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The debate around this VMS holdings ecosystem has shifted quickly and furiously recently. A year ago, most of the conversation started to fly around AI disruption, Software disintermediation and whether LLMs would eat into the moat of niche, mission-critical vertical market software. I’ve written about this extensively in my Software Darwinism series, and I don’t think the disruption thesis holds up well under scrutiny. So I won’t revisit it here.

What I do think deserves more attention (and curiously isn’t getting it) is a different question altogether: where does each entity in the CSU ecosystem sit within its own lifecycle, and what should incremental capital realistically expect to earn from here? This matters far more to long-term IRR and it’s what I want to work through today.

For those new here, the three names I’m referring to are Constellation Software (CSU), Topicus (TOI), and Lumine (LMN). The three heads of the empire that Mark Leonard 🧙🏻‍♂️ has spent 30 years building through an elegant and endlessly repeatable playbook: acquire niche, mission-critical software businesses at disciplined multiples, operate them for cash flow, and redeploy that cash flow into more acquisitions.

The model works and that part is already settled as long as the system and culture remain intact after the heartbreaking Mark Leonard’s departure (sigh). The more interesting question now is which of the three vehicles gives you the best return on incremental capital from today’s entry point and why the pecking order matters.

Before I rank them, I want to ground the conversation in the structural forces that make this complex worth owning in the first place:

• The digitalization of public sector and SME operators is still early in many geographies. The UN reported that the share of the global population lagging in digital government adoption dropped from 45% in 2022 to 22.4% in 2024, a two-year move, and not one that reverses. For Topicus specifically, this is directly relevant. European healthcare, education, and local government software customers are still in relatively early innings of their digitalization cycle, which goes a long way toward explaining why Topicus’ organic growth is running 200–300 basis points above the parent.

• The founder succession pipeline is expanding, not shrinking. The global VMS landscape is populated by tens of thousands of founder-led niche software businesses generating between $1M and $50M in revenue. The baby boomer generation of software entrepreneurs is retiring, and that pipeline of acquisition targets is opening up, particularly in geographies that CSU and Topicus have only recently begun to penetrate. CSU has already acquired over 1500 businesses serving 250 000 customers across more than 100 countries, and the sourcing machine shows no signs of running dry.

• AI-driven margin enhancement within portfolio companies has potential. I want to be careful here because this one gets hand-waved a lot. AI tooling embedded into VMS products will not suddenly push organic growth to 15%. My realistic version of this thesis is that AI supports modest price increases and improves retention in segments where the software is already sticky. For a business running at 2–5% organic growth, even a 100 basis point improvement compounds meaningfully over a decade. That is worth acknowledging, but it shouldn’t be the load-bearing pillar of any investment thesis.

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Topicus: The Most Interesting Risk/Reward

I don’t think the organic growth differential between Topicus and CSU gets nearly enough attention. Topicus is posting roughly 5-6% organic growth versus the parent’s approximately 2-3%.

That gap does not sound as much until you think about it more carefully: Topicus’s existing portfolio companies are operating in markets where the digitalization cycle is earlier, horizontal SaaS competition is lower, and pricing power has more room to run. That seems to me like a structural difference, but the market does not seem to be giving it much credit though; which is, in my view, one of the better mispricing opportunities in the ecosystem right now.

The geographic runway is, to my mind, the most visible and least-priced-in optionality in the entire CSU complex. CSU’s North American VMS market is mature. Bid competition for targets is real, multiples have crept up (although SaaS-mageddon is reverting that trend), and the law of large numbers is obvious at this point (more on this later).

And Topicus’ geographic expansion has become one of the most compelling parts of the investment case.

For years, the company steadily expanded beyond its Dutch roots into the rest of Europe, with a particular focus on Southern and Eastern Europe, while also strengthening its presence in France, the Benelux, and Germany. Last year alone, we saw landmark transactions such as the Asseco stake in Poland and the acquisition of Cipal Schaubroeck in Belgium. During 2026, however, the pace and breadth of expansion have been keeping up. A quick look at 🔗 TSS Insights gives you a good sense of just how active the company has become, specially after a slow start in Q1 2026 as the company used it to deleverage the balance sheet post-2025 acquisitions/investments spree.

This creates what I believe is a highly visible and repeatable multi-year runway. Topicus is operating in markets where the “boomer founder” succession wave is only beginning, acquisition competition remains significantly lower than in North America, and software assets are still available at attractive valuations.

Perhaps even more interesting is that Topicus is no longer thinking solely about Europe.

The company has quietly started laying the foundations for international expansion:

• Asia (Indonesia more precisely), where it has already deployed dedicated M&A professionals to build local sourcing capabilities. One example is 🔗 Alwyn Rusli’s LinkedIn, who recently joined to lead M&A efforts across the region.

• Australia, where it attempted the acquisition of 🐘 🔗 ReadyTech , demonstrating a willingness to pursue larger strategic targets outside Europe.

• North America, where earlier this year TSS acquired another sizeable 🐟, 🔗 Keypoint Intelligence, a New Jersey-based software business rumored to generate roughly €50 million in annual revenue. To me, this was one of the most interesting acquisitions of the year, extending the Topicus playbook back into the original home turf of the CSU ecosystem.

Returning to Europe, though, I think it’s worth revisiting what makes the region so attractive.

European regulatory complexity, fragmented languages, and localized software markets are often viewed as obstacles. I see them as competitive advantages for an operator like Topicus, ready to deploy the CSU’s permanent-owner philosophy and M&A playbook in this complexity. A traditional private equity buyer, operating on a 5-year exit horizon, in such a complex environment simply cannot replicate that model.

So, the very friction that discourages competitors is the same friction that creates Topicus’ opportunity. Or, as an owner-operator shark like ol’ good Bezos would put it: “Your regulatory nightmare, is my opportunity.”

It’s one of the reasons I believe the company’s acquisition runway remains significantly longer than the market currently appreciates.

Size is also still working in Topicus’s favour. At approximately €1.55 billion in revenue (in 2025) and around 10 000 employees, Topicus can still move the needle with smaller, lower-priced acquisitions, which is where the CSU playbook has historically generated its best returns. CSU at $11.6 billion in revenue needs increasingly larger deals to register at the portfolio level. Larger deals mean more contested auctions, more execution risk, and more often than not, higher multiples. Topicus is still at the sweet spot of the original playbook, where the best returns were made.

There is also an architectural detail here that gets overlooked: Operating Unit (OU) proliferation. The real bottleneck to scaling the CSU playbook has never been capital (at least so far); it has been finding and nurturing autonomous Business Unit (BU) managers capable of sourcing and running acquisitions locally. Each time Topicus buys a software company in Southern and Eastern Europe, it’s effectively building decentralized operating pods on the ground. When TSS/Topicus establishes a local M&A hub in Poland, Spain, or Indonesia, it drops the effective deal size threshold down to €1M–€5M natively, completely bypasses corporate overhead, and operates under the radar of European PE. Size isn't just a hurdle rate advantage; at Topicus's current scale, it’s the culture and agility advantage that the mothership has displayed for many years.

On the other hand, Topicus has consistently been the early testing ground for CSU’s most interesting experiments. Organic growth ran stronger at Topicus first. And PEMS, the most important capital deployment development in the complex right now, also ran its earliest proof of concept through Topicus, not CSU. If you believe that Topicus has historically been the advanced child of this ecosystem, that’s one more reason to pay close attention to what it does next.

Now let’s move from the narrative to the cold, hard numbers.

I spent some time digging into Topicus’ financials using what I call Cash-on-Cash (CoC) Returns, a simple framework I use to assess management’s capital allocation skills (if you’re unfamiliar with it, you can read my full piece here: 🔗 Understanding CoC Returns).

I also combined those CoC returns with the company’s reinvestment rate to estimate its expected intrinsic value growth using a straightforward relationship:

Intrinsic Value Growth ≈ CoC Returns × Reinvestment Rate

The full model (including the Excel spreadsheet) is available for download in the 🔗 Portfolio Corner. The key results are summarized below.

As you’ll notice, Topicus generates exceptionally high CoC returns, currently the highest within the CSU family, ahead of both Constellation Software and Lumine.

Historically, however, one criticism of Topicus has been its relatively modest reinvestment rate. Strong capital allocators only create value if they have enough opportunities to redeploy capital at attractive returns.

That’s begun to change in the most recent years though.

Following the surge in M&A activity throughout 2025 (what a year 🙌🏼), Topicus’ reinvestment rate has now climbed above the 100% threshold, reflecting management’s willingness to supplement internally generated cash with external capital when sufficiently attractive opportunities arise. That shift has only recently begun (2025), so its full impact on the financials and capital allocation metrics, like my CoC Returns and Reinvestment rate ratio, won’t be apparent until we move further into 2026.

Lastly, I wanted to share my DCF model for Topicus, specifically built and adjusted for serial acquirers like the CSU family. If you’re unfamiliar with the process for building it, you can read my full piece here: 🔗 How to Build a DCF for Serial Acquirers Like Constellation Software

And, just like the CoC Returns model, it’s available for download inside the 🔗 Portfolio Corner, where you’ll find the full extent of my assumptions and all the calculations done over a 40 years period to get to the Implied Share price.

Here’s the valuation summary extracted from my DCF model:

At the time of my analysis, using a CAD 102 share price and my base-case assumptions, the model implied +46% upside to intrinsic value.

Quite undervalued, don’t you think? That said, take the output with a dose of skepticism.

Valuing serial acquirers is inherently difficult. The biggest challenge isn’t forecasting next year’s earnings, but estimating how long management can continue reinvesting capital at high incremental returns. That depends on the availability of attractive acquisition opportunities, competitive intensity in European VMS markets, execution quality (keeping hurdle rates intact), and the unknown long-term implications of AI for software businesses.

Even so, under what I believe are reasonable assumptions, my model suggests the market is undervaluing Topicus today, particularly over the next several years given its superior organic growth profile (you can see how it makes a difference on the FCF over the years vs CSU/LMN once you get to compare them on the Serial acquirers DCF model spreadsheet). Whether that valuation gap ultimately closes will depend less on multiple expansion and more on management continuing to execute the playbook that has served the CSU family so well for decades.

