time.

Previously this date was ~15+ years away, but today post Google’s March 2026 whitepaper signalling Shor’s algorithm can run with fewer than 10,000 qubits, we’re far close than 15 years.

It’s looking more likely to be the end of this decade.

The main issue however is that full PQC migration (enterprises’s timelines from nothing to protecting themselves against this quantum) is ~12 years. So if “Q-Day” arrives in the next 3-7 years, organizations that haven’t started yet are structurally very late.

This means the threat timeline is now regulatory driven and deadline driven rather than technologically driven. Customers will begin buying PQC hardware not because quantum computers exist today but because:

1. Governments will mandate this.

2. The migration process may take years regardless.

3. Harvest-now-decrypt-later ultimately means waiting is not safe even if “Q-Day” is 10+ years away anyway.

Market Size

This is a difficult one to gauge because research varies and there’s a lot of companies operating in sub-niches different to what LAES does.

Here’s my best estimate:

The embedded security chip market: This is where LAES’s legacy products ultimately operate and this market is forecast to be ~$10 billion by 2028.

The PQC hardware market: This includes secure semiconductors, TPMs, and HSMs (Hardware Security Module) implementing PQC algorithms in certified hardware. There is the most variety in this estimate because the market is very nascent and because its currently gated by certifications.

Estimates put this market ~$2.5 billion (but ranges up to $20 billion).

Take this with a pinch of salt because customers (governments, defense, financial services etc) legally cannot deploy uncertified PQC hardware in production systems yet so gauging the market size is almost an impossible job today.

The market will not grow linearly at all. And this is another reason why LAES is a riskier investment today. But as regulatory deadlines approach and certified products become available, expect this $2.5 billion figure to jump considerably.

The Certification Issue

As I just touched on, regulated sector customers cannot legally deploy PQC hardware in production systems until that hardware holds specific certifications, regardless of how technically capable the product is today.

There are two key certifications:

1. FIPS 140-3: This validates that a cryptographic module meets specific security requirements. LAES is currently pursuing Level 3 (out of 4). Just like getting FDA approval, this process costs millions and takes between 12-24 months from submission.

2. EAL5+: Level 5+ is an international security standard requirement for hardware targeting defense, intelligence, and critical infrastructure applications. It is one of the most demanding certification processes in existence, typically taking 2-4 years and costing ~$5 million pre product. LAES currently has four variants in the pipeline that each require their own independent evaluation. LAES has already passed two of the most demanding parts of the process (fault injection and side-channel attack testing).

I’ll dive into this more later, but this matters a lot. It’s evidence that the path from "$200M pipeline”, or “interested customer”, or “115 customers actively testing” to customers actually paying in volume is extremely challenging.

This is the main point I want to get across in this LAES deep dive.

The upside is high. The downside is also very clear and right now it’s definitely considered a bet on things going right.

The other important note is that LAES currently has a certification target of Q4 2026. If they miss this target because of delayed or failed certification, then the risks of missing CNSA 2.0 January 2027 new-acquisition deadline become a real risk.

Recent News:

On March 30th, Google Quantum AI released a document co-authored with Stanford and the Ethereum Foundation establishing that breaking cryptography (the security behind Bitcoin and Ethereum) requires fewer than 500,000 physical qubits.

That’s a 20x reduction from prior estimates.

And the CEO of LAES, Carlos Moreira referenced this in their earnings call:

“Remember last year, in January last year, we were still thinking that quantum computers will be only able to break RSA triple desk. In 30 years’ time, this was reduced to 10. And now Google announced yesterday they are actually dividing that by 10.”

“Now quantum companies are also expanding faster than their qubits generation. The company we have invested and the ones that we are in the process of investing in, they are already able to generate between 10 and 100 qubits. And some of them, they are predicting to be able to reach the 500 qubits, which is what Google says that will actually be enough to break cryptocurrencies.”

The implication is that the algorithmic side of the threat is compressing fast. Faster than the hardware side of quantum anyway.

And then on June 22, 2026, Trump signed:

• EO 14411: An effort to produce a scientifically relevant quantum computer within five years, quantum sensors, and networks.

• EO 14409: The PQC mandate. Four binding deadlines:

  • NIST pilot project complete by December 31, 2027.

  • Federal civilian agencies transition high-value assets for key establishment to PQC by December 31, 2030.

  • Federal contractors under covered procurement rules meet the same standards by the end of 2030.

  • Digital signature systems migrate to PQC by December 31, 2031.

Here’s what it actually means:

I think this news gives us a few ideas:

1. The timelines are still quite a way down the road so expecting these stocks to move considerably in the short term is arguably naive…but it’s a great time now to learn and start to slowly build positions. NIST pilot project by 2027 creates a near-term procurement and testing cycle meaning vendors who can demonstrate compliant products by then will have a structural advantage.

2. The orders do not name, reference, or contract with LAES in any way. There is no plans to support specific quantum companies over the likes of IBM, GlobalFoundries, or KeysSight for example. That’s something to be aware of and to be careful about.

3. Despite point 2 above, direct funding recipients are not LAES competitors in the PQC hardware market. IBM and GFS are quantum computing hardware builders, but not PQC hardware builders. That’s an important distinction and not a bear case for LAES.

4. Despite point 3 above, there is still a lot of competition in the PQC market. American Binary is a pure-play PCQ software company with partnerships with players like Oracle. It’s operating in the exact regulatory environment LAES is targeting but just on the software side. Although they compete in slightly different areas of the market, it’s an illustration that there are a lot of well-credentialed players in the PCQ market.

5. The “Made in USA” angle got more valuable. These executive orders prioritize domestic supply chains so LAES’s plan to operate mainly on US soil aligns. Those companies that can credibly say “designed, personalized, and certified in the United States” will likely be very big beneficiaries as we head towards the 2030 deadline.

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Product Portfolio

LAES’s products sit across two categories:

1. Secure elements

2. Trusted platform modules

QS7001 - The Secure Element

This is LAES’s flagship post-quantum secure element.

A secure element is a tamper-resistant chip that sits inside a device (a smart meter, an IoT sensor, a medical device, an EV charging station).

It handles all cryptographic operations such as storing keys, authenticating the device, encrypting communications. The simplest way to explain it like a locked vault inside a device.

The differentiation for QS7001 is that it implements ML-KEM and ML-DSA - these are two NIST-standardised post-quantum encryption algorithms. This isn’t a software add-on. It’s directly into the silicon.

QVault TPM

This is a different product for a different type of customer.

A TPM is a security chip that sits inside a computer and acts as the hardware identity card. Every time the device boots up, the TPM checks that nothing has been tampered with, stores the encryption keys that protects the devices data, and provides a verifiable proof to any network it connects to that the device is what it claims to be.

The simplest way I think about it:

QS7001 goes inside devices. TPM’s go inside computers. This means the QS7001 is designed for manufacturers building smart meters, drones, medical devices, sensors etc… products that need a secure identity chip embedded inside them.

The TPM is designed for the computing infrastructure that runs the world - servers in data centres, PCs etc.

The addressable market is therefore slightly different but the underlying mission is the same: post-quantum security baked directly into the hardware.

PKI & Trust Services

PKI and Trust services currently represents just 2% of LAES’s total revenue - approximately $0.4 million in FY25. Most people skip past that but there’s big potential here.

Here’s what PKI actually is and how it connects to everything LAES is building.

Every chip LAES sells needs a digital certificate. That certificate doesn’t just get issued and then forgotten. It needs to be renewed, managed, and verified throughout the chips life span.

It is unlikely to be the main revenue driver for LAES, but even a $0.10 per chip at a scale of 100 million chips per year (the Kaynes JV in India is targeting 300 million chips at scale) is ~$10 million per year in potential revenue. If you look at my model below, you’ll see the potential of this segment.

Competition

This is arguably the most important part of this article I think because it sets the picture for the small cap, high growth stock vs the established well-resourced semiconductor companies.

I’ll break it down via tiers:

Large Cap Players

Infineon (IFNNY): This is the most direct competitor to LAES core TPM market. IFNNY’s TPM is already designed into hundreds of millions of devices across PCs, servers, industrial systems, and network infrastructure - and it’s next gen chip will include post quantum encryption as an upgrade path for existing customers.

That’s the key danger for LAES. IFNNY customers won’t need to switch vendors or go through a new design process, or change their hardware supplier to access post-quantum security. That’s a huge competitive advantage.

But IFNNY currently has no post-quantum chip that is actually available so they’re far behind LAES in that regard. We have no public knowledge of timeline or launch data.

NXP Semiconductors (NXPI): NXPI product is EdgeLock which will compete with LAES’s QS7001 but just like IFNNY the timeline is behind LAES with no publicly disclosed timeline.

It’s a very similar story to IFNNY in that NXPI has an enormous customer base with existing relationships meaning its post-quantum version is just an evolution of a product rather than an entirely new product.

Microchip Technology (MCHP): MCHP announced its entry into post-quantum hardware security on April 28th 2026 with a direct competitor product to LAES’s TPM. It’s probably the furthest ahead but again has no publicly disclosed certification timeline at all so gauging that is much harder to tell.

Ultimately, every company here is trying to build a chip with post-quantum encryption standards baked in and get it certified by federal regulators.

Right now, no company has achieved this.

To put it as simply as I can - LAES appears the furthest ahead at the moment in terms of product and certification (at least from what has been publicly disclosed) so they have a first mover advantage. But MCHP, IFNNY, and NXPI all have the capital and manpower to get jobs far quicker.

They also have the existing customer relationships so first mover advantage actually means a lot less for them.

An interesting battle of the safer compounders vs the small cap that needs to meet the strict deadlines to stand any chance in the market.

Smaller Cap Players

BTQ Technologies (BTQ): BTQ is the most direct pre-revenue hardware competitor to LAES in the small cap space. From my understanding, certifications are ~12-18 months behind where LAES is today in terms of actually delivering chips to customers.

This makes the timeline risk of meeting certification deadlines far trickier for BTQ.

Valuation

Given everything I’ve told you above, valuing a company like this is extremely challenging.

It’s similar to valuing an early stage biotech seeking FDA approval.

But I think the best thing I can do here is model out a bull, base, and bear case over the next 6-8 years.

You can see my valuation models here below. It’s a Google Doc that I am giving viewing access to with 3 different tabs… bull case, base case, and bear case.

Read more

Growth is still very strong, forecasts are still very strong, the economy is in good stead.

But the market front-runs what is actually happening, and I suspect that by 2027/2028 the rate of growth in the hardware buildout will start to cool. When that happens, the risk/reward profiles across some segments of this AI trade will look a lot less attractive than they do today.

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Let me be clear before I go further: this is not a bearish take.

I’m probably one of the more optimistic bulls out there. I think capital will continue flowing into this once-in-a-lifetime technological revolution for years to come.

But at some point we have to start asking which niches of that revolution will outperform from here?

The first thing to understand is that the growth slowdown and the valuation re-rating are not on the same clock.

The hardware buildout has years left in it. Nvidia’s Vera Rubin platform only began shipping in volume this quarter, with Rubin Ultra’s 600-kilowatt racks not arriving until 2027.

In absolute terms, that part of the story is still early.

But the price you pay for exposure to it is a different question entirely. Big Tech CapEx is tracking toward roughly $725 billion this year, capital spending as a share of revenue has climbed past 23%… more than double what it was pre-ChatGPT. And credit spreads tied to the buildout are already widening as bondholders start asking who is actually paying for all of this.

The second thing to understand is that the infrastructure trade has matured from a basket into a stockpicker’s market. For two years, owning the buildout meant owning everything attached to it (chips, power, data centre landlords) and watching them move together. That is largely over.

The bottleneck has migrated from raw compute toward cooling, power, optics and memory, and each time the bottleneck moves it the baton to a different set of winners. Of those, I remain most bullish on optics and memory.

But the broader point is this: the names that carried the basket higher are not necessarily the names that carry it next.

Which brings me to the bigger question.

If these models are this good (and they are) and if agents can now act rather than merely suggest, where does the return on all this CapEx actually show up?

The first phase funded the obvious things: chips, data centres, power. That was the easiest trade to see and the easiest to underwrite.

The next phase is harder to see, which is exactly why it hasn’t been priced yet.

For me, the answer is the application layer - the companies turning extraordinary intelligence into something a customer genuinely needs and depends on, and finds painful to remove.

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The Application Layer

The bull case for the application layer is simple. Once the underlying models are this capable, the constraint stops being “Is this intelligence good enough?” and becomes “Who turns it into something a customer will pay for and depend on?”.