If you want to use it as a framework to input your own assumptions, you can do so by downloading the model from the Portfolio Corner.

Constellation Software: The Ultimate Compounder You Don’t Sell

CSU is the one you don’t sell.

Capital allocation track record over 30 years on this spectacular systems-driven, culturally-entrenched M&A machine is as close to a secular compounding guarantee as public markets offer, and I don’t mean to use that language lightly.

But the other (less rosy) assessment is that new $$ deployed through CSU today are competing for targets in a more crowded environment than at any point in the company’s history, and the returns on incremental acquisitions is slowly and gradually starting to reflect that.

Low-to-mid-20% Cash-on-Cash returns hardly make for a bad investment, don’t you think?

Even more so when they’re paired with reinvestment rates that have consistently remained above 85%, occasionally approaching 100%. That’s a great combination, and it’s what has made Constellation such a compounder beast over the past two decades.

That said, one trend has become more apparent in recent years.

(And as always, don’t take the outputs of my model as absolute truth. CoC returns and reinvestment rates fluctuate over time, so longer measurement periods tend to paint a more representative picture of the returns earned on incremental acquisitions.)

As Constellation has grown, the law of large numbers has inevitably started to assert itself. Deploying billions of dollars every year requires pursuing increasingly larger acquisition targets, and larger deals rarely generate the same exceptional returns that were achievable when the company was much smaller and buying tiny vertical software businesses.

That’s simply the arithmetic of scale.

The key question is whether management can continue deploying capital (close to 75-100%) at returns comfortably above the cost of capital for many years to come. If the answer remains yes, even at somewhat lower incremental returns than in the past, the compounding story is still very compelling.

While I am not here to deny that CSU’s decentralised model still works (it does as you can see on its CoC Returns and Reinvestment rates over the years), I do think investors sometimes conflate the quality of the track record with the prospective returns on capital deployed today. Those are two different things.

Going forward, I see two key growth drivers that could push the "gravity of large numbers" a little further into the future.

The emerging market optionality is still underappreciated for being ‘too difficult’ and carrying more uncertainty. Asia-Pacific should be expected to be the fastest-growing VMS region going forward, and CSU has explicitly begun studying and piloting acquisitions there. The playbook successfully travelled from North America to Europe via Topicus but also to South America, specially in Brazil. The intellectual capital to travel further exists. That said, execution risk in less institutionally developed markets with more pronounced cultural differences is higher, and I think this optionality deserves a discount until CSU demonstrates it at scale.

(By the way, successfully applying its playbook in Japan, once and for all, would be a dream 👀. So far, they’ve had a hard time doing so).

The PEMS strategy has drawn a lot of attention and for good reason.

It’s probably the most important thing happening in the CSU ecosystem right now, and I don’t think the market has fully processed what it means.

Earlier this year, Constellation formally introduced what it calls the Permanent Engaged Minority Shareholder strategy (PEMS) as an additional capital deployment mechanism, with the investments in Asseco Poland and Sabre as the first meaningful expressions of it at the parent level.

The rationale is straightforward. CSU now generates so much FCF that the traditional acquisition model cannot readily absorb it all, particularly given that private software acquisition multiples have not meaningfully declined (yet) despite the AI-driven pressure on public SaaS valuations. When Buffett’s insurance float began exceeding what private acquisitions could absorb, he started taking large public equity positions. CSU is at an analogous inflection point. The thing is, this comparison is not hyperbole. This is how Berkshire’s capital deployment architecture evolved, and I think it’s a reasonable framework for thinking about where CSU goes next.

Now, here’s where Topicus deserves way more credit that I rarely see people give it: the precursor to PEMS at CSU was Topicus’s stake in Asseco Poland. Topicus acquired its initial position at approximately 85 PLN per share and ultimately built to roughly 24.8% ownership at a total cost of around $500 million USD. By mid-2025, Asseco was trading near 200 PLN, implying an entry at roughly a 60% discount to where the market subsequently valued it. That is not luck. That is sourcing and conviction operating at a different level than the market gives Topicus credit for.

More importantly, Asseco operates in 62 countries and is itself an active VMS acquirer in Central and Eastern Europe, essentially a Topicus twin for markets that Topicus had not yet penetrated directly. The investment didn’t just generate a return, it also opened a new geographic corridor.

The Sabre investment follows a similar logic at the parent level. CSU accumulated a combined 9.7% stake across common stock and derivatives, then negotiated a board seat for a Constellation executive on Sabre’s Technology Committee. The PEMS structure allows CSU to deploy hundreds of millions in a single investment, install operational influence, and benefit from a platform company’s FCF without paying a control premium. A board seat also functions as a window into future carve-out or full acquisition opportunities, which is precisely how we should think about Topicus’s Asseco position.

The key risk is the obvious one: minority status means influence without control. If target management resists the CSU operating philosophy, the capital sits in a suboptimal structure. The Sabre situation illustrated this briefly before the standstill agreement was reached. That’s a real risk, and it’s worth sizing for. I think the market is still figuring out how to price PEMS as a capital deployment channel, which means the optionality is not fully in the stock yet.

Speaking of the culture post-Mark Leonard: the reason CSU’s decentralized engine will outlive its creator comes down to where decision-making actually lives. CSU’s hurdle rates (traditionally ~20-25% IRR) aren’t enforced from a corporate boardroom in Toronto; they are embedded into the compensation formulas of dozens of Operating Group presidents and hundreds of BU managers. Capital allocation at CSU is essentially an algorithmic incentive structure. Mark Leonard built an intellectual franchise model. That organizational design is precisely why the mothership can handle multi-billion dollar capital deployment stress while the underlying operating units continue compounding unimpeded.

Before moving on to CSU’s DCF valuation, there’s another source of optionality that I think deserves attention: spin-offs.

Arguably, spin-offs have become Constellation Software’s most effective tool for fighting the law of large numbers, and I wouldn’t be surprised to see more of them over the coming years.

That said, spin-offs solve the scale problem more effectively for the newly created entity than for the parent company itself. By separating a collection of businesses into a smaller, more focused organization, management can preserve the entrepreneurial culture and capital allocation discipline that become increasingly difficult to maintain as organizations grow.

For CSU shareholders, however, the beauty lies elsewhere.

Constellation typically retains significant ownership stakes in its spin-offs, roughly 30% of Topicus and 60% of Lumine Group, for example. That means shareholders continue participating in the value creation of these businesses while also benefiting if the market assigns them higher standalone valuations.

And if another spin-off were announced tomorrow, existing CSU shareholders would immediately participate in that optionality through their ownership of the parent.

It’s a very shareholder-friendly mechanism: management creates another independent capital allocator without forcing investors to choose between the parent and the spin-off. In many ways, you get exposure to both. Thank you, Leonard, Sir. 🧙🏻‍♂️

Now, let’s move into the DCF model I’ve crafted for CSU. Like the Topicus DCF model, it is available for download inside the 🔗 Portfolio Corner; and, the resulting valuation summary below:

At the time of my analysis, using a CAD 3000 share price and my base-case assumptions, the model implied +32% upside to intrinsic value.

Still undervalued, just like Topicus at these prices.

Again, take my output with a dose of skepticism. If you want to use it as a framework to input your own assumptions, you can do so by downloading the model from the Portfolio Corner.

Lumine Group: Great Management, Asymmetric Upside

In my view, Lumine is the highest-ceiling, highest-risk name of the three, and I think the appropriate framing is that it’s a high-conviction bet on a differentiated strategy, not a core compounder in the CSU or Topicus sense.

Their carve-out playbook is what makes this business so special.

Lumine is, as far as I can tell, the only permanent-owner acquirer specifically positioned in the telecom and media VMS vertical. Telco software customers demand continuity. The “buy and hold forever” model is a meaningful competitive advantage in seller conversations, particularly when the alternative is a PE fund that will flip the business in five years. As large vendors like Nokia, Ericsson, and Cisco continue to rationalise their software portfolios through 5G infrastructure transformation and Open RAN adoption, the pipeline of carve-out assets is likely to grow rather than shrink.

Now, what I like the most about this company is their management. The team is executing the playbook to a T this year, and it’s beating my own high bar expectations. Do a little bit of DD and take a good look at their recent acquisitions: 🔗 Lumine | Press Release.

Music to my ears.

The funny part is I suspect the market won’t appreciate the next few quarters. Large acquisitions tend to weigh on margins, create operating noise, and muddy both the income statement and cash flow before the benefits show up.

That’s the price of playing the long game…

Anyways, onwards.

So, they are running their playbook flawlessly, and I’ve been genuinely impressed by CEO David Nyland’s leadership after listening to him on the recent CSU AGM. Nyland is the closest thing I’ve seen to Constellation’s Mark Leonard, i.e. exceptionally pragmatic, deeply thoughtful, and entirely systems-driven.

Out of our three CSU family holdings, Lumine is simply executing the best so far this year. And after some hesitation last few months, it feels way better than I feared to have my capital anchored back here.

What makes Lumine's carve-out playbook so lethal when executed correctly is the sheer magnitude of margin expansion post-acquisition. When legacy tech giants like Nokia or Ericsson divest software divisions, these assets are often saddled with bloated corporate overhead, inefficient sales structures, and (sometimes) sub-10% operating margins. Lumine doesn't buy these businesses for their organic growth. but to strip out corporate cost, re-orient management toward net revenue retention, and apply CSU’s rigorous benchmarking metrics. Within 18 to 24 months, Lumine regularly converts 5-10% margin telecom corporate orphans into 25%+ EBIT margin cash cows. That operational turnaround lever gives Lumine a margin of safety on valuation that other pure buy-and-build serial acquirers don't have.

Lumine's greatest asset may well be its management team. (What a blessing for Lumine’s investors). This is an exceptionally complex playbook to execute, and without the right people at the helm, it would be almost impossible to replicate consistently.

That said, there are a few things I want to highlight that makes this name riskier:

1. Large carve-outs are inherently messy to integrate, and some of the underlying telecom software businesses face structural volume declines that have nothing to do with Lumine’s operating skill.

2. Each deal at Lumine’s scale is more binary than at CSU or Topicus. One poorly executed $200 million acquisition has outsized portfolio impact in a way that would be noise inside CSU’s 1 500-business portfolio.

3. What continues to hold me back is the underlying end market, which David Nyland himself described as “fatigued and bruised.” The persistent low/zero (potentially negative) organic growth profile of telecom software (especially as Tier 1 operators consolidate) keeps me cautious.

Ironically, I fully understand that this is precisely where Lumine’s strengths lie: buying dysfunctional carve-outs and operationally improving them. But this strategy feels more execution-dependent and management-sensitive than CSU’s or Topicus’, which benefit from broader and structurally healthier end markets.

Last, the full CoC returns and DCF models (including the Excel spreadsheet), are available for download in the 🔗 Portfolio Corner. The results are summarized below:

Lumine’s Cash-on-Cash returns have consistently remained in the high-20% range, while reinvestment rates have exceeded 100% throughout the four years since the company went public.

That’s not entirely surprising given Lumine’s strategy. Its focus on large carve-outs naturally creates a deeper pipeline of opportunities to redeploy capital. That doesn’t mean execution is easy (far from it), but it does make deploying operating cash flow at attractive returns somewhat easier than for businesses pursuing smaller acquisitions.

The combination of high CoC returns and aggressive reinvestment is exactly what you want to see in a serial acquirer.

The DCF tells a similar story. Under my base-case assumptions, the smallest member of the CSU family still appears meaningfully undervalued, with roughly 43% upside to my intrinsic value calculations.

Sometimes I catch myself wondering why I don’t just put all my eggs in the CSU basket. 😅

Then I remember that risk management exists and that diversification is one of the few free lunches in investing. Even the best capital allocators deserve position sizing that acknowledges uncertainty.

Again, take my assumptions with a grain of salt and make your own opinions.

👀 Important Note on DCF Models Assumptions

You may have noticed, after digging through the full DCF models inside the spreadsheet, that I’m using a tad more conservative assumptions for the spin-offs than for the mothership.

What can I say? Constellation Software has a 30-year track record, exceptional bench depth, and the market’s confidence. That deserves a premium reflected in some of my numerical assumptions.

There’s also a more practical consideration. While it shouldn’t matter over the long run (nor has any impact on their business fundamentals), Constellation trades on the Toronto Stock Exchange, benefiting from greater liquidity, broader institutional ownership, and higher visibility. The spin-offs, meanwhile, remain listed on the TSX Venture Exchange, where liquidity is thinner and many institutions simply don’t participate.

Perhaps one day they’ll graduate to the TSX alongside their parent. Until then, I think a slightly more conservative underwriting is justified.

My Pecking Order & A Word on AI

The secular tailwinds that the VMS complex is riding (i.e. public sector digitalization, founder succession, and AI-enhanced margins, etc.) remain promising. But the entity-level differences within the ecosystem matter more than they did 5 years ago, and I think many investors are still underweighting them.

Topicus offers the most legible organic growth profile, the most visible geographic runway at a size where the original CSU playbook still generates its best returns, and has already served as the proving ground for what may be CSU’s most important strategic evolution. I would say that Topicus is the most structurally interesting name in the complex today.

CSU is the legendary compounder you hold through any environment. While incremental returns on new capital are inevitably starting to reflect the law of large numbers, the PEMS strategy, the extreme decentralisation and ability to expand the playbook into emerging markets are some variables that could shift that calculus, and it’s a key thing to track over the next 12-24 months. The market hasn’t fully priced this optionality in yet.

Lumine is the asymmetric bet with a great management team at the helm, a special differentiated playbook carrying higher execution risks. I’m sizing it accordingly.

My pecking order for new incremental capital:

Topicus first, CSU second, Lumine third, with PEMS and successful expansion in key emerging markets being the development that could move CSU up that ranking faster than anything else.

Before wrapping up, a word on AI. Some of you may be wondering why I’ve barely mentioned the hot topic as part of the investment case.

It’s not because I’m skeptical about AI’s contribution to the CSU family. Quite the opposite. Constellation, Topicus, and Lumine are already rolling out AI-enabled products and workflows that are delivering measurable ROI to customers.

The reason is simpler: I’ve covered that topic extensively in previous deep dives, earnings digests, and other articles. More importantly, I find it incredibly difficult to incorporate AI into a comparative valuation framework when analyzing businesses with broadly similar models, customers, and industry dynamics.

At this stage, AI feels more like a rising tide than a differentiator.

If I had to bet on which company within the CSU family ultimately extracts the most value from AI, I’d still lean toward Constellation Software. Mainly, because it has by far the deepest installed base, the broadest collection of operating groups, and the greatest ability to identify successful use cases and systematically disseminate them across hundreds of business units.

With that said, Thank you all for following along,

— Nikotes

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This third and final installment of the Software Darwinism series won’t focus on CSU or its spin-offs. I’ve written extensively about them over the last four or five months (don’t worry, there will be more coming), but this piece takes a different direction entirely.

If you’d like to read the first two parts before diving in, here are the links:

🔗 Software Darwinism: Does All SaaS Die in the Age of AI? And Where Does Constellation Software Fit?

🔗 Software Darwinism 2.0: How Intelligence (AI) Deflation is Impacting Software & Where the CSU family Stands

This third piece is heavily influenced by the SemiAnalysis EDA market primer launched a few weeks ago, which I’d encourage every reader to go through in full. Here is the link: 🔗 EDA Market Primer - Market Dynamics, Cadence, Synopsys, Siemens, China EDA Rise

The core argument they lay out is one I find compelling and, frankly, underappreciated by most investors when assessing software and their moats: Electronic Design Automation (EDA) at the leading edge is the closest thing to a true utility monopoly that exists in the entire technology stack … and it happens to be software.

Weird, isn’it?

While nearly every software vendor faces some narrative of AI-driven disruption, EDA, dominated by the duopoly of Synopsys and Cadence, operates in a structurally different category. You cannot design a microchip, an AI accelerator, or an advanced system-on-chip without their IP and physics-based software suites. These tools are not just optional productivity layers, they are engineering constraints embedded directly into the semiconductor and systems development process.

That’s precisely what makes them so valuable.

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The Three-Headed Moat

The competitive moats here are self-reinforcing in a way that’s very rare to find, even among the best vertical software businesses.

The first and most obvious moat is switching costs, but I’d argue the market still underestimates just how punishing they are in practice. A chip design team spends years mastering the proprietary tool chains embedded in either Cadence’s or Synopsys’s ecosystems. Forcing hundreds of highly specialized engineers off tools like Virtuoso (Cadence) or Design Compiler (Synopsys) onto an unproven alternative delays time-to-market by years and introduces risk of catastrophic tape-out failure. A tape-out failure on a leading-edge chip can cost hundreds of millions of dollars and set a product roadmap back an entire generation. No CFO is signing off on that risk to save on an EDA license that makes up a small portion of their R&D spend.

The second moat is less talked about and, in my view, the most underappreciated of the three. For an EDA tool to be usable at the leading edge, it must be rigorously calibrated to the physical manufacturing capabilities of the foundry it’s targeting. TSMC, Intel Foundry, and Samsung provide confidential, hyper-precise Process Design Kits (PDKs) exclusively to Synopsys and Cadence, and they do so years before a new manufacturing node goes live. This isn’t a business arrangement that a new entrant can negotiate its way into. The data required to write competitive EDA software for leading-edge nodes is, quite literally, inaccessible to everyone else.

The third moat is what I’d call the “Lego Brick” lock-in. Chip designers don’t build chips from scratch; they license pre-designed building blocks (PCIe interfaces, DDR controllers, memory PHYs, etc.) and drop them into their layouts. Synopsys and Cadence are the world’s dominant suppliers of this non-processor physical IP. Because their software tools are natively optimized to integrate these IP blocks seamlessly, customers face compounding switching costs: leaving the software ecosystem also means leaving the IP ecosystem. The two reinforce each other in a closed loop that makes migration not just painful but economically irrational.

Put all three together and you have one of the most structurally defensible business models in technology: extreme switching costs, gated access to foundry data, and deeply embedded IP blocks. A legacy software competitor starting from scratch is just very unlikely to succeed.

The AI Opportunity

Historically, EDA was a software tool wielded by human engineers. Generative AI is fundamentally restructuring that relationship, and I think most investors (and I include myself) are still sleeping on what this means for the pricing power and TAM of CDNS and SNPS over the next decade.

Designing a chip layout involves navigating an astronomical number of physical variables to balance what engineers call PPA: Power, Performance, and Area. Traditionally, a human engineer might spend weeks manually tweaking these variables to find an acceptable solution. Tools like Synopsys’s DSO.ai and Cadence’s Cerebrus use reinforcement learning to autonomously discover near-optimal layouts in days, consistently delivering double-digit power savings and dramatically shorter time-to-market. This becomes a step-change in what their software can do.

Here’s Anirudh Devgan (Cadence’s CEO) during Q1 2026 conference when asked about AI’s multiplier effect on Core EDA usage:

“When a user designs a chip... 1 engineer will run like 1 or 2 experiments. But when the agent runs those blocks, they may try 10 or 100 variations of those things... So not only agent can give more productivity, it by nature runs more of the base tools.” — Anirudh Devgan, CEO

What’s interesting about this shift is the pricing implication and how Cadence and Synopsys are already benefitting from it.

Once an EDA tool demonstrably saves a customer $50 million in engineering labor, wafer space, and several months of development time, the historical “per-seat software license” model starts to look materially underpriced.

Even activist investor Elliott Investment Management (now influential at Synopsys following its large stake) has called out this dynamic, arguing that EDA vendors likely have far more pricing power than the market appreciates.

What’s emerging instead is a hybrid “subscription + consumption” model, and the effects are already beginning to flow through revenue growth and margins. Cadence management was unusually explicit about this during the Q1 2026 earnings call.

On agentic AI and the transition toward consumption-based pricing, CEO Anirudh Devgan stated:

“What agentic AI allows us is to sell products in spaces we didn’t have products before, like RTL generation and analog automation... So that will be priced as a subscription plus consumption model, very similar to other kind of leading AI tools. So that’s a completely new category for Cadence... And then in turn, agentic AI will drive more of our base tools.”