The trigger that turns this from theory into an actual capital flow is enterprise adoption moving from pilot to production.

For the better part of two years, "AI productivity gains" lived all in narrative.

But what's changing now is that that narrative is actually starting to show up in the numbers… in margins, in headcount that stops scaling with revenue.

Agents now can take an open-ended, difficult problem, and work autonomously on their own. Systems now don’t just answer questions but generate hypotheses, run experiments, execute transactions, and do all of this with zero human approval.

The companies that win here the most are within:

1. The largest industries

2. The most inefficiently ran industries

Those are:

1. Insurance

2. Drug design

3. Some areas of finance

4. Materials science

The prize is enormous. But gauging how much some of these sub $10B companies can actually disrupt the market is something I could argue both ways.

However, positioning yourself on the long side of some of these companies I’ll talk about here is right now, in my opinion, probably the best risk to reward set up in the market.

If these companies do end up disrupting these markets…the upside in some cases is enormous.

How to Invest:

Read more

But the more time I’ve spent listening to those who know where quantum truly is gave me a pretty good push to get this article and quantum basket out. Here’s the basket performance (and constituents):

Sundar Pichai for example thinks quantum is where AI was 5 years ago.

Until more recently quantum has been a theoretical promise and nothing more but it’s now slowly entering a period of commercial utility. Most notably in materials science, chemistry, drug discovery, logistics, and in national security too.

A quick intro on quantum computing. I’ll keep this brief because there’s thousands of YouTube videos and articles out there explaining what quantum does and they’ll probably explain it better than I will.

My edge is in painting out the investing roadmap for you:

Quantum Computing

Quantum computers behave very differently to classical computers. Classical computers process information in “bits”. That’s a 1 or a 0. That’s it.

Quantum computers operate using quantum bits (qubits). This allows them to be in multiple states at once which leads to problem solving on a whole different level to classical computers.

My Focus

My focus is more on the technologies and bottlenecks involved in the quantum computing revolution. Just like with the AI revolution, we’ve seen breakthroughs in optics, lasers, 3D packaging etc…we’re going to see that same process play out for quantum. And this means a new wave of industrial development focused on cryogenic control chips, scalable quantum chip fabrication, precision lithography, and the interconnects needed to link it all together.

Looking at the TAM, McKinsey is currently estimating quantum computing could create $1.3 to $2.7 trillion in economic value by 2035. I take these estimates with a pinch of salt because the range of estimates I’m seeing is so broad and the timelines I’m seeing on when quantum becomes economically active is wide too.

But the big picture is there. Quantum has a big future. And it’s one to start learning about.

The US Department of Commerce is telling us exactly this as well. Just last week, nine letters of intent were signed to direct $2.0 billion through the CHIPS and Science Act to quantum companies for non-controlling equity in each company. These equity stakes were split nicely across a range of quantum architectures such as photonic, silicon-spin, trapped-ion, and superconducting.

Whether it’s worthy of an investment today is another question. Most quantum plays aren’t really breaking out technically just yet so dependent on how much those technicals mean to you could depend on when you consider initiating a position.

Here’s how I’d breakdown quantum (without looking at the pure plays like IONQ, RGTI, QUBT, and QBTS):

• Critical Minerals

• Cybersecurity

• Lasers & Photonics

• Superconducting Circuits

• Cryogenic Test Equipment

• Quantum Hardware

• Quantum Chip Fabrication

• Quantum Applications

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Critical Minerals: The Foundation

It depends on the quantum architecture used, but a range of critical minerals and rare earths are needed in quantum too. I’m already very bullish on rare earths over the next 5 year technological revolution, but add quantum on top of this which could be another tech revolution on its own, and the demand for rare earths over a 10+ year period is likely substantial relative to what it is today.

The key plays are niobium and nickel which are critical for superconducting quantum computers (more on this below). It’s one of the reasons we’ve seen Chinese firms take huge stakes in Brazilian niobium and nickel miners over the last decade.

Examples:

1. CMOC Group acquired full ownership of Anglo American’s niobium business.

2. CNMC (Chinese state owned) purchased Mineracao Taboca.

3. CITIC Group formed a consortium called China Niobium Investment Holdings.

The U.S. currently is 100% import dependent on niobium with the vast majority of that coming from Brazil.

Niobium is used in superconducting qubits, capacitors, and resonators. It’s in the core architecture of IBM and Google style quantum computers. Importantly, the supply risk is quite severe with 85% of global production coming from a single mine in Brazil.

And then there’s nickel. Nickel is part of the mu-metal shielding process. Mu-metal magnetic shielding is the material used to stop any stray magnetic field. Nickel is by far the best metal for this job and probably makes it one of the most underappreciated metal going forward assuming quantum computing turns out like we expect it to.

Here’s the niobium playbook:

NioCorp Developments (NB): I wouldn’t personally overcomplicate it if you’re looking at pure niobium investments aside from NB. It’s developing the only niobium and scandium project in the US making it the most advanced niobium resource outside the US.

Personally, I’m invested in scandium through Sunrise Energy Metals (SRL.AX/SREMF) but I have no exposure to niobium right now. I suspect that’ll change at some point with a potential addition of NB to the portfolio. More than just being nice thematically, NB has a great balance sheet with 8+ years runway before $800M bank financing comes through.

I’ve been using TrendSpider for all of my charting needs for a while now and honestly haven’t looked back - if you’re not already on it… worth checking out. You can sign up through my link above.

Forward P/S is only ~1.5x on implied $577 million in annual revenue confirmed from materials alone. I think this one is cheap and a great trade thematically for quantum and for other reasons too.

Here’s the nickel playbook:

Read more

The dominant model for AI infrastructure for the last decade or so has been massive data centers, hyperscaler compute, and models too large and power-hungry to run anywhere else but the cloud.

That model is being extended now by a new reality where inference happens at the point of need (the device, the vehicle, the robot etc).

That’s all old news though.

But what’s more important is how to invest in this transition now.

We’ve had lots of names move a lot already.

• KLAC has moved 150% in the last year.

• AMKR has moved 259% in the last year.

• MU has moved 704% in the last year.

The question now is where is the value? Are some of these names still valued fairly or is there new names to seek out?

The important thing to understand is that there is always another bottleneck. The bottlenecks just shift around when one bottleneck is solved. I.e. when silicon performance scale, the constraint shifts to memory bandwidth. When that improves, it shifts to advanced packaging…then power conversion efficiency…then thermal dissipation…then materials etc.

Understanding where those constraints are is the challenge and in this brief paper I’m going to outline it for you.

The Edge market is currently valued at $31 billion and set to grow to ~$70 billion in 2031. That’s a CAGR of 17.5% for 5 years. That’s a market we want to be a part of.

Here’s how I have broken down the layers:

• Layer 1: The Bedrock (Materials, Mining) - 0 to10 years

• Layer 2: The Foundation (Equipment, Packaging, Memory) - 0 to 4 years

• Layer 3: The Enablers (Power, Cooling, Connectivity) - 0 to 4 years

• Layer 4: The Builders (Systems, Design Infrastructure) - 1 to 5 years

• Layer 5: The Perceivers (Sensors) - 1 to 5 years

• Layer 6: The Brains (Edge Silicon, Software) - 0 to 4 years

• Layer 7: The Frontier (Humanoids) - 3 to 8 years

You’ll note I added a timeframe next to each year. That’s my best estimate on when I think this layer is going to generate the most returns and for how long. You’ll note I start a few of them at 0 years…indicating we’re already in the big move for that layer.

You’ll also note based on the timeframes that Layer 1, Layer 4, and Layer 5 are to me the best places to be invested right now to be ahead of the moves.

Layer 1: The Bedrock (Materials & Mining)

Every technology revolution eventually runs into the physical world. Edge AI is no different. Beneath the silicon, the software, and the systems lies a layer of materials that no amount of engineering ingenuity can replace. Copper for power. Silicon for conductivity. Rare earths for magnets. Silver for connectivity.

The bedrock layer is the most upstream layer and often the most overlooked by tech investors.

But it’s also the most structurally compelling part of the entire investment universe which I am well positioned for.

Core (Copper & Silver)

Rare Earths

Layer 2: The Foundation (Equipment, Packaging, Memory)

This is one of the more concentrated layers in the Edge AI universe. ASML is the sole manufacturer of the extreme UV lithography machines where literally no advanced chip can be made without it.

TSMC’s CoWoS advanced packaging process which is the critical tech for stacking memory onto compute.

And then you have memory production dominated by 3-4 companies.

It makes this layer a key chokepoint controlled by a handful of companies. Every Edge AI device for the next decade passes through the following companies.

Layer 3: The Enablers (Power, Cooling, Connectivity)

This is the unglamourous, but necessary layer of Edge AI. It’s where incredible technology is met efficiency priorities.

Every additional watt of AI compute that has been generated has to be removed. Power has to be converted. Data has to be transmitted. And it all has to be done as efficiently as possible.

Air cooling is no longer feasibly possible, so liquid cooling is the new norm. Power conversion efficiency becomes a first order cost driver. Optical interconnects are becoming first order cost in deployments.

Power

Thermal Management & Cooling

Networking & Interconnect

Layer 4: The Builders (Systems, Design Infrastructure)

This is the layer where the physical infrastructure of the Foundation and Enablers is translated into deployable intelligence. It’s the layer of design tools, intellectual property, and system integration that determines how chips get designed, assembled into systems, and how enterprises deploy them.

AI chips are becoming far more complex and harder to design. ARM’s set architecture sits inside virtually every edge device on earth collecting a royalty on each one.

And then the electronic design automation (EDA) software is basically a duopoly with Cadence and Synopsys. EDA market is growing +11% through to 2030. Nothing too exciting but structurally also key to the next few years.

Layer 5: The Perceivers (Sensors)

What makes this layer structurally interesting now is that it’s all about the migration of AI inference onto the sensor. Processing is moving from centralised compute to the point of capture, reducing latency, bandwidth consumption, and power draw.

Historically, sensors were a commodity component but today they’re becoming a compute platform in their own right. That should lead to software like margins.

This layer will lag the silicon buildout. Sensor platforms mature after the compute infrastructure that will process their output is in place. This makes the next 12 months a perfect time to start considering some of the plays in this basket.

Layer 6: The Brains (Edge Silicon, Software)

This is the layer we all know about…the NVDA’s, QCOM’s, AMD’s. NVDA has Jetson and DRIVE, QCMON has Snapdragon X Elite.

The hardware is almost the old story here. The more interesting part of these plays today is the software. This software determines which silicon gets designed in at the platform level. It’s ultimately the level that will prove far more durable over time.

Layer 7: The Frontier (Humanoids)

This is a market projected to be worth ~$40B by 2035. We already have Tesla Optimus entering low scale production with goals to price Optimus at $20k. Figure AI has been valued at $39 billion as of September 2025. Boston Dynamics is in commercial production.

This is where the value will ultimately accrue at the end but we’re still years away and there’s a lot of money to be made in all other layers before we get there.

Disclaimer

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Not Investment Advice

The opportunity I want to talk about today is beneath this. It’s the chemicals layer that makes almost all of this physical buildout possible.

The pipes, the cooling systems, the thermal infrastructure, the chemicals, the adhesives that make all of this possible.

• How does advanced packaging work without the chemical systems? It doesn’t…Underfill adhesives mechanically bond the die to the substrate. Die-attach films then manage the heat path between these dies with tolerances measured in microns.

• Photoresists and etching are a huge part of the modern fab process and these are predominantly chemical processes.

• Where does the capital in the $6B deal between META and GLW go? Yes, optical figure is the core of this deal but many don’t realize that every inch of fibre is wrapped in a polymer system.

• Every 800G transceiver is held together with adhesives. Every fab is plumbed with fluorpolymer pipes.

Thinking of the AI infrastructure buildout without the chemicals layer is an incomplete look.

No token can be created without a huge amount of optical fibre, polymer coatings, buffer tubes, fab piping, optical adhesives, thermal interface materials, and ultra-pure fluid etc.

But the most exciting part for an investor is that a lot of these stocks haven’t had their big move yet. Some of them have had a nice move from their lows in 2025 but relative to most “AI driven” stocks, chemical stocks haven’t had their time yet.

• Entegris (ENTG) is trading only 30% above where it was 5 years ago.

• Chemours (CC) is down compared to five years ago.