Meanwhile, CFO John Wall highlighted the operating leverage embedded in the model:

“When we look at our organic incremental margin, it’s closer to 60% these days than 50%... With the benefits that we’re seeing in terms of customer engagement accelerating on the agentic AI front, I think there’s even more opportunities to stretch that incremental operating margin going forward.”

The implication is significant: both Cadence and Synopsys may be entering a phase where AI not only reinforces their moats, but also structurally expands monetization and margins.

That likely explains why these stocks have continued to rerate upward while much of the broader software universe still struggles with AI disruption fears.

There’s also another angle here that I find particularly interesting: the hyperscaler in-sourcing tailwind. As Google, Amazon, and Meta aggressively pivot toward designing custom internal ASICs (TPUs, Inferentia, MTIA) they are simultaneously trying to execute these designs with lean hardware teams. They lack the deep armies of hardware specialist engineers that traditional semiconductor companies have built over decades The solution, not coincidentally, is to lean heavily on the AI-automated design suites of CDNS and SNPS. The hyperscaler arms race to reduce NVIDIA dependency is not a headwind for EDA. It is a recurring, structural cash tailwind.

And this is actually where I’ve changed my mind. Previously, I held a more bearish view around the risk of hyperscalers eventually developing internal EDA capabilities. But the deeper I’ve dug into the complexity, physics constraints, and embedded workflows of modern chip design, the less likely that outcome appears (at least at scale).

I’ll dedicate an entire section to this topic at the end of this piece for Expanse Stocks subscribers.

The Risks of AI Disruption

The bearish scenario that’s been more discussed is the in-house AI challenge. If a tech giant with massive computational scale (say, NVIDIA) were to build a proprietary, highly specialized AI model capable of autonomously routing and verifying circuits better than the broad generalized models built by Cadence or Synopsys, you could make the case that dependency on legacy EDA suites declines over time. Google’s AlphaChip work has been the most visible example of this ambition. I don’t want to dismiss the possibility entirely, but I think the SemiAnalysis framework makes a fairly convincing case for why the incentives to pursue this aren’t as strong as they appear. (I’ll get into this more in detail in the last section reserved for subscribers.)

The second risk is Synopsys-specific and more near-term. Synopsys has finalized its multi-billion $ acquisition of Ansys, a leader in engineering simulation software. The strategic logic is sound: modern chips are stacked vertically in 3D-IC configurations and face extreme thermal and structural stress, so combining electronic design with physical simulation creates an extraordinarily deep, full-stack workflow moat. But the execution risk is real. This is a large, complex integration that stretches Synopsys’s balance sheet and creates a multi-year vulnerability that Cadence doesn’t have to worry about. I think of this less as a structural threat to the thesis and more as a company-specific risk that will make SNPS noisier to own over the next two to three years.

Structural Growth Outlook: Decoupled From the Cycle

One of the things I find most compelling about the EDA business model is its decoupling from the consumer electronics cycle that tends to drag down sentiment on anything with “semiconductor” in the description. EDA revenue scales with the volume of R&D chip design starts, not with the physical volume of manufacturing units shipped. Every time a car manufacturer designs a custom EV chip, a medical device company develops an embedded IoT sensor, or a tech giant refreshes its AI accelerator architecture, they must pay the EDA tax.

This means that even in a world where smartphone and PC sales flatline, EDA compounds because the underlying driver, i.e. the proliferation of custom silicon and embedded complex systems across every industry vertical, is secular, not cyclical. The market is essentially paying for an annuity on the complexity of the modern world.

I’d argue that’s one of the highest-quality growth profiles in the entire technology stack, and it’s one that remains durable precisely because of the moats discussed above.

A Note for Expanse Subscribers: Why I Changed My Mind on Cadence

Read more

I started this conversation on SaaS, AI, and the shifting market narrative two months ago with my first piece:

🔗 Software Darwinism: Does All SaaS Die in the Age of AI? And Where Does Constellation Software Fit?

And I think this is a conversation worth continuing. As investors, we’re watching a sector that’s evolving, and accelerating, as quickly as it has in years. Understanding where value accrues, where moats weaken, and where they strengthen is becoming one of the defining questions for software investing today.

There’s a debate worth paying attention to, one that some of the brightest minds in tech (including Jensen Huang) have been hinting at:

If intelligence (AI) is trending toward marginal cost zero, what happens to companies whose entire business model is acting as a toll-booth for that intelligence?

Some argue software may become an intelligence (AI) wrapper trap, others that the era of intelligence deflation will benefit software incumbents cost structures.

The thing is both sides of this debate may be correct, but they are missing an important point : their conclusions don’t necessarily apply uniformly across the broader software market. There will be winners and losers.

Just as the semiconductor industry went through a long consolidation that ultimately produced some of the most durable growth businesses in the world, something similar could happen in software. For decades after the dot-com crash, software benefited from a favorable structure: high margins, low CapEx intensity, and generous SBC-funded growth narratives.

That “advantage” may be changing.

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The SaaS Re-Rating is Real and Deserved ?

Let’s start with what’s happening in the SaaS market and what’s driving the SaaS-mageddon narrative, because this sets up everything else.

A growing share of OpenAI and Anthropic’s enterprise ARR is flowing through cloud platforms and SaaS products that embed their models. These businesses plug into the Claude or GPT API, slap a “Copilot” feature into their dashboard, and charge clients an extra $20/month per seat. They’re functionally reselling Anthropic’s intelligence with a markup.

It gets interesting when you look at the deflationary trend of intelligence (AI).

Foundation models are getting cheaper and better. That’s a fact, and Nvidia’s roadmap is hard proof of this and a glimpse into the future. So, if you are a software company and your entire value proposition is “we make it easy to use AI to write marketing emails,” your terminal value is trending toward zero. As underlying models get cheaper, barriers to entry collapse, competitors flood in, and pricing power evaporates.

The market increasingly believes this and it’s applying the same whip across the broader software industry. As a result, many horizontal and vertical SaaS companies have been heavily punished over the past 8–12 months.

The message from the market is becoming clearer: if you’re primarily a distributor of a deflationary asset (compute, intelligence), you shouldn’t trade at 15× ARR. You should trade more like a traditional distributor at a low double-digit EBITDA multiple. We’re not there (in most cases), but that’s the direction sentiment is moving.

The worst part of software investors is this re-rating does not seem to be a temporary market pessimism but a fundamental reassessment of what these businesses are actually worth, repriced one new Claude’s AI feature release at a time.

And when valuation frameworks shift at the industry level, not just the company level, multiples rarely snap back quickly.

The death of the GUI moat, and why horizontal SaaS deserves the scrutiny it is getting

There is a piece circulating from SemiAnalysis, 🔗 Claude Code is the Inflection Point, that has been generating a lot of discussion, and rightfully so.

It is a very good articulated framework for understanding what AI agents actually do to the software industry’s economics, not in a vague sense, but structurally. It is worth taking seriously, particularly if you own any software name.

The core of the SemiAnalysis argument is simple: AI agents do not rely on human-oriented workflows. For the better part of two decades, companies like Salesforce, ServiceNow, and Microsoft built part of their switching cost moats by forcing humans to learn their interfaces. An entire sales team that knows how to navigate Salesforce is a sales team that is not going anywhere. That is a real moat, and the market has priced it accordingly, sometimes generously so.

The problem SemiAnalysis points out is that the moat was never the software. The moat was the human in the loop.

Let me give you an example : If an autonomous AI agent becomes so good at its job that it’s able to query a database directly, synthesize the output, and deliver a finished analysis to the VP of Sales without a single human ever opening a CRM tab, then the $150/month seat license is not competing against a better CRM. It is competing against an API call that costs a fraction of a dollar. That is a different conversation entirely, and I think the market has been internalizing this. We are not there yet, but we are getting there fast.

This is why, if you’ve been following me for some time in my 🔗 Portfolio Corner, you’d notice that I don’t spend much time worrying about horizontal SaaS, even at current multiples. Thin wrappers, BI tools, and data-entry software built on 75-80% gross margins are facing a structural problem that no amount of AI feature-bolting will fully solve.

SemiAnalysis is basically saying: The foundational models are going to consume those margins, and the incumbents’ only defense is switching costs that are themselves being eroded.

When you put it this way, that is not a thesis I’d want to be long on. But, do I fully agree with this take ? Not really, I believe there are nuances within the industry.

Stress-testing VMS against the same framework

Where it gets more interesting and more contested is whether this framework extends to Vertical Market Software. SemiAnalysis specifically names Accenture’s use of AI agents in public sector and healthcare. Those are not random verticals. Those are the exact verticals that CSU and TOI have spent decades colonizing. So I think it is worth being honest about both sides of this.

The bear case is not unreasonable: the collapse in migration and maintenance costs.

One of the key reasons a municipality keeps paying its $50-100k annual maintenance fee to a VMS vendor is not because they love the software. It is because the alternative, hiring consultants to migrate decades of legacy data to a modern system, costs a few million dollars, takes months / years and some non-negligible operational pain. That switching cost is a function of human labor, and human labor is precisely what AI is making cheaper. If Accenture can use ‘almighty’ Claude Code, at some point, to build and deploy a custom billing system for that municipality in three weeks instead of months with supervised AI agents maintaining the new software autonomously, the $50-100k maintenance fee starts looking a lot less sticky. I would be intellectually dishonest if I dismissed this risk entirely. Again, we are absolutely not there yet, but the pace of innovation in AI suggests we might not be that far. The market believes this.

The bull case, however, rests on something that SemiAnalysis (and the market) mostly gloss over: the difference between information processing and regulatory reality.

VMS is not just software that processes data. At its best, it is software that encodes decades of hyper-local compliance requirements : union rules, tax codes, public sector procurement regulations, pension payout structures,… The code is not valuable because it is technically complex. It is valuable because it reflects bureaucratic reality that took years to accumulate and it’s deeply embedded in customer operations. No AI agent is going to hallucinate its way through safely. And even if an AI lab claims it can, there’s usually no decision-maker on the other side willing to delegate responsibility for those workflows to a probabilistic system.

There is also a liability dimension here that I think gets underweighted.

An AI agent generating the wrong slide for a marketing team? Embarrassing.
An AI agent miscalculating a 911 dispatch route or a pension disbursement? That’s a lawsuit and a news story.

The tolerance for hallucination error varies by vertical, and VMS tends to sit in the low-tolerance end of that spectrum.

Why the CSU Family is Different

If you own Constellation Software, Topicus, or Lumine, you should absolutely be monitoring this debate.

Now, let’s point out why I do think the CSU family is different and more resilient to this AI narrative :

1. The Code is No Moat. It is the Workflow, Switching Costs and Customer Trust

I feel like I’ve repeated myself so many times on this topic across the Substack that I’m starting to get déjà vu. So, I’ll keep this one simple.

VMS moats aren’t built on code complexity. They’re built on switching costs, regulatory compliance, embedded workflows, industry-specific know-how, and customer trust.

The software could be written in COBOL or generated by ChatGPT, the customer doesn’t really care. What they care about is that it works, remains compliant, and doesn’t introduce migration or reliability risk into mission-critical processes.

We’ve covered this before, so I won’t go deeper here.

2. CSU Owns Distribution and Data

CSU companies already have the customers and the proprietary data. If an AI feature truly adds value to a golf course management system, the CSU company will simply plug the Anthropic API into their existing software. Because they own the distribution (the customer relationship) and the data (20 years of golf course tee times, booking patterns, member preferences), they can defend their position.

They might not be able to mark up the AI feature aggressively, and they shouldn’t try, but they won’t lose the client to an upstart either. The customer relationship and embedded position are the assets that matter, not the sophistication of the codebase.

3. The First Paradox: Why intelligence deflation might actually be a tailwind for CSU family margins and cash flows

Here is the part of this thesis that I find underappreciated. The same AI forces that threaten VMS’s organic growth could simultaneously be the best thing that ever happened to Constellation’s margins and cash flow generation.

Why?

The CSU family owns thousands of legacy software assets that require ongoing developer resources to maintain, patch, and update. If one developer with access to modern AI tooling can now do what previously required a team, the internal R&D and maintenance burden on those assets drops considerably. And that matters, because R&D is one of the largest operating cost lines across the Constellation ecosystem. Of course, I don’t know exactly where margins land (nobody does) but the direction of travel seems fairly clear. EBITDA margins that currently run around 25% could organically expand without any organic revenue growth whatsoever. That would be an unusual situation.

4. The Second Paradox: Buying the “ashes” of the SaaS industry might actually be a tailwind for CSU and family growth runaway

The M&A angle is, if anything, even more interesting.

SemiAnalysis is essentially arguing that VC-backed horizontal SaaS companies are going to see their moats and margins compress. When that happens, their valuations compress with them.

CSU has spent 30 years building a database of acquisition targets and a repeatable process for deploying capital into software businesses at disciplined multiples. If the cost of acquiring a SaaS business drops from 8x revenue to 1x revenue because AI has structurally impaired its growth outlook, then the ROIC on Mark Leonard’s next wave of capital deployment could be meaningfully higher than the last. The M&A bonanza thesis requires the bear case to be directionally right about SaaS valuations (we are seeing it already in the public market), which is exactly why it is worth taking the SemiAnalysis framework seriously rather than dismissing it.

So, I say : let the SaaS-mageddon unfold while CSU and co. pick up the corpses and proof test its new strategy, PEMS.

How I think about this in portfolio terms

Put all of this together and I think the honest conclusion is that software deserves a reduced weight relative to where most long-term software investors have historically sized it, not because the cash flows are impaired today, but because the range of organic growth outcomes has widened in an unfavourable direction.

For VMS and a holdings companies like the CSU family, the upside scenario (AI drives internal margin expansion and a cheap M&A wave) is compelling. But, the downside scenario (switching costs erode faster than margins expand) also creates uncertainty. That uncertainty could warrant a smaller position, not a zero.

The other natural hedge here, which I am more inclined to take, is owning the companies actually causing the intelligence deflation : the semiconductor ecosystem and the hyperscalers. If AI agents are truly going to commoditize software labor and erode software moats, then the economic surplus has to land somewhere. It lands with the companies selling the picks and shovels. Owning both sides of this transition is not a hedge in the traditional sense; it is an acknowledgment that the direction of travel is clear even if the exact casualties are not.

The SemiAnalysis thesis does not make VMS uninvestable. What it does is raise the bar for what you need to believe to size it aggressively. And right now, I think that bar is higher than many long-term software investors are giving it credit for.

Thanks for following along,

—Nikotes

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The market is pricing in a software apocalypse. Many SaaS stocks have been hammered since October 2025, other sectors (data services, financial services, cybersecurity) have followed, with the narrative being that AI will unbundle, displace, and destroy the incumbents. Companies will vibe-code their own solutions, agents will replace seats, and decades of software moats will evaporate overnight. 2026 starting strong 🙌🏼

The thing is this narrative is both right and catastrophically wrong, depending on which type of companies you’re talking about.

Not all software are created equal. Some software must be correct. Other software just needs to be useful. Understanding that distinction is key to building conviction if you want to keep holding these companies today.

Another question that keeps coming up among fellow Constellation investors is where Constellation Software stands in all of this. So let’s walk through the “apocalypse” scenario together and try to bring a bit of light to it.

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• New Article Format Coming: Short analysis briefs on the watchlist stocks I currently find most interesting (or am digging into more deeply):

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  • what I like,

  • and what keeps me from pulling the trigger.

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Types of Software

There’s been a lot of chatter on FinTwit and among software investors about what separates software that’s vulnerable to AI disruption from software that isn’t.

I won’t rehash the whole debate, but it’s useful to frame the divide.

On one side, you have deterministic systems where precision is key. On the other, you have probabilistic systems where “good enough” is acceptable.

Deterministic Systems: Selling Correctness

Deterministic software follows a simple rule: same input → same output, every single time. These are systems where errors are catastrophic.

Think about payroll software. If the system is off by 2%, that’s not “close enough”. That probably ends up in a lawsuit and potential regulatory violation. The same goes for accounting systems, banking ledgers, hospital billing, inventory management, tax software, and airline reservations. These systems must be correct.

Some characteristics of deterministic software are:

• Mission-critical to operations

• High switching costs

• Long contract cycles (3-5 years is common)

• Moderate but steady growth

• Retention rates approaching 100%

• Pricing based on value delivered, not usage

• Often focused on specific verticals

This is where most VMS thrives. This is where companies like Constellation Software live. And this is where the AI disruption narrative starts to break down.

Probabilistic Systems: Selling Improvement

Probabilistic software operates in likelihoods rather than certainties. The outputs are statistically good but not guaranteed. Errors are expected and tolerated as long as the overall system performs adequately.

Netflix recommending a mediocre movie? No big deal. Google showing you a slightly less relevant search result? Minor inconvenience. Marketing attribution being directionally correct but not precisely accurate? Acceptable. These systems work with pattern recognition, optimization, prediction, and generation.

Of course, many probabilistic systems are built on top of, or tightly integrated with, deterministic layers. So drawing a clean line between the two isn’t as straightforward as it might seem.

The business model for these looks entirely different:

• Usage-based or consumption pricing

• Rapid iteration cycles

• Data network effects as the primary moat

• Horizontal platforms serving broad markets

• Lower switching costs

• Commoditization

The examples are everywhere: search engines, recommendation systems, fraud detection, marketing tools, LLMs like ChatGPT, image recognition, demand forecasting. All valuable, all useful, but none require perfection.

So, the main take here is that: deterministic software sells correctness. Probabilistic software sells improvement.

Why This Distinction Matters

AI is fundamentally a probabilistic technology. It excels at pattern matching, generation, and “good enough” solutions across different problem spaces. This means that AI is a direct substitute for probabilistic systems in ways it simply cannot be for deterministic systems. Or at least on the current state of the art.

If an LLM can replicate your probabilistic product with 90% of the quality at 10% of the cost, you may end up not having a good business anymore. Even a great UI or UX won’t save you.

But try getting an LLM to run payroll for a 10 000 person company. Try having it manage municipal billing where errors create regulatory violations. Try using it for public safety dispatch where lives depend on precision. The answer isn’t “the AI isn’t quite there yet”, it’s that these problems don’t suit probabilistic solutions.

Anthropic uses Workday for HR. OpenAI uses Slack for communication. It’s incredibly clear to anyone with half a brain that nobody is vibe-coding critical infrastructure. The liability alone would be absurd. When the cost of failure is asymmetric: lawsuit, business shutdown, regulatory violation, people dying, … You don’t experiment with “good enough.” You pay for proven, deterministic systems that simply work.

A Bear Case Stack

Let me lay out some bear cases I came up with for incumbent SaaS. In no particular order, except one of them.

1. Platform differentiation trends toward zero. We were already trending toward every platform offering every app. AI just made it easier to copy features.

2. Value will accrue to the agentic layer sitting on top of systems of record. The AI layer that orchestrates across systems (siloed systems of record) might capture more value than the underlying systems themselves.

3. Investor sentiment becomes a structural headwind as the business model gets de-rated. If the market believes software quality is declining and with it, the durability of terminal value, then multiples compress, regardless of underlying fundamentals. Sentiment matters and for a software investor, this is arguably the most dangerous risk of all IMO.

4. AI-native startups deliver tremendous value at better prices, eating incremental LTV. A startup without technical debt, built AI-first, might offer 80% of the functionality at 20% of the price for certain use cases. I don’t really believe in this though.

5. As agents do more work, seat-based revenue declines. If one employee with AI agents can do the work of three, you need fewer seats. This breaks the traditional SaaS pricing model.

6. Legacy SaaS struggles to transition from seats to outcomes. The companies built on seat-based pricing don’t have the infrastructure, go-to-market motion, or pricing expertise to shift.

7. Diminished pricing power due to decreased differentiation. As features commoditize and lock-in weakens, pricing power goes away.

8. Gross margins deteriorate because AI revenue is structurally more expensive. Running inference costs money. If your AI features have 60% gross margins versus 85% for traditional software. Margins compress as AI adoption grows.