Although some of them feel a bit more expensive today, a lot of the target entry prices you’ll see below are fairly close to todays prices.

Before we get into the article…a quick note on my web-app. I am released a web-app that I have been developing for the last 2 months. It’s a good upgrade on my current spreadsheet. It contains:

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A Concise Look into the Chemicals Thematic

I’ve edited this section a lot.

My first draft was detailed but long. I realized there’s probably not many of you out there who actually want to learn about the chemicals so I made this section about 50% shorter than it originally was.

I’ll go into a bit of detail… but my aim here is to give you an idea on the chemicals thematic without you having to read a 10-minute chemistry paper.

The money right now is in the industrial materials. It’s why miners has been such an important thematic for me to build positions in. We’ve had SREMF jump +50% this month and TMQ, COPX showing some strength. CTGO is also a new purchase for me too which is up nicely.

And it’s why chemicals is next on my radar. If you need interconnect, cooling, efficiency etc, you need the miners and you need the chemicals players.

For me, here’s the four key shifts happening at once which will lead to a chemicals bull market:

1. Fiber Optic Glass

Light moves far quicker than electricity through copper wires which is why optical fibre has quickly become the backbone of the long-distance interconnect. Copper simply can’t move data fast enough or efficiently enough within data centres or between data centres.

Here’s the chemical angle of this:

A fibre-optic is not just “glass”. It is a glass-polymer composite.

The core (the glass) is useless on its own so to make it deployable you coat the strand for protection, bundle those coated fibres into protective inner rubes, and sheathe the whole bundle in a flame-retardant outer jacket with gels and resins and alike.

For every dollar of glass, there is a dollar of specialty polymer pulled in beside it. And this is where names like Celanese, Chemours, Shin-Etsu, and Arkema operate.

It’s where the narrative around these names shifts from “diversified industrial” to an “AI infrastructure derivative”.

2. Fluoropolymer Pipes

A semiconductor fab is a factory where chips are made. Inside these fabs are miles of pipes that carry the chemistries needed to etch, clean, and pattern silicon wafers. These chemicals are highly corrosive acids and bases, aggressive solvents, abrasive slurries, and ultra-pure water that is cleaner than anything used even in the pharmaceutical industry.

Demand is now driving the largest semiconductor buildout in history. TSMC, Samsung, Intel, SK Hynix etc are racing to add 3nm nodes (3 billionths of a metre) onto a silicon wafer.

The smaller the node the more chemically demanding the process becomes. The content-per-wafer increases at smaller node sizes. This means that chemistry benefits from:

1. Smaller nodes

2. More wafers

Every chemistry operation that improves yield by even a fraction directly ties to revenue. Every new fab that comes online requires its own chemical supply infrastructure. Simple as that.

That’s why demand for companies like Chemours, Entegris, and Arkema is set to rise with AI.

3. Liquid Cooling

This is the simplest one.

Today’s AI chips draw ~700-1,200 watts each. And advanced packaging them into a single rack creates power densities that air conditioning cannot physically cool down enough.

This is why liquid cooling is the only way to manage it. Data centres now have coolants flowing through pipes attached directly to the chips (“direct to chip”) or in some cases data centres have entire servers submerged in non-conductive fluid (“immersion cooling”).

This creates a materials problem though. The coolant, the seals, and the gaskets all have to be chemically compatible with each other. There’s only a select few materials that qualify for this which are fluoropolymers, EPDM, silicone, and certain thermoplastics… exactly what Chemours, Arkema, Rogers, and Henkel produce.

4. Optical Transceivers

Back to optical fibre…A fibre on its own does nothing. It’s nothing without an optical transceiver at each end.

A transceiver is a small USB sized device that converts electrical signals from a switch or GPU into pulses of light heading down the fibre. On the other side it does the opposite (i.e. translates incoming light back into electricity).

Every fibre link in a data centre has one of these at each end which means transceiver volumes scale roughly at twice the rate of optical fibre. Here’s where it gets important though.

The speeds that these transceivers have to handle is climbing and will continue to climb. But the device itself isn’t getting any bigger to compensate. At those speeds the issue becomes:

1. Keeping the glass fibre and the silicon chip lined up perfectly because at that speed even slight misalignment scatters the light and the signal degrades.

2. Getting rid of the heat the chip throws off without room to add a larger heatsink.

Guess what solves both of these issues? Materials.

Optical adhesives are glues that bond glass to silicon holding the alignment.

Thermal interfact materials are compounds that move heat from optical chip to a heatsink, keeping the module from overheating itself at 1.6T speeds.

Henkel are one of the key players here.

Here’s Your Basket of Stocks:

How I’ve scored them:

1 = Revenue most directly tied to the AI buildout.

3 = Revenue least directly tied to the AI buildout.

Mini Deep Dives into My Favorites:

Celanese (CE) - AI Purity: 2

CE is one of the largest engineered materials and acetyl chain producers. The most relevant AI part of the company is Crastin PBT. It’s a thermoplastic the company explicitly markets as a top choice resin for high performance optical fibre cables. The rest of the business is in the traditional cyclical chemistry industry (engineered plastics for cars and industrial uses for example).

As hyperscalers continue to commit to data canter build out, demand for optical fibre accelerates and CE should remain one of the larger beneficiaries of this.

Valuation:

CE currently trades at $57 ($6.3B market cap) which means we’re trading ~8x 2026 expected EBITDA of $2.15B. CE currently trades in the mid range of its cycle ~8x EBITDA. Historically, this at the top of cycles this has been ~12.5x so if my assumption is correct and we’re heading into a chemicals cycle, then CE on FY27 EBITDA of $2.3B at 12.5x EBITDA gives you $28.75B EV.

If we subtract net debt of $9B you’re looking at a market cap of ~$20B or $181 share price on current shares outstanding.

That valuation target sits around this key resistance level. Probably a worthy trade to consider if you’re long chemicals and if you can wait for a nice entry around these moving average cluster, though not one in the basket I’d look for if I was looking for one that is going to be a lot more tied to AI demand.

Chemours (CC) - AI Purity: 2

CC is a fluorpolymer company that handles:

• Fab plumbing (pipes, valves, and tank linings to move corrosive chemicals and acids around fabs).

• Cooling (heat transfer fluids sit directly within the direct-to-chip and immersion cooling systems). This is still in the very early days though with capacity coming online in late 2026 making this more of an emerging opportunity for CC.

The broader immersion cooling fluids market is growing at 24% CAGR to ~$1.6B in 2032. CC has potential here to build a meaningful share which, if they execute, should definitely re-rate the company further towards the more AI pure players in this basket and further away from CE trading in the 8-12x EBITDA range.

These two angles make CC a solid play on the physical AI infrastructure buildout. I see more upside here than a company like CE, but the AI demand story is not yet material enough.

Valuation:

I value CC very similarly to CE… on an EBITDA multiple basis. CC is also in a mid-cycle trading at $23 and slightly further extended away from MA’s relative to CE which has run less.

CC trades at 8x EBITDA and 14x EPS whilst set to grow EBITDA at 14% and grow EPS at 37%. These EPS growth rates are historically quite lumpy though.

EBITDA is expected to be between $800M and $900M in FY26 and $1B in FY27 so despite not being as pure as I’d like on the AI story yet, the growth rates are actually very reasonable for the multiples it trades at which to me gives a nice floor in the valuation.

The upside currently is a bit less certain, but the downside risk here is likely limited.

Element Solutions (ESI) - AI Purity: 1

ESI is a pure advanced packaging play… far more “AI Pure” than CC and CE above. It’s arguably as close as we get to a pure play infrastructure materials company that exists in the chemicals space.

It’s involved in the plating, solders, and metallization processes that hold modern AI accelerators and HBM memory stacks together.

Here’s the AI angle:

• Semiconductor Solutions: Advanced packaging materials for leading-edge chips where AI GPU demand is the key driver.

• Semiconductor Solutions: Thermal interface materials for high power consumption AI GPUs and CPUs.

• Kuprion: This is a next-gen die-attach material that uses copper rather than silver sintering. It is currently a supply constrained segment of the business but ESI are investing into capacity to make this a material revenue generator in 2027-2028.

• Circuitry Solutions: This is the chemistry involved to plate and etch the dense multilayer PCBs inside AI servers and networking gear that just generated a record quarterly revenue growing organically 17% YoY.

AI pure but pricey…see below:

Read more

This won’t be an in-depth article…but it will be a 5-minute read where I hopefully give you a very good insight into where I think the market opportunities currently sit.

I’m writing this post the hyperscaler reports where only GOOGL is up after hours. META, AMZN, and MSFT are all down between 2.5-6%.

Oil is trending a bit higher again, airline stocks look like they’re heading down in the near term, and SPY looks like it needs a little cooling off.

This is not a bearish argument or anything saying we are near the top of the cycle. I don’t think we are. It’s just an honest assessment that we moved a lot in quite a short amount of time, and that often is a sign that a cooling off period is needed.

Look at my plays today for example. LMND reported very strongly…and closed down 14%. I think a large part of this move was algo driven but the story remains.

Before we get into the ideas for the week, I just wanted to highlight the database I’m currently building which is currently in beta testing and will be scheduled for full release in May.

This is a fully functional web-app / database / research website all in one go. You also get:

• Daily market commentary

• My personal portfolio and watchlist

• Weekly thematic commentary

• New Ideas

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I am nearing the end of my beta testing now. I do not have a specific release date but I’m working as quickly as I can to make sure this product is one of the best on the market. I hope for the release to be in early May.

Here’s where I think the opportunities lie right now:

Paid subs should know that I am getting quite bullish on certain critical metals. I have been buying scandium regularly for weeks now. I’m up ~22% on that. I’ve been buying copper now for months. I’m still flat on that position.

And more recently I started initiating buys into silver. You can see why I’ve been buying silver here (it also tells you the 3 silver stocks I've been buying).

If you’re not reading that article…let me do a very brief silver summary here:

Silver is no longer just a monetary metal and inflation hedge. That framing misses the bigger picture entirely.

The bull case for silver is that it sits at the heart of the AI trade and I think the metals/materials/chemicals are next in line for a bull market.

Silver has the highest electrical conductivity of any element on earth, making it a critical metal inside the connectors, switches, and advanced semiconductor packaging that power both data centers and edge AI devices like robotics and drones.

As the AI buildout then shifts from brute force training to inference at scale, efficiency and energy loss becomes the advantage. And that’s precisely where silvers properties become indispensable.

Critically, silvers cost as a percentage of the total AI buildout is completely immaterial, meaning even a significant percentage increase won’t slow demand.

On the supply side, the picture was already broken even before AI entered the equation. The market has been in a deficit for 4 consecutive years because silver essentially is only mined as a byproduct of other metals making it impossible for miners to simply ramp output.

Yet despite this backup, silver miners remain historically undervalued - PAAS for example has seen cash from operations frow 196% and margins expand from 2.2% to 31.7% yet trades at just 12x forward earnings as if the market expects silver prices to collapse. The gap between miner valuations and the underlying commodity price represents what looks like a significant opportunity to me.

Metals and mining are a big opportunity today I think.

The Other Big Opportunity is With The Chemicals:

Paid subs will know that I have not bought into a chemicals play yet, but I’ve been researching them heavily to understand exactly where each stock lies in the supply chain.

I’ll have a separate piece out on the chemicals layer soon (within the next week) so make sure you’re subscribed here so you get that for free.

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The core argument behind chemicals is that the chemicals and purification systems are extremely in demand for the ongoing AI trade. It’s the “hidden layer” as I like to think about it.

As AI drives demand for more complex chip architecture (HBM memory, 3D packaging, 2nm logic etc), manufacturing tolerances tighten, and the risk of yield destroying contamination grows.

This is where companies like Entegris (ENTG) come in.

Ideas For the Rest of the Week:

Here’s some charts I’m monitoring closely outside of the thematics above.

Read more

AI started as a computing power problem. It then became a memory and packaging problem. It then became an electricity problem. It’s now a physical materials problem.

Jensen Huang is telling us exactly this as well. He estimated an $85 trillion physical world infrastructure upgrade over the next 15 years and I bet silver plays a bigger role in all of that than many people are expecting right now.

My focus recently has been less on the stocks/thematics people are agreeing with (optics, thermal management, power systems etc) and more with those thematics people aren’t talking about as much (silver, metals, chemicals).

I’m not saying there’s no more money to be made in optics, thermal management, and power systems… I think there is. But I look for outsized risk to reward opportunities and when every man and their dog is on board an investment theme…it tends to be a signal that the risk to reward is diminishing more than many think.