9. Competition for scarce AI talent increases SBC/opex faster than revenue. Incumbents fight to keep A-players from jumping to AI-native startups, bidding up compensation while growth slows. I can see a world where this happens, particularly with the US software darlings.

These are all real risks. Some could play out for certain companies.

A Bull Case Stack: Why Incumbents Win

The counter-narrative is that the AI disruption will be highly selective, and incumbents in the right categories have more structural advantages than headwinds.

1. AI expands TAM by enabling outcome-based pricing. The opportunity isn’t selling seats anymore, it’s displacing labor by charging for outcomes. This could become a new larger market.

2. Customers are willing to pay for an AI add-on if it actually works and solve their problems. If a business currently spends $20-50 to close a support ticket with human labor, they’ll be happy to pay $0.50 for AI to solve it. Similar dynamics exist with lead qualification, business development, and other workflows.

3. No company wants to use another vendor or build in-house. The idea that enterprises will eagerly rip out proven systems to cobble together AI point solutions is fantasy. It is infinitely easier to just use your existing relationship and infrastructure.

4. Customers are rooting for incumbents to figure this out. Customers don’t want to re-evaluate competitors, migrate data, retrain employees, and manage additional vendor relationships as long as the existing ones offer them “AI augmented” value.

5. Even if they’re testing other solutions, they’ll switch back if the incumbent becomes good enough. The bar isn’t “the incumbent must be better.” The bar is “the incumbent must be acceptable.” That lowers the hurdle.

6. Incumbents still have time to become acceptable. If they execute reasonably well, the switching costs and relationship inertia will continue to protect them. If they fumble for 3-4 years, the window may close though.

I believe that many incumbents will figure it out. If their AI talent gap is closing, if their playbook becomes clearer, and their incentives are properly aligned, betting against them is as foolish as betting on all of them.

Where Does Constellation Software Fit in All This?

Constellation Software and the broader VMS universe sit mainly in the deterministic camp.

I’ve gone over what CSU does many times on previous articles but let’s do it again: CSU specializes in acquiring and operating mission-critical systems for niche industries: municipal billing, public safety systems, healthcare administration, utility management, education administration, transportation logistics, real estate management. These are boring, essential systems where correctness is a must have.

The characteristics are textbook deterministic:

• Must be accurate (billing errors create lawsuits)

• Must be compliant (regulatory violations shut you down)

• Must not fail (when the system goes down, operations stop)

• Rarely replaced (switching costs are big)

• Deeply embedded in customer workflows (often the system of record)

CSU explicitly avoids the things getting easily disrupted. They don’t chase:

• Speculative tech bets

• Platform plays with network effects

• Consumer software

• AI-first businesses

• “Growth at all costs” narratives

Their model is: buy boring, critical, deterministic software → improve margins → hold forever. The result is high ROIC, high free cash flow generation, customer retention rates close to 100%, and steady compounding.

They sell reliability. And reliability doesn’t get disrupted by tools that are probabilistic by nature.

The AI Impact on VMS

AI both threatens and helps software businesses, depending on how you look at it.

Why VMS moat is different from horizontal SaaS

There’s been a bunch of articles on Fintwit and X explaining how horizontal systems of record - Salesforce, Workday, HubSpot, are at risk of disruption. Not in 5 years but in the next 12 to 18 moths.

But VMS companies such as the ones sitting in Constellation’s portfolio made hundreds of them are different: marina management systems, ski resort software, construction bidding tools, library systems, etc.

The moat here isn’t just “we have your data.” It’s “we encoded 30 years of domain expertise into workflows that actually work for marina operators.” That’s harder for an agent to replicate than a generic CRM.

The customers are different (especially for Constellation)

Enterprise buyers with AI teams might say “let’s have an agent interact with our systems.” But the owner of a small marina in Wisconsin? They’re not spinning up AI agents. They’re not even thinking about AI. And even if they are, they still just want software that works, doesn’t break, and doesn’t require them to overthink it.

Constellation’s sweet spot is small businesses and mid-market companies that are risk-averse and technically unsophisticated. These are the last people who will experiment with replacing their mission-critical software with AI agents.

Switching costs in VMS

In horizontal SaaS, you might have 5 credible alternatives. In VMS, there’s often 1-2 players. If you run a cemetery and you’re using cemetery management software, switching means:

• Migrating decades of burial records

• Retraining staff on completely different workflows

• Risking compliance issues

• Dealing with integrations to other niche systems (plot mapping, funeral home integrations, etc.)

The “just copy the data to an agent” argument assumes the data is the whole product. But in VMS, the product is often the workflow, the integrations, and the fact that everyone in your industry uses it.

The computer use assumption is weakest here

Many of these articles I’ve come around in Fintwit assume computer use agents “just work” with existing systems. But VMS systems are often messy software with legacy codebases, weird UI patterns, industry-specific quirks. The idea that a general-purpose agent navigates this reliably feels less plausible than it does for clean, modern SaaS.

A Plausible Threat: Domain Expertise Commoditization

The traditional VMS moat rested partly on domain expertise. Building software for municipal utilities required understanding regulations, workflows, and compliance requirements that took years to accumulate. This created a knowledge barrier that protected incumbents.

AI, eventually, can potentially compress this learning curve. Big players (like hyperscalers or the AI labs - OpenAI and Anthropic ) could start seeing value in going after smaller vertical markets. By engaging industry domain experts, feeding their knowledge into models, and develop a “good enough” product delivering 80-90% of the value at 10-20% of the cost. For smaller VMS companies, especially those optimized for extraction rather than innovation, this is a threat.

Many PE-backed or serial acquirer-owned VMS businesses run on a simple playbook: acquire the software, reduce Operating costs to bare minimum, raise prices annually, harvest cash flows, repeat. Customers stay because switching is painful, not because the product is great. The software is often old, clunky, and under-invested.

If an AI first company can deliver a modern, intuitive product that solves the core workflow problem adequately, the incumbent’s switching cost moat starts eroding. It won’t happen overnight. These are still deterministic systems where errors matter, but the risk is real over a 5-10 year horizon.

There are other legit scenarios, where Constellation might be vulnerable:

1. The high-end VMS customers might defect first. Larger, more sophisticated customers in each vertical could be the ones who experiment with agents. If agents can handle 80% of use cases, the high-value customers might accept that trade-off.

2. The services revenue dries up. Many VMS companies have sticky services/implementation revenue. If agents make implementation easier, that revenue stream compresses (exactly the KPMG dynamic).

3. Pricing pressure becomes universal. Even if customers don’t switch, they’ll use the “AI should make this cheaper” argument. To some extent, Constellation’s model relies on maintaining pricing power in these niches.

The Opportunity: Productivity Enhancement and TAM Expansion

There’s also another side to this. AI can make VMS businesses more efficient and expand their addressable markets in ways that weren’t economically viable before.

VMS companies can use AI to:

• Automate tier-1 support, reducing cost-to-serve by 70-80%

• Build features faster, shortening development cycles from years to months

• Offer outcome-based pricing that captures more value from AI-enhanced productivity

• Expand into adjacent workflows that previously required too much custom development

For well-managed VMS businesses that reinvest adequately and maintain product quality, AI is a tool that could strengthen the moat rather than erode it. They can serve customers better, faster, and cheaper while maintaining the accuracy that customers require.

Constellation Software, with its decentralized structure and track record of acquiring underinvested VMS assets and improving them, seems well-positioned to leverage AI for operational enhancement while avoiding disruption risks.

I was playing around the other day with my AI chatbot, asking how software incumbents, particularly VMS players, could reinforce their products and services with AI. It actually came up with some pretty interesting ideas.

Software Darwinism: The Fittest Will Survive

The market sees an apocalypse. I see Darwinism.

Some software will get displaced by AI. Other software will thrive, using AI as a tool while maintaining the characteristics that made it valuable in the first place.

The way I see it, the winners will share some common traits:

Deterministic over probabilistic. Systems where precision matters will outlast systems where “good enough” is acceptable.

Must-have over nice-to-have. Mission-critical software where failure means business shutdown will survive. “Vitamin” software that provides marginal improvements will struggle.

Consolidators over point solutions. Customers want to reduce vendor count, not increase it. Platforms that solve multiple problems with one vendor relationship win.

Long contracts over short contracts. Multi-year agreements create switching cost moats and allow companies to be strategic about product development rather than chasing quarterly metrics.

High-value over low-value. Software that prevents $10 million problems can charge $100,000. Software that saves two hours per week can only charge $50/month. Guess which survives pricing pressure.

Change over static. Companies that continuously improve their products and embrace AI to enhance their offerings will win. Those staying put will disappear.

Vertical over horizontal in certain cases. Deep vertical expertise creates switching costs that horizontal platforms can’t replicate. But, only, if you’re actually reinvesting and innovating, not just extracting.

Their portfolio is deterministic, mission-critical, focused on consolidation within verticals, contract-heavy, high-value, and increasingly dynamic as they push operating groups to adopt AI for internal productivity.

The VMS businesses that are at risk? PE-backed extraction plays with minimal R&D, weak products, and customers staying only because switching is too painful. An AI startup offering 80% of the functionality at 30% of the price with a modern UI could absolutely disrupt those over the next decade.

But the well-managed VMS businesses, the ones actually serving customers, reinvesting in the product, and using AI to get better, have decades of runway ahead.

Time for Constellation Software and its teams to prove the doom sayers wrong. Again.

Thanks for following along,

—Nikotes

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I’ve increasingly been discussing the bifurcation in the current market, and frankly, the setup we are seeing entering 2026 is unlike anything I’ve encountered recently.

The AI narrative has effectively broken the market into two distinct camps: the “AI takes-it-all believers” who are bidding up semicaps and infrastructure plays to the moon, and the “AI skeptics” who are indiscriminately selling anything software-related. We are seeing quality names like ServiceNow down 40% and Constellation Software cut in half. The prevailing narrative of the crowd is that AI kills SaaS margins and turns software into a commodity.

I believe this view is fundamentally flawed. The market is pricing in structural decline for companies that are actually going through a period of adaptation within a broader secular growth trend.

That said, I’m not suggesting all software companies are created equal. Quite the opposite. Tech is an extremely competitive sector, and many SaaS companies, especially in North America, have traded for years at nosebleed valuations, coupled to excessive stock-based compensation and, in some cases, mediocre management teams more focused on personal incentives than long-term value creation. The market’s willingness to reward the sector masked a lot of weak fundamentals.

But there are also truly exceptional companies in this space. Businesses with real moats, durable customer relationships, and, most importantly, top management teams that have proven their ability to adapt and compound value over time. When the market starts behaving irrationally, as we’re seeing today, the risk–reward equation flips in favor of the patient investor.

The goal of this article is to unpack three companies where I believe the market has lost the plot: MercadoLibre, Amazon, and Constellation Software + spin-offs.

Constellation Software (CSU) and Spin-Offs — Buying the Panic

This is probably the most controversial pick, so I’ll start with it.

Constellation Software is down ~45% from its highs, now trading around CAD $2,850. The market is effectively pricing in an “AI apocalypse” for Vertical Market Software (VMS).

The debate on FinTwit went to extremes almost immediately this year.
For some, this is a once-in-a-decade opportunity.
For others, it’s proof that AI will break the entire model.

Let’s reset and remind ourselves what CSU actually does.

Constellation acquires and operates vertical market software: mission-critical systems of record for industries like utilities, the public sector, healthcare, education, and justice systems.

These aren’t flashy products, they never have been. Some still run on 30-year-old, ugly-ass user interfaces.

So what are these “ugly-ass” businesses, really?

They’re infrastructure.

• Billing systems for utilities

• Permitting workflows for municipalities

• Employee and payroll systems for school districts

• Case management software for courts

This is the software that cannot go down. But, why are they so sticky?

Because they’re deeply embedded in processes, regulation, and decades of accumulated data. The cost of the software itself is tiny relative to the customer’s total operating cost. Migration risk is high. Failure tolerance is close to zero.

Customers don’t rip these systems out. They layer on top of them and rely on their “IT trusted advisors”, i.e. Constellation.

One X user made me laugh the other day with this take:

He’s not wrong.

The “Death of Software” Narrative

The bear case is that AI makes software a commodity, allowing cheap competitors to displace CSU’s systems of record.

However, we must differentiate between “vibe coding” and “enterprise software.”

• Software development is just one part of the business.

• The Business involves sales, complex integrations, compliance, security, and customer success.

The skeptics don’t understand that B2B software stickiness comes from regulatory integration and process reliance, not just the code itself.

In verticals like public sector, utilities, and healthcare (CSU’s core), the risk of displacement is low because failure tolerance is zero. In my opinion, AI is more likely to be a productivity layer than a replacement.

The Key Questions for Investors

Forget abstract debates about whether AI is powerful or not. We already know it is. Focus on observable signals:

• Are contract cancellations increasing?

• Is recurring revenue growth slowing in core verticals?

• Is R&D spending spiking to stay competitive without margin payoff?

• Or is AI integrating into products and operations without eroding stability or margins?

Right now, none of the alarm bells are ringing. The fear is narrative-driven, not data-driven.

The Valuation Reset

We rarely get to buy a compounder of this quality at a discount.

• Current Valuation: ~22x Free Cash Flow available to shareholders (FCFA2S).

• Historical Returns: CSU has compounded capital at 20%+ annually for two decades.

My conservative case assumption at this valuation is 15%+ IRR.

If we run a reverse DCF at current levels, the market is clearly pricing in a sharp and sustained slowdown in growth.

That assumption deserves scrutiny. CSU’s management has proven to be intellectually honest, adaptive, and pragmatic for nearly three decades across multiple shifts in the software landscape. AI is simply the latest frontier. They’ve openly said they are “monitoring it closely” and are “obsessed” with understanding its impact. That doesn’t sound like a team sitting still, waiting to be disrupted.

The current narrative-driven distress is uncomfortable, no doubt. But it may also create opportunity.

At roughly 22x FCFAS, you’re buying CSU with a management team that has repeatedly proven its ability to allocate capital well during chaotic periods. That combination, compressed expectations, optionality on M&A, and elite capital allocation, offers a meaningful margin of safety.

The Long-Term Bet Among a Painful Narrative

Constellation’s model has never been tested like this. That’s fair. The AI era is uncharted territory.

But there’s another side to the story. CSU has adapted before. What investors are really struggling with today is narrative discomfort: the loss of a familiar, predictable playbook that felt safe for years.

And yet, distress narratives often creates opportunity.

In this “SaaS-mageddon” environment, you could picture how over-leveraged PE firms struggle to refinance. Or, how some founders may prefer to sell rather than compete in an AI-native world.

The result? A larger pool of potential acquisition targets and, potentially, better entry valuations. If you’re a disciplined capital allocator, like CSU, that’s exactly the setup you want.

I could be wrong. Major technological shifts can do more than break narratives, they can permanently damage even great businesses. I don’t dismiss that risk.

But my conviction rests on CSU’s structure: decades of aligning returns-focused operators with pragmatic, high-quality capital allocation. If any organization is built to navigate uncertainty like this, it’s Constellation.

If you want to go deeper on this name, my views are largely reflected on this Deep Dive Brief trilogy:

• 🔗 Part I: Constellation Software Capital Allocation Outlook

• 🔗 Part II: Constellation Software and AI

• 🔗 Part III: How to Build a DCF for Serial Acquirers Like Constellation Software (includes DCF for CSU)

As for the spin-offs, Topicus and Lumine, I also wrote two pieces last year:

• 🔗 A Hidden Gem Deep Dive Brief: Topicus

• 🔗 A Hidden Gem Deep Dive Brief: Lumine Group

Mercado Libre (MELI) — The LATAM Digital Economy Builder Disguised as E-commerce

Many investors look at Mercado Libre (Meli) and see “the Amazon of Latin America.” If you view it through that lens, you are missing the real story.

Meli is not only another e-commerce company in LATAM. It has been building, for over two decades, the digital economy of a continent with 600+ million people.

I’ve been writing extensively on this name since I started Expanse Stocks and my readers know the high conviction I have been building on this name. This is reflected on my latest Deep Dive Brief trilogy I’ve published recently in the second half of 2025:

• 🔗 Part I: Mercado Libre’s Origin Story

• 🔗 Part II: Mercado Libre’s Flywheel (includes DCF model)

• 🔗 Part III: Deconstructing Mercado Libre’s Optionality

The Valuation Disconnect

Let’s look at what’s currently priced in. We’re talking about a company with a ~$120 billion market cap trading at roughly 24x forward EBIT, an all-time low valuation.

A compression of this magnitude typically signals a business that’s hitting saturation or facing structural decline. But the underlying data tells a very different story:

• E-commerce penetration in LatAm: ~14% (vs. ~26% in the US and ~30% in China)

• TAM penetration: Meli has captured only ~2% of its ~$1.3 trillion serviceable market

So here’s the disconnect. You have a business growing revenue north of 30% annually (and recently, reaccelerating in key regions), the only company in history to compound at 20%+ YoY for 24 consecutive years, still sitting at 2% market penetration, yet trading at what looks like a terminal-decline multiple.

When fundamentals and valuation diverge this much, the market is offering a gift.

The Moat: Chaos is the Advantage

The bear case usually revolves around macro volatility or competition from Amazon and Shopee. However, I believe the specific challenges of Latin America act as a barrier to entry that protects Meli’s returns.

As I explained in the first part of my deep dive brief trilogy, Meli didn’t just copy the ebay or Amazon model like many still claim, they took the high risk to built what didn’t exist from the ground up.

1. Mercado Pago (Fintech) - 23 years old: Created to solve the lack of trust in a cash-dominated economy, now processing $200+ billion annually.

2. Mercado Envíos (Logistics) - 13 years old: A network spanning 18 countries with 22 fulfillment centers and 70,000 employees.

Even if a competitor arrived with unlimited capital today, they could not replicate the “muscle memory” Meli has developed by navigating two decades of regional instability. Operating in chaos is not a risk factor for MELI; it is their competitive advantage.

With gross margins trending toward 40% and a leadership transition that ensures continuity (Ariel Szarfsztejn taking the helm), the drivers for earnings growth are robust. The “flywheel” effect is real here: the marketplace drives payment volume, which provides data for lending (multi-billion $ credit portfolio), which reinforces marketplace usage.

Amazon (AMZN) — The Re-Rating Candidate

Amazon has arguably been “dead money” for five years, underperforming its big tech peers. Investors are fatigued. But as I have discussed in previous articles, investor fatigue often creates the best entry points.

The Sum-of-the-Parts Opportunity

The thesis here is simple: the market is mispricing the components and the optionality.

AWS: Projected to hit $170B in ARR with reaccelerated top line growth.

The Valuation: If you apply a 15x P/S multiple to AWS (consistent with peers like Microsoft in recent years), the math implies you’re almost getting the rest of Amazon for free.

Read that again. The entire e-commerce empire, the advertising business, the logistics network, Prime, MGM, Whole Foods, Kuiper, the Trainium chip unit… all of it priced at zero if AWS trades at peer multiples.

The Margin Story

The narrative that retail is a “low-margin” business is outdated in my opinion. Amazon is undergoing a margin revolution:

• Robotics and automation driving fulfillment efficiency

• Last-mile logistics optimization reducing delivery costs per package

• Advertising revenue (high-margin) scaling inside the e-commerce flywheel

We are seeing a setup where retail margins expand due to automation, while the high-margin advertising business scales inside the flywheel.

There is a consensus building that 2026 will be the year of acceleration for both AWS revenue and retail margins. Although I don’t really like the “consensus” in investing, I’ve got to agree with this take.

Fears of AI disrupting Amazon’s search dominance are valid but likely overblown in the medium term. Even if discovery shifts to AI agents away from Amazon’s interface (a real risk, by the way), the logistics moat remains untouchable. Nobody else can deliver at this speed and cost structure. Discovery might fragment, but fulfillment doesn’t. The physical last-mile delivery, which Amazon dominates, cannot be digitized.

Trainium: The Chip Asset

AWS’s custom silicon unit is a massive long-term margin lever that almost nobody talks about. As AI infrastructure scales, hyperscalers with proprietary chips maintain pricing power and avoid full dependency on NVIDIA.