I ultimately wouldn’t be doing my job right if I was discussing the next theme to invest in as being packaging or optics.

That’s why I have started to research silver on a daily basis over the last month or two… all of which I’m going to concisely unpack into this article.

Introduction

Paid subscribers will know that I have been bullish on silver for some time now. I invested in Silvercorp Metals (SVM) last year at ~$3 and sold it on the 30th of January ~$12.15.

Above is the timestamped alert of that from my Google Spreadsheet (soon to be updated to my web-app).

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I invested in SVM more on the basis of a catch-up trade that I thought miners were undervalued compared to the underlying commodity (which I still deem to be very true) but my conviction on the underlying commodity (silver) was nowhere near as high as it is now.

So now I have:

1. Huge conviction in silver and its potential to head to +$150-$250 in the next 24 months.

2. A remaining conviction in silver miners being undervalued relative to the underlying commodity.

That creates a strong investment thesis.

Silver has always been thought of a precious metal or a monetary metal. One that acts as an inflation hedge or moves against the US Dollar. Whilst that may be true, it’s only a very small part of the silver thesis today.

Silver is an industrial metal with properties that no other metal has. And unsurprisingly… these properties are core to the entire AI trade.

When you combine the entire demand story which I’m going to explain with a supply picture that was already broken before AI entered the equation properly… and then you overlay that with equity valuations that remain historically depressed… you get a setup where the risk to reward seems very unique.

Contents

1. Silver Demand

2. Silver Supply

3. How high can silver go?

4. Why silver miners are still undervalued

5. The best silver miners to invest in

Silver Demand

Silver has the highest electrical conductivity of any element on earth… higher than copper, higher than gold. For most of the AI buildout early phase, that fact wasn’t too important because the near term bottlenecks were so important.

You needed more GPUs, more memory, faster networking, more power etc. It’s why stocks like:

• AMKR is up 330% in the last year

• BE is up 1,140% in the last year

But the phase we are entering next is different. It’s gradually becoming less and less about brute-force training and more becoming inference at scale and high efficiency. The economics begin to change quite a lot based on this.

The difference with inference is that the demand for continuous compute power is much more than in training. Tasks require thousands of loop-backs, multi-tasks working as part of a larger task, and above all continuous work.

The question becomes more about who can produce AI output at the lowest cost per unit with the least amount of energy wasted. At least, that’s what it is becoming. The first 3 years or so was brute force training and a race to build out AI. At some point efficiency had to become the more important part of the equation.

And that’s exactly why silver is becoming very important.

Silver sits inside all of the current bottlenecks:

• You have connectors for AI data centers and high-voltage grid infrastructure.

• You have switches for power electronics, circuit breakers, and grid distribution.

• You have packaging for advanced semiconductors and microelectronics.

All of these components govern electric loss and thermal performance so as hardware scales, demand for these components scales with it. And subsequently when these components become more important, the makeup of these components (i.e. the materials…i.e. silver) becomes more scrutinized.

But there’s much more to the AI trade than just the data centers. AI is heading to the edge with robotics, drones, medical devices, smartphones etc. And the same logic that applies in the data centers applies to the edge…but its’s amplified at the edge.

Edge devices have to have smaller batteries meaning power efficiency becomes even more important. There’s no room in edge devices just to add another cooling devices if thermal management is the issue. In data centers, there’s always room and capital available to spend your way out of the problem. That is not the case at the edge. You can’t just add more components because weight matters so much.

Here’s where we can take it an extra step.

Silvers cost as a percentage of the total AI buildout is negligible. By that I mean, when you’re building $1 billion data centres, the line item for silver is barely noticed. The material items are the land, the power, the GPUs, the memory, the networking gear. It’s not the cost of the silver within those components.

That means if silver costs rise by 50% over the next 2-3 years, it will still remain an immaterial part of the AI buildout cost. And people will keep buying it because:

1. It’s so necessary.

2. It’s so cheap relative to everything else.

So, from the demand side, I put it simply like this:

Bullish on the AI data center buildout? You should be bullish on silver.

Bullish on the Edge AI thematic? You should be bullish on silver.

I haven’t discussed solar, EVs, and other electrification here in this article either. But those longstanding themes remain and are still bullish for silver.

Supply

Before AI entered the equation, the silver market was already in a structural deficit. In 2024, the silver market was pressured because of solar demand, a grid upgrade, and general electrification. Today, those same pressures still apply but we also have the AI hardware demand as well.

There is currently ~148.9 million ouches of silver shortage which is the 4th consecutive years we have had a deficit. The main issue in supply is two fold:

Firstly, the vast majority of silver is mined as a byproduct of other extractions like lead, copper, and zinc. This simply means miners can’t just produce more silver. The silver output is fundamentally constricted by the output of copper, lead, and zinc.

Secondly, Mexico. Mexico supplies ~25% of global silver. For reference, that’s a much more concentrated source share than Saudi Arabia holds in oil.

Mexican output has been in a sustained mulit-year decline with no replacement capacity on the horizon. When your largest supplier is structurally shrinking and there is no pipeline of new projects ready to offset it, you do not have a cyclical supply problem. You have a long-term structural issue.

How high can silver go?

This is where the trade starts to get really interesting for me.

At the time of writing this, silver sits at $75.36. Most investors look at this and think that’s a 56% increase on 1980s and 2010 levels which may seem like a fair jump based on CPI and a modest increase in demand.

But it’s way off.

Silver is a monetary asset. It should not be measured against how consumer prices move. Instead, it should be measured against how much money exists to chase a fixed supply of metal…i.e. M2 money supply.

M2 money supply was $1.6 trillion in 1980. It stands at approximately $22.6 trillion today.

That’s a 14x increase.

So, if you apply that multiplier to the 1980 peak of $47, the money-supply adjusted equivalent is $658/oz today. You can look at different money supply aggregators but you’ll end up above $500/oz no matter how you look at it…compared to $75 today.

Let me be clear. This is not a price target. It’s a way of calibrating a bullish outcome and it’s a way of doing it fairly logically as well.

Adjusted for the dollars in existence, silver at $75 represents ~ a ninth of what $47 represented in 1980. Hopefully that gives you a gauge of the potential upside for the underlying commodity.

A reminder as well:

This article is actually going to get all tied up in the section below talking about the silver miners. The silver miners currently have a clear valuation gap between themselves and the underlying commodity…and I just put a logical way (though fairly bullish way) of the underlying commodity prices increasing over 8x from here.

Why Silver Miners Are Undervalued

With silver prices above $75/oz the earnings profile of silver miners has changed fundamentally from 2-3 years ago.

Here’s a couple examples of cash from operations for Hecla Mining (HL) and Pan American Silver Corp (PAAS).

PAAS’s cash from operations relative to FY23 has increased 196%.

Margins have increased from ~2.2% to 31.7% (PAAS) and 6.0% to 37.3% (HL).

It’s a completely different outlook for well operating mines.

Yet, despite this equity valuations have actually depressed since 2023. In 2023, PAAS traded above 22x NTM PE. Today it trades at 12.1x NTM PE. Its the market pricing silver miners as if the current earnings stories are temporary… or as if a reversion in silver prices is likely and therefore cash flows should be heavily discounted.

I personally disagree with all of that as I’ve made evident in this article.

For what it’s worth…if you adjust PAAS for example to measure how the stock is valued relative to the underlying commodity… you see PAAS near the very lows.

So, here’s how the situation can get resolved:

1. Unlikely: Silver prices break down sharply which would agree with the current multiples miners are trading at but disagree with my silver thesis entirely.

2. Likely: Equities re-rate upward to reflect the earnings power that these businesses have now silver is at $76/oz. This should only get stronger and stronger over time.

Given my thesis on the structural supply constraints and the expanding demand base, I think my likely scenario has ~80% probability of happening.

Which Silver Miners Are My Favorite?

The natural next question is of course how we play this theme. Here’s my plan:

Read more

1. We’ve had our scandium play (SRL / SREMF) jump 50% in the last month.

2. NuScale Power (SMR) just 42% in the last week.

3. ClearPoint Neuro (CLPT) jump 37% in the last week.

4. And most importantly, Lemonade (LMND), my largest position jump 29% in the last week.

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This is a very challenging, but great time for stock pickers. I think it’s very important here, as always at new highs, to act with a bit of caution. Futures are currently down which is of course more than welcomed and expected after the recent surge. Whether this is a technical pullback (good), or the start of a more long-term structural pullback because of re-escalation again (bad), I’m not sure.

But as ever, I’ll let the index charts dictate what I do rather than getting lost in the political and macro madness of today’s world.

On a less macro level, I still see the biggest opportunities in hardware, mining, and LatAm as well as my AI application plays like ZETA, LMND, and UPST (of which my returns are currently quite mixed although they all had great weeks last week).

Before we get into the ideas for the week, I just wanted to highlight the database I’m currently building which is currently in beta testing and will be scheduled for full release in May.

This is a fully functional web-app / database / research website all in one go. You also get:

• Daily market commentary

• My personal portfolio and watchlist

• Weekly thematic commentary

• New Ideas

• Weekly Videos

All for just $24 a month (or $240 a year).

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Lowest Risk: Chemicals

This is the trade people aren’t thinking about enough. For the last few years, the AI investment conversation has been centered around the likes of NVDA, TSMC. Now it’s moved rightly on to the bottlenecks (packaging, optics etc). The more upstream layers is where I think the biggest alpha gap currently is though.

That’s critical metals (silver, copper) like I talked about last week:

And then the molecular foundation that makes all of this physically possible: Chemicals. Of which most are trading around 2019 levels.

Let me be more specific. Many investors now know about the optics trade (AAOI, CRDO, LITE etc). Fibre optical cables are not just glass though. It’s much more complex.

Every part of this fibre requires UV-cured polymer coatings, adhesives, protective jacketing made from advanced compounds etc. So as hyperscalers continue to deploy billions of metres of fibre optic cables, they are also relying on the demand for the specialty chemicals that make this possible.

The market has yet to price this in.

I’ll dedicate a separate post to this theme soon. But here’s the best chemicals stocks:

1. Element Solutions (ESI)

2. Entegris (ENTG)

3. Chemours (CC)

4. Cabot Corp (CBT)

5. Rogers Corp (ROG)

Dedicated post incoming on the chemicals industry.

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Medium Risk: Silver

I spoke about silver last week quite comprehensively. I always get torn here between discussing new themes or just doubling down on themes I have already spoken about. I have recently decided to do the latter.

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The war in Iran continues to reshape global energy markets at a pace that is almost impossible to keep up with but markets are slowly starting to look a lot more bullish again.

This environment remains very favourable to the stock pickers rather than index holders. YTD there’s been some incredible moves in many thematics (stablecoins, optics, semiconductor testing etc) whilst indexes have struggled to stay afloat.

Personally, I’m seeing the biggest opportunities in hardware, mining, and LatAm world right now whilst still remaining very long term bullish on a few AI application plays like LMND and ZETA, though the market currently isn’t rewarding those plays in 2026.

That’s why I’m starting to slowly increase my exposure to plays like copper, solar, and scandium which have some very nice momentum at the moment. If you want to see my exact stock portfolio, click this link:

Before we get into the ideas for the week, I just wanted to highlight the database I’m currently building which will be released to paid subs for beta testing in the next 48 hours with full release scheduled for May.

This is a fully functional web-app / database / research website all in one go. You also get:

• Daily market commentary

• My personal portfolio and watchlist

• Weekly thematic commentary

• New Ideas

• Weekly Videos

All for just $24 a month (or $240 a year).

Subscribe now

Lowest Risk: Silver

Most investors still think of silver as just another precious metal but that’s a massive underappreciation.

Silver has the highest electrical and thermal conductivity of any metal…by far. That makes it a critical one in the AI infrastructure buildout, especially as we shift from training to inference. The aim over the next few years will not just be to build the biggest models, but more importantly to run them efficiently and continuously.

This challenges the economics of the entire hardware cycle that we are in.

The objective now ultimately becomes a focus on lower cost per token and electrical and thermal efficiency. Silver sits within all of these hardware stacks like connectors, relays, packaging, thermal interface materials, and switching systems.

This makes silver heavily in demand in the agentic and physical AI world. More hardware equals more silver in systems where electrical loss and heat management matter enormously.

And then you need to add in the angles of:

1. Solar: The world just installed a record amount of solar capacity in 2025. Silver is the critical input in a photovoltaic cell.

2. Defence: Modern warfare is becoming more and more an electronics problem. Drones, sensors, ruggedized connectors etc. Silver is a critical metal in all of this.

3. Supply: Silver runs as a byproduct of lead, zinc, and copper so miners cannot just increase the supply of silver. We’ll likely run at a supply deficit for a while.

Considering all that…it’s hard not to be uber bullish on silver.

A higher risk way to play the silver trade is through SVM. Paid subs will know that I sold this last month for a +200% gain. I have not currently entered this one again, but it’s high on the watchlist.

Other potentials are Hecla Mining (HL), Pan American Silver Corp (PAAS), and Contango Silver & Gold (CTGO).

Medium Risk: Solar

I’m becoming very bullish on solar as nice way to play the next 2-3 years. Paid subs will know that I have recently started buying into TAN but it’s quite likely I’ll also add an individual stock quite soon to heighten the risk on this theme a bit.

Solar panel costs have now dropped 50% since 2022 and annual installations have nearly tripped. A solar panel built today generates electricity for 30 years with no fuel costs, no prices increases, and no supply risk.

The events of the last 6 weeks show you why this is so important.

From an individual stock pick point of view, my current options are:

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Behind the paywall below is the link for my April 2026 spreadsheet. In this article, I’m going to explain exactly how this portfolio and database works and how you can get value from it.

Firstly, it’s where I post all of my current holdings (with real monetary amounts), allocations, trades, buys, sells, adds, trims, and watchlists. It’s 100% transparent and all timestamped to the exact second.

But that’s just a small part of the total value add.

I also have an exciting update to this "spreadsheet” too.

Here’s how the database works:

Before we get into the spreadsheet, here’s the update:

By the end of April, I’ll have a fully functional web-app. Here’s a sneak peek of the UX right now.

And that’s just a small part of the total offering. On top of this database you also get:

• Daily market commentary

• My personal portfolio and watchlist

• Weekly thematic commentary

• New Ideas

• Weekly Videos

This web-app is going through beta-testing starting this week. My expected timeline is by the end of April it will be fully functional.

Portfolio:

• My core portfolio including exact dollar amounts.

• My exposure broken up into themes. Here’s a snippet of the portfolio tab to show how I’m currently weighted.

Everything here is formula driven directly from Yahoo finance live prices. You get full access to my exact portfolio and monetary amounts at all times. I don’t hide anything unlike most people. I’m all for transparency.

Portfolio Valuations:

In this tab, I’ve broken down my portfolio using a nice quantitative approach measuring revenue and EBITDA expected growth rates vs current NTM multiples. It’s a nice way of screening out some stocks in my opinion and it’s a nice building block for a lot of the work I do… though of course a lot more analysis goes into it that that.

Watchlist:

I also share my exact watchlist with:

• Technical entries: Where the chart says the “risk/reward” is skewed in your favour.

• Fundamental Entry: Where I see a fair value price where the math actually makes sense.

Here’s a snippet so you can see what the watchlist looks like.

Here you have access to daily movements in my watchlist, entry price per technicals, entry price per fundamentals, and then ultimately whether I’m interested in the stock or not.

Any that I am interested in are communicated in the paid chat (I send 5-20 messages on a daily basis in that chat).

Theme Tracker:

This tab is still not complete, but it will be very soon on the web-app.

This tab collates all the stocks per theme and gives you the weekly price action on them to give you a very quick indication of what theme is running hot right now. No need to search each stock on your chosen website. You have access to all stocks, and all price movements per stock/theme right here.

I hope you’re starting to realize this service is far more than just a portfolio. It’s a full database allowing you to either follow my portfolio and stock picks, or use the data to validate your own picks.

Specific Tabs Per Theme:

On my database I have a tab for each theme.

Current we have:

• Robotics

• Space

• Power Grid Upgrade

• Optics

• AI Applications

• Miners

• Cybersecurity

• Edge AI

Each tab has every stock in that theme broken down by revenue and EBITDA growth rates relative to its EBITDA multiple.

Here’s an example of the Edge AI tab:

1. A list of all the stocks in the theme.

2. A way to track the daily price action of all the stocks within the theme.

3. A way to see if the growth rates to multiple makes sense (“Bullish Fundamentals” column).

4. A way to see if the technicals look attractive based on moving averages (“Bullish Technicals” column).

5. A way to see if both fundamentals and technicals make sense at the moment (“Overall?” column).

This tab updates itself automatically every minute.

Link to spreadsheet

I’m going to put the link below the paywall below:

Read more

But if there’s one lesson we’ve all learnt from the optics megatheme, it’s that huge money can be found by looking where nobody else is.

That’s why I’m writing this piece. I’m bullish on the plays a lot of us know about (ETN, HUBB etc), but there’s far more ways to play this theme than owning these stocks which now trade at PE multiples +30x.

The power grid upgrade isn’t an AI trade, nor a clean energy trade. It’s something far more fundamental. We’re on the verge of major economic growth, technological leadership, and energy transition…but every single one of these run through wires.

Not least old, overloaded, and massively underfunded wires.

BNEF’s latest grid outlook showed that globally grid CapEx has now topped $470B in 2025 and that rate of CapEx growth is still growing in the double digits. Capital is flowing into hardware, software, advanced power-flow control systems, and grid-enhancing technologies simultaneously. This is not just a cyclical spending spree…it’s the beginning of what forecasts are predicting as a $1.4 trillion infrastructure super-cycle running to 2030.

Here’s the part you need to understand though. You can’t simply just modernize a grid. You can’t train a transmission line crew in a few months. You can’t get HVDC cables delivered in under two years. You can’t manufacture a large power transformer to order and receive it before 2027.

The supply chain that builds and upgrades this infrastructure has some real constraints… in materials, in manufacturing capacity, in labour, in regulations that can’t be resolved by just increasing CapEx. This pressure is what makes the grid infrastructure buildout one of the most non-discretionary investment themes in the global economy today.

Before we get into this article, I want to mention my database that I am building for paid subscribers.

For the last 1-2 years I have shared a Google Spreadsheet. You can see the latest one here:

This document gives you access to:

• My portfolio

• My watchlist

• My theme tracker

• All of the stocks per theme I follow ranked by growth vs multiples (250+ stocks tracked amongst the one exciting themes).

What’s even better is that this document is becoming a web app.

Over the next few weeks I’ll be sharing sneak peeks as we enter beta testing with a group of paid subscribers helping shape the product into exactly what this community needs. This is being built with you, not for you.

Because what I’m building goes well beyond stock picks and data dumps. I’m building a platform where subscribers have access to all the research, all the data, and all the commentary they need — in one place, updated in real time. And I do it fully transparently. My exact portfolio is shared so you always know precisely where my own money is going as well.

If that sounds like something you want access to, the link is below.

Subscribe now

Contents:

• Why this is a decade-long structural theme

• Bottleneck 1: The Transformer

  • Solid-State Transformers

• Bottleneck 2: Grain Oriented Electrical Steel(GOES)

• Bottleneck 3: Switchgears & Breakers

• Bottleneck 4: High Voltage Cables

• Bottleneck 5: Interconnection

• Bottleneck 6: Transmission Line Construction

• Bottleneck 7: Towers, Poles, & Structural Hardware

• Bottleneck 8: Grid Resilience

Everyone is talking about the grid. But almost nobody is talking about it correctly.

A proper thesis requires understanding why the money flows, where it gets stuck, and which second and third-order beneficiaries capture the value that the first-order trades have already priced in.

This piece does that. We’re going to walk the entire grid upgrade chain from raw material to software layer, identify every genuine bottleneck, price those constraints, and give you the full investable universe for each one (which you’ll then see on my database/web-app). I mention every relevant public stock, and then offer my highest conviction name/names within each section.

Why This Is a Decade-Long Structural Theme

U.S. electricity demand is doing something it hasn’t done since the 1970s: it’s growing meaningfully.

For two decades, from 2000 to 2020, overall electricity consumption in the U.S. actually declined slightly as efficiency gains offset population growth. That era is over.

AI data centers, manufacturing reshoring, EV fleets, and the electrification of homes and industrial processes have reversed the trend sharply. Analysts now project the US will need more than 150 gigawatts of additional capacity by 2030. To put that in context, the entire existing U.S. power fleet is roughly 1,200 GW — so we need to add the equivalent of ~12% of the entire grid in 5 years.

The grid itself — the wires, poles, substations, transformers, switches, and software that move electrons from generation to consumption — was largely built in the 1950s through 1970s. More than half of U.S. distribution transformers are beyond their expected service lives. Many transmission lines are 40-50 years old. The system was designed for a one-directional flow of power from central plants outward. Now we’re asking it to handle bidirectional flows from millions of rooftop solar installations, intermittent wind, distributed storage, and the concentrated power demands of 50MW data center campuses.

Global grid capital spending crossed $470 billion for the first time in 2025, up 16% year-on-year. U.S. utility capex hit $202 billion in 2025, up 8% from the prior year which itself was up 12.6%. This isn’t a one-year event. It is the beginning of what many analysts are calling a $1.4 trillion utility infrastructure super-cycle from 2025 to 2030.

The constraint is not capital. Capital is flowing well.

The constraint is physical: you cannot build the grid faster than the materials and workers that go into it.

The Eight Bottlenecks

Bottleneck 1: The Transformer

Electricity is generated at power plants at quite low voltages…10,000 to 30,000 volts. But the transmission of electricity at these voltages is inefficient today. Basic physics…the longer the wire, the more resistance, the more energy is lost as heat.

To move electricity economically across hundreds of miles of wires you therefore need to increase the voltage to +200,000 volts. This is what a transformer does. It steps voltage up before transmission and steps it back down before it reaches its end destination.

Pretty much all electricity generated in the US passes through at least 1-2 transformers before it is used.

How are transformers made?

Most transformers are made from a highly specialised steel alloy. It’s called grain-oriented electrical steel (GOES) - that’s the core part of a transformer.

You’ve also got:

• The windings made from copper.

• The insulation

Here’s some basic stats to evidence this bottleneck:

1. Power transformer demand has surged 119% since 2019 whilst distribution transformer demand is up 40%.

2. Wood Mackenzie estimate 30% supply shortfall for power transformer and 10% shortfall for distribution transformers.

3. Power transformers now have a 2.5 year (128 week) lead time.

4. Utilities are paying 4-6 times what transformers cost in 2022.

5. The global transformer industry carries a 2-3 year manufacturing backlog not expected to ease before 2027.

List of stocks:

• Eaton | ETN

• GE Vernova | GEV

• ABB Ltd | ABBNY

• Siemens Energy | SMNEY

• Powell Industries | POWL

• Hubbell | HUBB

• Hammond Power Solutions | HMDPF

• Hitachi Energy | HTHIY

• SPX Technologies | SPXC: Has transformer components and electrical testing equipment business relevant to the bottleneck.

• Legrand | LGRDY

Favorites:

Eaton | ETN | $140.1B

ETN is a diversified power management company that sits right in the middle of the US grid modernisation theme. It designs and manufactures the full stack of electrical infrastructure - transformers, switchgear, circuit breakers, power distribution units, busway systems etc - across every voltage class.

Specifically in the transformer space, ETN is one of the small number of Western manufacturers with the engineering capability to build the transformers. It’s also acquired Resilient Power Systems making them a play on solid-state transformer technology too (see below).

Considering the growth rate estimates for ETN (mid teens for EPS growth), a 27x PE is quite expensive…but there are many stocks that are expensive for a reason and I’d put ETN in that basket.

GE Vernova | GEV | $242B

GEV does much more than solve the transformer bottleneck. It’s a massive global energy company operating across:

1. Power

2. Wind

3. Electrification

Its electrification segment is the fastest growing segment and supplies the hardware and software that connects generation to consumption. The business has an extremely strong moat but the investment thesis relies on you being comfortable buying a stock trading at 62x NTM EPS.

Here’s how I do “back of the napkin” maths on GEV:

Management guidance implies $5-6B in FCF in FY27-FY28 which means GEV is currently trading ~48x 2027 FCF which is a premium multiple, but it’s also a multiple that can be justified when FCF is growing at +40%. I can’t see GEV earning much more than 50x FCF multiple even if the electrification backlog doubles, and the wind segment stops becoming a drag. I wouldn’t be bearish on GEV at all, but I think at current levels you’re not aiming for more than 20-30% upside from here in the near term.

With that being said, I think GEV is one of those stocks you should always follow. If you get a +20% pullback I’d be inclined to invest as a fairly comfortable way to earn ~50% from a trade.

Solid-State Transformers (SST)

There’s a potential long-run solution to this transformer bottleneck though in Solid-State Transformers (SST) and the SiC Revolution.

The conventional transformer is a passive iron core filled with oil. It does one thing and one thing only: It converts voltage.

The emerging alternative is a software-designed power conversion built on Silicon Carbide (SiC) semiconductors. Instead of sitting on a pad and just converting voltage at a fixed ratio, an SST consolidates voltage conversion, fault isolation, power factor correction, frequency regulation, harmonics control, and phase balancing into a single programmable package managed in real time by software.

This means you replace not only the transformer, but the switchgear, tap changers, and capacitor banks as well.

The SST market is still in its infancy. It’s valued ~$180M as at 2025 but the technology is moving faster than I think most realize.

—> Eaton (ETN) acquired SST developer Resilient Power Systems in August 2025.

—> Navitas (NVTS) demonstrated a 250kW SST at APEC in 2026.

—> Wolfspeed (WOLF) launched the industry’s first commercially available 10,000-volt SiC MOSFET (the enabling technology for SST) in 2026.

Here’s the names you need to know in the SST space:

Wolfspeed | WOLF | $430M

WOLF is the most important name in the SST SiC layer. It’s the US pioneer of silicon carbide…Here’s what a professor from Duke said:

“The timing of WOLF’s commercialisation could not be better. The world is racing to connect AI data centers to the grid, and this will be the enabling technology.” - Dr Subhashish Bhattacharya

This still remains a very high-risk and investment stories aren’t just a play on technology. WOLF’s financials are pretty poor with net income rising, huge debt, and a lot of dilution.

WOLF just issued $379M in convertible notes with is dilutive at $20.14 per share meaning if WOLF trades above $20.14 at any point before 2031, noteholders can convert into equity. The other side to this is that proceeds are being used to redeem existing senior notes…making this more of a debt refinancing rather than a cash raise for continued operations.

It’s a messy capital structure, and a high-risk bet, but I think the reward is there assuming execution. It’s one of those speculative bets I’d be happy to take but position accordingly.

Navitas Semiconductor | NVTS | $2B

NVTS is probably the purest play on the SST thesis today and the financials also look far more solid than WOLF (though the competitive environment is worse), although the stock has moved 450% in the last year alone. That tends to be quite off-putting for some investors, me included, but the thesis is so intact for NVTS here.

Two very important quotes from the recent earnings call:

“You’re going to see first couple of megawatt SSTs, bundled with battery energy systems. Then you see high single-digit megawatt type of SSTs coming up.”

“You cannot deploy remotely half of what we’re trying to deploy with AI data centers with the grid we have today. So for me, AI data center and grid is the same thing.”

Despite the competitive environment being a challenge for NVTS, most competitors are either pure GaN or pure SiC. NVTS has both.

The part I’m slightly cautious about with NVTS is the lack of transparency around profitability timeline. Analysts currently aren’t estimating EBITDA profitability anytime in the next 3-4 years and management haven’t given any specific timeline so this is certainly something to be wary off.

Bottleneck 2: Grain-Oriented Electrical Steel (GOES)

This one is quite multi-faceted.

Grain-oriented electrical steel is the critical raw material used in most transformers. It’s a silicon steel alloy rolled and heat-treated which gives it very strong magnetic properties. Without it, you can’t build a power transformer.

And the vast majority of supply is controlled by a single US producer - Cleveland-Cliffs (CLF).

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The SPY had its worst week since the start of the Iran war down 2.2% over the last week making this its 5th straight weekly close and now ~8.7% above from highs. More importantly, the SPY reaffirmed its position under the 200 daily this week and looks to be now heading towards the next key level which is the 100 weekly at 608 (another 4.1% decline from here).

I’ve said it over and over again…people have been calling “buy the dip” for the last few weeks but completely ignoring the SPY structure. When the SPY isn’t holding any form of bullish structure, you have to be a bit more cautious. It’s why I’ve held off buying individual names (aside from my regular DCAs) for ~7 weeks now despite some of those individual names I’m interested in being at levels I thought were cheap. They’re all now much lower. That’s why taking into account the index structure is very important…and it’s what I’ve been telling subscribers on a daily basis for the last few weeks.

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On the contrary, I do feel as though we are now much close to deploying cash than many perhaps fear. We’re now at what feels like peak uncertainty and peak fear and whether the war continues or not for 1 weeks, 1 month, or 6 months, I think the market is getting close to pricing in that peak fear.

I’m sitting on ~17% cash now and have been for quite a while. That’s a healthy cash position with continued healthy long exposure. I’m ready to deploy that cash into a handful of names whenever necessary and I suspect that time will come fairly soon.

Before we get into my 3 ideas for the week, take a look at my March database and portfolio. You get:

• Portfolio (real monetary amounts with 100% transparency)

• Watchlist

• Theme tracker

• Valuation models

• 10+ themes with stocks per theme measured by valuation

• Daily notes in the paid chat

• 1 video chart review per week

I also want to give an example of one of the many tabs within my portfolio. Here’s the optics tab:

I created this back in December 2025 before LITE and AAOI had their massive runs. It gives you a list of all the stocks within the theme measured by revenue and growth rates relative to multiples and also combines that with where the stock is trading technically vs key MA’s.

As you can see, LITE, VIAV, CIEN, and MRVL are still currently showing as very bullish. Outside of CRDO which I currently own, I think MRVL is my next favorite.

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Here’s what I wrote last week about COPX, TMQ, LEU, SANM, and OUST. All held up very nicely over the week (aside from OUST).

I still believe these are all at nice levels today.

Let’s get into my ideas for this week👇

Lower Risk

There’s one theme very few are talking about, but it’s one I have mentioned quite consistently in my paid chat for the last two months….chemicals.

Chemicals sit at the intersection of the defensive macro and the offensive AI.

On the “safer” side, a lot of chemical demand is anchored to must-have end markets like autos, energy, defense, and infrastructure. That means volumes are tied to government spending, reshoring, and basic economic activity rather than just hype cycles. And then when you layer in the fact that many chemical prices are fairly well tied to oil and gas prices you have a theme that is quite nicely a more defensive play on the Middle East tensions.

At the same time, chemicals are a huge beneficiary of the AI buildout. Here’s a post I put out on X on March 2nd 2026 for example.

Every AI data center, and every chip fab is essentially a huge chemical consumer. They need specialty gases, advanced polymers, high purity solvents, coolants etc. So the big thematic is that as AI infrastructure scales, there’s a clear secular demand for chemistries that enable more servers, more chips, and more thermal management.

In other words, the chemicals industry is no longer just an “old economy” trade.

My favorite plays here are:

1. Celanese | CE: CE uses thermally conductive plastics (called CoolPoly) to replace metal as a coolant. It’s mainly used in data centers, 5G equipment, LED lighting, and high speed connectors where high power density and tighter packaging is needed. CE trade at 9x FCF for ~10% CAGR in FCF for the next 3 years.

2. Entegris | ENTG: ENTG sells the ultra-pure chemistries and materials that lets fabs run at scale. It’s the cleanest play on every incremental wafer and layer of complexity driving more contamination control, and more content per too. ENTG is far pricier than CE at 39x FCF but if there’s a continued chemicals bull market I see upside here as well.

Medium Risk

The Iran war has so far wiped out ~30% off the global mining industry’s value. I was an owner of Silvercorp Metals (SVM) which I full sold out off (see screenshot) a month ago for ~210% gain today.

Since then, we’ve seen even the big players like Rio Tinto (RIO) drop 12% over the month and Newmont (NEM) down 17% over the last month. SVM is down 18% as well.

Despite this selloff, critical minerals remain vital for defense and we’re seeing an ongoing supply deficit for many of these critical materials. Paid subs will know that I just opened up a position in a sub $1B scandium play just last week. I view scandium as potentially having the next copper like move.

From a broader thematic angle, if you’re bullish on the following themes:

• Power grid upgrade

• Robotics

• Defense

• AI infrastructure buildout

• Electrification

Then you have to be bullish on the mining industries which sits at the core of all of these themes. We have surging demand in pretty much all critical metals (some more than others) and quite a clear supply deficit. There’s no need to overcomplicate the result of this over a 5-10 year period.

Here’s the critical metals I am following most closely so far. I’m not going to give specific mining stocks in this free release as I’ll leave that for paid subs, but this list is a good start for you if you don’t want to become a paid sub:

• Copper

• Scandium

• Rhenium

• Hafnium

• Lithium

• Gallium

Higher Risk

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I’m not sure how useful that has been as ultimately the narrative is changing hourly, and today has been no different. Futures opened very red, only for the market to open up green. At one point today the SPY was up +2% and then we closed +1%. Another green day amongst what is likely continued red days.

As much as today has seen some more positive narrative, I still am playing a very rules-based approach. We’re still below the 200 daily. We’re still below the 663 level. We’re still sitting on the sidelines as this chop continues.

It seems boring to do, but most people either:

• Get bored and overtrade in an environment where they have no edge.

• Get scared of a choppy market and chase defensive plays like oil which have already moved huge amounts.

Your best bet now is sitting on your hands until we have more clarity.

Personally, I feel good. I have a nice cash pile and I have nice long exposure. There’s absolutely no need for me to rush into any trade right now.

Here’s what I wrote last week. I spoke about ITRI, LEU, and MELI.

Before we get into my 3 ideas for the week, take a look at my March database and portfolio. You get:

• Portfolio (real monetary amounts with 100% transparency)

• Watchlist

• Theme tracker

• Valuation models

• 10+ themes with stocks per theme measured by valuation

• Daily notes in the paid chat

• 1 video chart review per week

I also want to give an example of one of the many tabs within my portfolio. Here’s the optics tab:

I created this back in December 2025 before LITE and AAOI had their massive runs. It gives you a list of all the stocks within the theme measured by revenue and growth rates relative to multiples and also combines that with where the stock is trading technically vs key MA’s.

As you can see, LITE, VIAV, CIEN, and MRVL are still currently showing as very bullish. Outside of CRDO which I currently own, I think MRVL is my next favorite.

Lower Risk

As paid subs know, I own two copper plays that I have been DCA’ing into for ~2 months now. COPX is one of them and TMQ is the other. TMQ is a far higher risk play, but COPX is a general play on the copper market.

COPX is now down ~23% from highs on January 30th 2026 because of a potential higher inflation number combined with weaker output and a stickier central bank policy. All of this is ultimately bad news for metals like copper which is considered less of a safe haven metal.

Zooming out, this move is purely macro driven. The supply-demand gap is still real and I will continue to DCA into copper plays.

Here’s a reminder of the structural copper bull case:

We still have what appears to be a huge demand running against a very real supply constraint. There are very few mines coming online and major copper discoveries have been pretty limited for a few years now. When you add on the fact that several large mines are fighting weaker quality and more complex operational challenges…the simple case is that the world is not prepared at all for the huge step up in demand that is coming.

“Copper is a pretty simple story…it takes about 12 years, greenfield, to produce copper, and you got EVs, the grid, data centers, and believe it or not munitions…we just think the supply-demand situation is incredible for the next five or six years.” - Stanley Druckenmiller

"Copper is the new oil…there’s no decarbonization without copper. There is a long term supply gap of 8.2 million tonnes by 2030, twice the size of the gap that triggered the bull market in copper in early 2000s.” - Goldman Sachs

Here’s comes a slightly more interesting angle to invest in the theme though, and one that I wouldn’t include in the “Lower Risk” sector but one that slides in perfectly below that copper piece.

Look how similar this chart looks to COPX.

This is MSCI Chile Index which moves quite in line with copper though has historically slightly lagged which could potentially lead to a play on copper and a nice catch up play as well. ECH has moved 28% in the last year whilst COPX has moved 76%.

Medium Risk

Last week I spoke about LEU for my neutral risk play. That one remains very high on my list to consider but I’m going to introduce a new name today… SANM.

SANM isn’t a very well-known stock, but the numbers and bottleneck they solve seem too good to ignore for me as EBITDA ramps up in FY26 post ZT Systems acquisition which should double SANM revenue in the next 2 years to reach ~$16B in FY27. That ultimately means SANM is trading at ~0.46x FY27 revenue whilst set to (inorganically) grow revenues by over 100% in 2 years.

That’s why the numbers make sense. Now let me explain the business.

SANM is a highly complex electronic manufacturing services (EMS) company that solves a lot of bottlenecks in today’s compute and power stack. The main bottleneck they solve is PCB boards. These are essentially the backbone of any electrical system.

It’s a flat insulating board (fiberglass + copper) that is where the chips, connectors, and all other components sit. As electronic systems have got more and more complex, there’s been fewer and fewer companies that are able to serve this bottleneck. SANM designed PCB boards with 60-80+ layers with high aspect ratios and they do so reliably at scale… and yet they trade at less than 0.5x NTM sales and less than 7.5x NTM EBITDA.

Here at $131 the technicals also look really nice right at the 200 daily and I think we see a move back up to ~$160 as long as the wider market holds up which isn’t clear right now.

Higher Risk

OUST is my higher risk play right now. Fundamentally, I think OUST is one of the better plays on the next 5-10 years of the physical AI megatheme.

Technically, we’re still sitting below the 200 daily, the 100 daily, and below the key $21.50 level so until we break those levels I think the risk is slightly higher.

You can see my OUST deep dive here:

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Not Investment Advice

Company Name: Ouster

Ticker: OUST

Market Cap: $1.34B

Headquarters: San Francisco

Shares Outstanding: 62M

CEO: Angus Pacala

Revenue Growth: 52.5%

Introduction

The vast majority of my ideas stem from identifying megatrends, finding the quality companies within those themes, figuring out what is a fair valuation for that business, and then finding a nice technical entry for that position.

This is a perfect example of how I first initiated my position in OUST.

I dived into the basic numbers in my database for robotics, I then spent hours diving into the company and the valuation, and then I tracked price closely to find a nice first entry.

OUST is now sitting slightly below my initial $25 entry at $21. It’s now at a level where I feel extremely comfortable going bigger on the position.

Just like I did with LMND in the $30s, SOFI below $10, PLTR below $40, SVM below $3, ALB below $80, AMPX below $12… and so on.

The only difference with OUST currently is that it has yet to make its move.

Big picture, my view is that OUST is positioned perfectly in the middle of the robotics and automation megatheme. More specifically it’s in the sensory & perception subtheme of this basket. Here’s a snippet of my database which my paid subs have access to.

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As you can see other players in this niche (though not competitors to OUST) are AEVA, CGNX, INVZ, TEL, APH etc. My database tracks multiples, expected growth rates, and technicals like MA’s to give an initial recommendation of the stock and its valuation.

It screens out all of those positions that likely are too expensive, or with too slow growth right away for you allowing you to focus your time on those quality stocks.

For example, in the sensory and perception niche, the best names are OUST, HSAI, TEL, and APH.

Just within the robotics tab alone, we have +140 stocks broken down in subthemes within the wider theme.

Paid subs will know that I already have a position in OUST at $25 which makes it my biggest pure robotics play (if you exclude NVDA and GXO). I’m currently down 15% on the position but with the robotics megatheme likely to be a +10 year theme, I’m fully prepared to own this one for the next few years unless anything materially changes within the business.

In this Deep Dive, I’ll cover the following:

1. What OUST does

2. Recent financials

3. Opportunities

4. Valuation

5. Technicals

6. My take and plan

What does OUST do?

OUST is the largest Western LiDAR provider (Light Detection & Ranging). LiDAR is a remote sensing technology that measures distance by emitting short pulses of laser light at objects and calculating how long it takes for the reflected light to return. It then converts that time into precise 3D distance and position information.

It’s basically the eyes of a robot, or the eyes of machines that need to move autonomously.

OUST’s differentiation is that they’re a digital LiDAR company.

Traditional LiDAR is analog meaning you fire a laser, swipe it mechanically, capture returning photons, and then reconstruct a 3D point load with a lot of complexity. Each new product generation must mean a new optical design and a new assembly process.

Digital LiDAR on the other hand is the idea of putting the complexity of LiDAR technology onto a silicon chip. Key functions of the sensor (photon detection, timing, signal processing etc) all are implemented in custom semiconductor chips rather than bulky analog assemblies. Here’s why this matters:

• This allows OUST’s products to ride the Moore’s Law wave with performance. This means that OUST’s technology improves exponentially like other semiconductor products have done over the last 3-5 years.

• Digital LiDAR is also designed to follow the semiconductor cost curve, i.e. OUST can make smaller sensors that are more power efficient and have better performance.

I can’t write this Deep Dive without acknowledging LiDAR’s biggest bear… Elon Musk.

Here’s a summary of Musk’s argument:

• Cost: Musk says LiDAR adds an expensive and unnecessary sensor to vehicles when cameras can achieve autonomy at a fraction of the cost.

• Weather sensitivity: He claims LiDAR performance is poor in rain, fog, and snow so it’s not fundamentally robust.

• Power requirements: He claims LiDAR has far higher power requirements and system complexity.

An “unnecessary, expensive appendices.” - Elon Musk

Whether you agreed with Musk or not, the risk of LiDAR not fulfilling the expected forecasts has been mitigated quite a lot post 4th February 2026 OUST’s acquisition of StereoLabs - a leading AI vision and stereo-camera company.

OUST paid $35M in cash and 1.8M OUST shares (vesting over 4 years) for the company. I’ll dive into the expected numbers of this acquisition in the valuation section but fundamentally here’s why this acquisition will work so well.

Overnight, OUST went from a LiDAR company (with risks as Musk claims) to a LiDAR + camera + AI vision software company.

This repositions them as the leading Physical AI sensing and perception platform…rather than the leading LiDAR company. The market is still underappreciating this transition as the stock is flat since the news. This OUST stack now includes:

1. High performance digital LiDAR

2. Stereo cameras and depth cameras (ZED line)

3. AI compute and sensor-fusion middleware

4. Perception software and AI models that detect, classify, and track objects in 3D.

OUST can now sell a full perception layer to customers rather than selling LiDAR / sensors into someone else autonomy stack. Financially, it also allows OUST to work towards higher margin, recurring, software revenue on top of their hardware sales. Most one-off sales hardware companies struggle to ever get rewarded with strong multiples like recurring revenue software companies do.

“This acquisition builds on Ousters momentum and positions us as the foundational end-to-end sensing and perception platform for Physical AI.” - CEO Angus Pacala

If customers want more vision and less LiDAR, OUST can still participate. If customers decide they want more LiDAR and less vision, OUST can still participate.

Financials

Demand

• Q4 25 Revenue: $62M

  • $41M was product revenue and $21M royalties (primarily one-tme).

  • Product revenue growth was +36% YoY in Q4 and full year revenue growth was 52% YoY (or 32% excluding royalties).

• 2025 full units: 25,000 sensors shipped which is +48% YoY

Industrials was the largest contributor to revenue, followed by robotics and smart infrastructure.

Software is now on ~15% of sensors shipped which is a 120% increase in software attached sensors relative to last year.

Profitability

• Q4 GAAP Gross Margin: 60% with 20 pts from royalties which implies a 40% ex-royalty margin.

• Full year 2025 Gross Margin: 49% with 8 pts from royalties implying 41% ex-royalty.

• Full year OpEx: $157M (+9% YoY)

  • This increase relates to investment in the roadmap, StereoLabs costs, compliance etc).

• Q4 25 adjusted EBITDA: +$11M (mainly because of royalties). Full year Adj. EBITDA was negative $12M (vs negative $42M in FY24).

  • Analysts expect EBITDA profitability in FY28.

Guidance

• Q1 26 revenue guidance: $45-48M which includes ~7 weeks of StereoLabs contribution.

• Long term financial framework reiterated 30-50% annual revenue growth with 35-40% GAAP gross margins.

• Management expect growth and operating leverage to provide a “clear path” to positive operating FCF and profitability with “plenty of operating runway.”

Balance Sheet

• Q4 25 cash position: $211M (note this is pre StereoLabs)

  • StereoLabs acquisition led to a $35M cash outlay (plus stock)

• Debt: $0

Opportunities

Total Addressable Market (TAM)

OUST management have consistently said $70B is their TAM. This has been the case for the last 18 months or so. With OUST expected to do $220M in revenue in FY26, that means OUST has currently won 0.314% of the opportunity right now.

This kind of TAM reminds me of companies like LMND, PLTR, SOFI etc with almost unlimited growth ahead.

But here’s where it gets more interesting for me. All of this $70B commentary came pre StereoLabs acquisition. StereoLabs is a small business today, but it’s very meaningful in terms of the value add it offers.

The stereo-camera / 3D camera market that StereoLabs operates in is a $2.5B market but the software and perception layer that this acquisition adds probably puts the TAM far above $70B in the long term. I won’t put a forecast out there for what I think the TAM likely is as it’ll but no more than an educated guess, but I suspect it adds far more than just a few billion dollars to the market OUST can win.

More importantly, in the short term it should increase OUST’s share of the wallet within the existing $70B Physical AI stack.

Many investors still label OUST as a “auto LiDAR” play. Let’s dive into how far off this narrative is:

1. Industrial LiDAR is OUST’s biggest (or 2nd largest) segment today and management peg it at a $18-19B opportunity by 2030. This opportunity encompasses the heavy machinery plays like AGVs/AMRs in warehouses, ports, mining trucks, construction, and agricultural equipment (John Deere for example). Current industrial revenue is in the tens of millions range within the $169M 2025 revenue. This implies far below sub 1% penetration in a market that is set to move from R&D to production very quickly. I’ve said this about my bullishness on GXO, but this subtheme within Physical AI is very likely to be the niche that moves first. This is the theme that is in the most repeating and stable environment in a relatively constrained labour market. In agriculture, this is exaggerated even more.

2. Humanoids is OUSTs small, but emerging opportunity. OUST’s customers include Serve Robotics (SERV) for example but this will likely take a lot more time to materially affect the numbers. But if you’re aware of the forecasts someone like Elon Musk has put out for the humanoid market, then ignoring OUST’s potential here is naive. This is where OUST’s management team have been very intelligent. OUST could have easily been grouped into the AV and humanoid niche like many other LiDAR providers. The timeline on these subthemes is still very unclear and likely will be quite unclear for the next 2+ years or so. If that were the case, then I would understand OUST’s valuation here at $1.2B market cap a bit more, but OUST has industrial and smart infrastructure scaling quite rapidly now.

3. Smart infrastructure is OUST’s largest or second largest segment today with an estimated $19B TAM. This spans traffic management, security, spatial analytics for example. Gemini and BlueCity have been the most important contributors in this segment for OUST not only for material revenue today, but also because software attached bookings have more than doubled here. Contract developments for BlueCity and Gemini now exceed 1,200 sites worldwide. A lot of this opportunity depends on if LiDAR based detection becomes a standard for intersections, public spaces, and private campuses but if it does the TAM will likely be much larger than $19B. Ultimately, we’ve seen through Gemini and BlueCity that the market is looking for full stack solutions. Not many enterprises want pure components now since it becomes too complex to integrate everything. There’s already evidence in the software attached sales that OUST are strong here and it’s only the very early days.

4. Automotive is the other smallest revenue contributor (single digit percentage) today but a huge piece of the long-term value. Most of the reason this revenue is quite slim today is because programs are largely in pre-production even more so than in the other segments. Robotrucking is a multi-billion dollar ($70B+) opportunity itself with the LiDAR specific part of that likely well above $1B. For OUST today, it’s mainly small R&D and pilot revenue, but once autonomy on the roads becomes a lot more common, these small wins so far can flip into a huge amount of units sold.

I think it’s clear that OUST is a diversified and proven business so far, and it’s still in the very early innings. They’re selling into 150+ use case across four key verticals whilst LiDAR peers generate little revenue on negative margins in one or two segments max whilst they wait for one or two OEMs to ramp up.

For example:

• Hesai (China): Extremely concentrated in automotive and robotaxis. It’s essentially a one-theme bet on Chinese AV adoption.

• RoboSense (China): Extremely concentrated bet on robotics. Another one-theme bet.

• Innoviz (US): Extremely concentrated bet on automotive market.

There’s no other LiDAR player that is anywhere near as diversified, with such strong margins, that is investing into the entire Physical AI perception stack like OUST.

This mismatch between current revenue and segment specific TAM alone should give you a pretty good read on where OUST is likely to head. OUST is already embedded across those niches so the 2030 outlook is not whether there’s room for OUST to grow, or how much they have to win, but it’s how fast those deployments and those markets scale from R&D (hundreds and thousands of units) to full production (tens to hundreds of thousands of units).

Financials

• Growth Rates: OUST management has given us a reasonable way to look out to 2030. I’ll dive into this a lot more in the valuation section, but with 30-50% annual revenue growth we can quite easily hit $700M in revenue by 2030 (absolute base case), and much more likely we hit $850-$950M.

• Profitability: OUST management have consistently said that GAAP gross margin will be in the 35-40% range. You’ll note that Q4 25 gross margin came in higher but this was artificially boosted by high margin royalty revenue. This is why the market didn’t react a lot. Firstly, I think 35-40% is the absolute base case. There’s clear potential that post StereoLabs and the mix towards higher margin recurring revenue should create more upside than perhaps management are forecasting (publicly). In the near term though, my models are assume ~40% gross margins. The main reason 40% gross margin is likely for the next few years is because as customers go into volume production, unit prices from OUST will drop. It’s healthy/necessary to ensure that OUST win large unit contracts but it’s also a headwind for margins. It will be the main offset to cost controls and software integration which are margin expanders.

OUST management are clear they will happily trade some gross margin for a 10x increase in volume. As an investor, with a TAM the size of $70B, going after margins and profitability as a $1.2B company would be massively off-putting.

If the opportunity wasn’t so large, then sure, it’s arguably just as important to focus on profits as soon as possible, but OUST management know the space they’re trying to win. There’s no point sacrificing a huge ramp up in revenue for a few bps on gross margin today.

Edge AI Upside

If you look at exactly the roadmap that has happened with cameras you’ll note the first phase is always raw imaging, specs, resolution, low-light performance etc… just as LiDAR is today with range, points per second, and cleaner point clouds for example.

Now leaders like Hikvision, and i-PRO are shipping cameras with embedded NVDA chips that run AI models on the edge. This object classification is happening in the camera itself rather than on a backend server.

For OUST, the opportunity is to make LiDAR run the same playbook over the next few years and capture the huge value shift that will happen when intelligence moves into the sensor (i.e. at the Edge). If LiDAR follows the same camera-style evolution that we’ve seen, OUST’s digital LiDAR chip, and it’s full stack physical AI perception profile, will be a ginormous market.

NVDA Partnership

NVIDIA is becoming the de facto compute standard for robotics, automotive, and industrial AI – and Ouster is wiring itself directly into that ecosystem. When an OEM picks an NVIDIA platform like Jetson or Isaac, they effectively lock in a 3–5 year roadmap: they build and validate their perception and control stack around that compute, then roll it out across product lines. Ouster is doing the same thing on the sensing side. Customers choose Ouster’s digital LiDAR, perception software, and datasets, then spend years integrating, validating, and hardening that stack in parallel with NVIDIA’s platforms.

The result is that Ouster ends up embedded alongside NVIDIA in long‑lived deployments. Strategically, Ouster is making sure this scales horizontally: DRIVE and ADAS for autonomy, Jetson for edge robotics, Isaac and Omniverse for simulation and digital twins. As long as Ouster’s sensors are natively supported, well‑documented, and easy to use inside these NVIDIA toolchains, it can position itself as the default 3D sensing option for developers and OEMs who are already all‑in on NVIDIA. Being “the LiDAR that just works with NVIDIA” is a very attractive place to sit.

The economics for Ouster are straightforward. On the growth side, NVIDIA is plugged into almost every high‑growth segment of Physical AI – from warehouse robots and industrial arms to AMRs, drones, construction equipment, and autonomous vehicles – and Jensen is on record saying they’re working with essentially every robotics company they know. If Ouster consistently ships the LiDAR and perception stack that rides shotgun with Jetson and Isaac into those designs, it effectively surfs the same demand wave. On the retention side, every new application built on NVIDIA + Ouster increases the customer’s sunk cost in Ouster’s data formats, calibration, models, and integration code. You don’t casually rip out that sensor and swap it for a competitor without redoing years of engineering and validation.

Put differently: NVIDIA provides the gravitational pull on the compute side; Ouster supplies the LiDAR and 3D perception that click into that gravity well when depth sensing is required. If a developer standardized on NVIDIA can also standardize on Ouster with minimal friction, you get exactly what long‑duration investors want to see – more growth, more retention, and increasingly durable attachment of Ouster’s sensors and software to the winning Physical AI compute stack.

US Manufacturing

One underappreciated opportunity for OUST is how well it positioned itself to line up with the current US onshoring and secure supply chain. They’ve proactively shifted manufacturing outside of China and de-risked themselves here. Whilst Chinese leaders like Hesai and RoboSense will undoubtedly dominate the Chinese auto and robotics markets, Western OEM’s, defense primes, and infrastructure operators will be encouraged (in some cases obliged) to source from Western providers like OUST.

Valuation

Here’s where it all ultimately matters. There’s no point buying a quality business if the valuation doesn’t make sense.

For OUST it makes complete sense. Here’s why and here’s my 2030 prediction.

I’m looking at this valuation a few different ways.

1. Relative to LiDAR peers

2. Relative to perception/physical AI peers

3. Model through to 2030

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It’s now week three of the war and I still can’t see much that evidences this is coming to an end. Just a few hours ago, Trump said he is considering putting boots on the ground to seize Iran’s Kharg Island. Here’s some more details on it:

• This will likely only happen if tankers remain stuck in the Persian Gulf.

• Kharg Island has 90% of Iran’s oil production.

• Trump is working to assemble a coalition of countries to reopen the Strait of Hormuz.

All in all, it still appears that there’s tons of unknowns and it’s very difficult to gauge how close to the end we are.

One positive we have taken over the last few hours is BTC now up ~$74,000 again whilst oil prices are staying slightly below $100. It’s nothing to scream home about, but it could be a little positive to take into another volatile week. Maybe the worst is behind us.

It looks quite clear now we’re heading towards the 200 daily. The question now is just whether this is an October 2025 style pullback or a Feb-April 2025 style pullback.

Price action on the SPY looks pretty bad right now, but the macro reasons behind this could change in a day. On the QQQ, it looks like tech had it’s pullback and so far we’re holding structure here, but a break of this 595 and 200 daily MA here will be the key focus this week (again).

Before we get into my 3 ideas for the week, take a look at my March database and portfolio. You get:

• Portfolio (real monetary amounts with 100% transparency)

• Watchlist

• Theme tracker

• Valuation models

• 10+ themes with stocks per theme measured by valuation

• Daily notes in the paid chat

• 1 video chart review per week

I also want to give an example of one of the many tabs within my portfolio. Here’s the optics tab:

I created this back in December 2025 before LITE and AAOI had their massive runs. It gives you a list of all the stocks within the theme measured by revenue and growth rates relative to multiples and also combines that with where the stock is trading technically vs key MA’s.

As you can see, LITE, VIAV, CIEN, and MRVL are still currently showing as very bullish. Outside of CRDO which I currently own, I think MRVL is my next favorite.

The reason I give access to all this data (and this tab is one of 10+ right now) is because I know we all invest in different ways. I offer complete transparency to my portfolio and my watchlist but I also offer you this extra benefit.

Stock picks are everywhere now. Having access to a nice quick screen is just an added benefit.

Another positive I am trying to take from the market at the moment is that we are seeing some pockets of strength here and there. It’s not a complete market sell off.

• CRCL has moved +100% in a month.

• HIMS is now +44% in a month.

• BE is holding up ~530% over the last year.

• LWLG has moved +77% in the last week.

Here’s a snippet from the spreadsheet. It shows prices per theme over the last week.

It seems like the last week still has very weak sentiment, still lots of selling pressure, but the market seems to be holding up a bit better than I perhaps expected for the most part given this. I feel like we’re edging towards a market where buying this dip is going to be the right play, but I need far more confirmation that a gut feeling like that.

I will continue to watch price action across a few key names and indexes and as soon as I see a bit more strength, I will likely start deploying some of my cash pile (~16% of portfolio).

SKEW Index

This shows perceived risk has decreased slightly relative to last week. SKEW measures how deep out of the money puts are vs at the money options on the SPY. 137 is still on the higher end but it’s been +130 since April’s crash. Look at April’s bottom ~125. We’re nowhere near there but the perceived risk compared to 158 last week is another more positive sign to take.

We also have NVDA’s premier conference this week… NVDA GTC.

This tends to be the biggest AI conference of the year where all the leading minds come together to discuss the next wave of AI. Hopefully it acts as a little reminder to the market that we’re still in the very early days of this AI buildout.

Defensive/Lower Risk Idea

XLU & ITRI

I never like to “re-run” ideas in consecutive weeks, but doing so also shows my conviction in the theme. I’ve now chosen XLU (S&P 500 Utilities Sector ETF) as my more defensive play for 3 out of the last 4 weeks.

This is the 1 hour chart but you can see it’s so far held up very nicely despite wider market fear. That’s a nice sign. But XLU isn’t just a pick I like to manage volatility…it’s a pick I like to outperform for the next 2+ years and my individual pick on that is ITRI.

Paid subs will know that I’ve spoken about ITRI a lot recently but have only put a small starter position amount of money into the stock right now. This $90 level that I have charted out is extremely key to hold here.

ITRI builds the smart meters and grid-edge hardware and software that lets utilities turn an aged, and overloaded grid into a data-driven network. There’s no modernisation of the grid without ITRI. It also now trades near it’s all-time low PE as the market focuses on the other key players like ETN, PWR, and HUBB. I think ITRI is next to run.

“This isn’t an if. It’s inevitable… It’s the way our customers need to cope with the world around them and the complexity of the environment that they operate in.” - ITRI CEO

“With more than $1 billion of durable Outcomes backlog, rapidly growing annual recurring revenue and expanding solutions for critical customer problems, Itron is well positioned for the multiyear grid build‑out in the years ahead.” - ITRO CEO

This isn’t the time for an ITRI deep dive…it’s more of an introductory idea. If ITRI becomes a top 10 play for me, then I will most definitely do a deep dive on the business.

In the meantime, I have my OUST deep dive coming out in the next 24 hours.

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Neutral Risk

Last week I spoke about SOFI, HROW, and NBIS as my neutral risk ideas and I still think they’re arguably some of the best choices. I won’t repeat my narrative on them today but you can view it right here.

For today, I’ll discuss another idea to save repetition - LEU.

I personally have no position in LEU yet but it’s probably in my top 5 buys as soon as I start deploying cash. It remains still below the 200 and 100 daily MA’s but it has reclaimed the 21 daily.

People underestimate the importance of LEU. It’s effectively the missing middle of the Western nuclear value chain. It doesn’t mine uranium, but it enriches it, and it’s the only Western company that actively produces enriched uranium right now.

Most next gen reactors (SMR’s) which I am very bullish on through my position in NuScale (SMR) need enriched uranium between 5-20%. Most nuclear plants today use low-enriched uranium ~3%. Currently, the US relies heavily on Russia for enriched uranium but this isn’t sustainable at all in the nuclear cycle we’re entering.

LEU currently sits at $2.3B backlog and a multi-billion dollar enrichment expansion plan targeting commercial enriched uranium. Add on the fact that the government is committing $2.7B in domestic enrichment explicitly aimed at reducing dependency on Russia, and you have quite a clear long term bull case.

The next step is just figuring out if there’s value or not which is hard for a company like LEU.

Here’s the way I’m looking at this valuation at $209:

Mid case revenue estimates are ~$650M in revenue in FY28 with $121M in net income. I know the above chart gives $495 in revenue, but I think that’s a data issue and a clear anomaly. LEU currently trades at 59x NTM PE which sounds pricey but when you’re growing net income ~28%, with long-dated contracts, US government support, and a huge backlog it doesn’t seem too high.

FWIW, CEG has historically traded at ~30x NTM PE and I think LEU should trade at a higher multiple based on:

• CEG’s economics rely on power prices, capacity auctions, and regulatory decisions. It’s why we’ve seen a massive sell off in CEG lately.

• LEU sells the specialized fuel into a capacity constrained market where there’s very few (if any) alternatives. That is a moat that deserves a higher PE. LEU has more pricing power and less reliance on commodity prices.

So, if we conservatively give LUE a 35-40x PE multiple on $120M in net income you have ~$4.8B valuation in FY28 which is higher than today and in my opinion that is based on a very conservative PE multiple. Let’s see. I am still not an owner of LEU, but I likely will be quite soon.

Higher Risk

Last week I spoke about IRDM and OUST. OUST I currently own… IRDM I am hoping to own but it’s at a very key technical level that I am watching closely.

Today, I’m adding one more stock in there that I think is great value today.

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