Trainium is a strategic asset that keeps AWS competitive in the AI buildout without getting crushed on component costs and margins.

The Optionality Stack

Kuiper: Satellite internet constellation. Direct Starlink competitor. Massive TAM if execution lands (and early signs suggest it will).

Advertising: Already a top-3 digital ad platform. High-intent commerce data. Growing faster than the core retail business. Analyst estimates suggest advertising revenue grows from $68 billion in 2025 to $142 billion by 2030, a 16% CAGR that keeps compounding on top of everything else.

The overlooked Prime ecosystem: 200 million+ subscribers and counting. Sticky, recurring, high lifetime value. The switching cost for a Prime member isn’t not only about losing free shipping, it’s losing the entire integrated experience.

It seems like the market is tired of hearing about “Amazon's potential”. That exhaustion is my opportunity.

Conclusion

My 2026 playbook won’t be about chasing the hot AI infrastructure trades. I’m already well positioned there and have been for years. Instead, it’s about spotting where the market has swung the pendulum too far the other way.

Mercado Libre. Constellation Software. Amazon.

Growth, quality, and optionality. All trading at mispriced valuations.

Thanks for following along,
— Nikotes

To my Expanse Readers,

As we close out 2025, I find myself reflecting not just on the year’s returns, but on something more fundamental: what kind of investor I want to be.

This year marked a turning point for the Expanse Stocks portfolio—not because of any single position or market call, but because I finally committed to a principle I’d long understood intellectually but struggled to implement: concentrate on what you believe in, and give those ideas time to compound.

The result is a portfolio that looks different from where we started the year. Sixteen names have become twelve. Diversification for its own sake has given way to conviction-weighted sizing. And the recurring theme is clear: this is a portfolio built around secular trends I believe will define the next decade.

But before diving into where we stand today, let me take you through the journey of how we got here.

Topics I’ll Cover

🔹 The First Half: Strength and Soul-Searching
🔹 The Transition: From Diversification to Concentration
🔹 Lessons from 2025: What I’m Taking Forward
🔹 A Personal Note: Why This Matters

🔐 For Paid Subscribers:
🔹 The Portfolio Today: Twelve Names, Four Themes
🔹 What This Portfolio Really Represents
🔹 The Risks I’m Accepting
🔹 Final Thoughts
🔹 Looking Ahead: Defining “Thesis Breaks”

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The First Half: Strength and Soul-Searching

When I wrote the 🔗 Semi-Annual Letter in June, the portfolio was performing well. We held quality businesses with strong competitive positions. The moats were real, the management teams capable, and the secular tailwinds intact.

Yet something felt off.

I had built what looked like a well-diversified portfolio on paper: software, semiconductors, consumer brands, industrial tech, healthcare, and financials. Spanning 16 positions plus two spin-offs. It checked all the conventional boxes. But as I prepared for my wedding and our trip through Namibia, South Africa, and Mauritius, I kept coming back to a nagging question: Was I building the portfolio I wanted to own for the next decade, or was I just building what looked safe?

That question became impossible to ignore when I came back home after those weeks away. When you step back from the daily market noise and actually think about where you want to allocate capital for the long term, clarity tends to show up itself.

The thing is, not all quality businesses are created equal. Some companies you own because they’re objectively good. Others you own because they genuinely excite you and because you believe in the thesis deeply enough to hold through 40% drawdowns, because you’re willing to spend weekends reading about their industry dynamics, because you’d happily own them for a decade.

I realized I had too many of the former and not enough of the latter.

The Transition: From Diversification to Concentration

The second half of 2025 was about making tough decisions. I wasn’t dissatisfied with the businesses I owned, most were excellent companies. But I was dissatisfied with my conviction levels across the portfolio.

Here’s what became clear: in a concentrated portfolio, every position needs to matter. If I’m going to own 10-15 names instead of 30, each one needs to represent a genuine edge—a thesis I’ve spent months developing, a business model I understand deeply, a management team I trust implicitly.

This led to some painful exits:

Hermès was objectively one of the finest businesses in the world. Unmatched brand power, generational pricing power, capital-light operations. But I had to be honest with myself: did I want to spend the next decade studying luxury goods? Does it really excite me? The answer was no. It was a great business for someone else’s portfolio, not mine.

Danaher, Atlas Copco, and Investor AB fell into a similar category. Quality serial acquirers with strong track records, trading at what looked like attractive valuations relative to their history. But here’s the thing about “relative value” as an investment thesis: it’s never compelling enough to hold through volatility. When a position drops 25%, you need conviction in the underlying business to add more or even just hold steady. “It looks cheap on a 5-year P/E chart” doesn’t cut it.

The truth is that valuation alone is a weak thesis for a compounder. If a business is truly exceptional, arguing about whether it should trade at 26x or 32x earnings is missing the point. The real question is: will this business compound intrinsic value at 15-20% annually for the next decade? If yes, the entry multiple matters far less than most investors think.

Meanwhile, I was adding to and initiating positions that, on conventional metrics, looked “expensive”:

Intuitive Surgical at what many would consider a premium valuation. But the business model, razor-and-blade recurring revenue from surgical procedures, a dominant competitive position in robotic surgery, and a massive runway as penetration moves from ~12% to potentially 50%+ over the next decade, justified the price. This was about buying durability and growth.

And I substantially increased allocations to my highest-conviction ideas: Constellation Software, ASML, Cadence, Google, and MercadoLibre. These weren’t positions I was trimming for “risk management.” These were positions where, if anything, I regretted not owning more.

Lessons from 2025: What I’m Taking Forward

This year taught me several lessons that will shape how I invest going forward:

1. Conviction Matters More Than Diversification

There’s a difference between owning something because it’s objectively good and owning something because you believe in it deeply. The former might help you sleep at night, but the latter is what generates superior returns.

I’d rather own 8% of my best idea than 2% each of my top four ideas. Concentration forces clarity. It forces me to think harder about each position, to monitor them more closely, to actually understand the businesses rather than just checking boxes.

2. Valuation Is a Weak Thesis for Compounders

I spent too much of this year worrying about whether certain positions looked “expensive” on traditional metrics. The reality is that great businesses often look expensive because the market correctly anticipates years of strong performance.

Constellation Software has looked expensive for a decade (not so much today). ASML, Heico or Amazon have looked expensive for years. If you waited for these businesses to trade at “fair value,” you missed some of the best compounding opportunities available.

The lesson: focus on whether the business can compound intrinsic value at high rates, not whether the current multiple looks reasonable on a historical chart.

3. Position Sizing Should Reflect Conviction

This seems obvious, but it’s surprisingly hard to implement. The natural tendency is to size positions for comfort. Add a little here, trim a little there, keep everything balanced.

But if you genuinely believe in a thesis, why would you limit your exposure? If I think Constellation Software can compound at 18% annually for the next decade with high confidence, why wouldn’t that be an 11% position instead of 5%?

The current portfolio reflects this principle: my highest-conviction ideas are 11-12% positions. My lowest-conviction idea is 5.3%.

4. Only Own What Excites You

This might be the most important lesson of the year. In a concentrated portfolio, excitement equals conviction equals holding power.

When one of my positions drops 35%, will I have the conviction to hold or add? Absolutely. Because I believe in the long-term thesis and I’m genuinely interested in following these businesses.

If I still owned Danaher or Atlas Copco and they dropped 35%, would I have the same reaction? Probably not. I’d be white-knuckling through volatility on positions I added for “balance” rather than conviction.

This is why the portfolio feels right for the first time: every position excites me. I want to read about AI and tech related advancements, M&A acquisition strategies in some of the best capital allocator engines over the last two decades, robotic surgery adoption rates, and fast growing emerging markets fintech penetration.

If you don’t find your portfolio interesting, you’re probably in the wrong businesses.

5. Mistakes of Omission Matter as Much as Mistakes of Commission

I never bought NVIDIA or Broadcom when I had the chance. Not because I didn’t understand them, but because I didn’t act.

These mistakes don’t show up on your portfolio statement, but they’re just as real. They hide in the research you never did, the skepticism that went too far, the ideas you liked but didn’t pull the trigger on.

I’ve started journaling more, keeping files with ideas I almost bought and revisiting them regularly to spot patterns and blind spots. The goal isn’t to beat myself up over missed opportunities, but to understand what held me back and whether those concerns were valid.

A Personal Note: Why This Matters

2025 was a transformative year, not only in my investing style, but at a personal level.

Getting married and traveling through Africa gave me perspective on what really matters in life. It’s not about optimizing every dollar or maximizing portfolio returns at all costs.

Money is a tool, not a goal. Wealth should maximize life fulfillment, not be hoarded endlessly.

That philosophy shapes how I think about this portfolio. I’m 33 and these are some of the most vibrant years of my life. I’m not deferring gratification until some distant retirement. I’m investing wisely for long-term security while also allocating capital toward what matters most—traveling, exploring, learning, spending quality time with family and the people I love.

The portfolio I’ve built reflects this balance. It’s concentrated enough to generate superior returns if the theses play out, but it’s also composed of businesses I genuinely enjoy following. Investing isn’t a chore, it’s something I find intellectually stimulating and rewarding.

If there’s one piece of advice I’d give to anyone reading this: build a portfolio that excites you. Not one that looks safe on paper or checks all the conventional boxes, but one that represents your genuine beliefs about the future and keeps you intellectually engaged.

That’s the only way you’ll have the conviction to hold through inevitable drawdowns. That’s the only way you’ll compound capital at rates that exceed the market over decades.

The Portfolio Today: Twelve Names, Four Themes

As we enter 2026, the Expanse Stocks portfolio is concentrated around four core themes that represent my highest-conviction views on the next decade.

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Why Industrial Moats Matter

In an age dominated by technology, it’s easy to overlook the compounders shaping our physical world. Yet moats exist here too: durable, understated and built, not with code, but with cost advantages, regulatory know-how, and operating discipline.

Industrial moats are forged in procurement relationships, proprietary processes, aftermarket dominance, or via decade-long capital allocation programs that scale globally without diluting quality.

True moaty industrials are arguably some of the most durable businesses out there, which is precisely why they deserve attention. The following six names:

Copart, Deere, LIFCO, HEICO & TransDigm, and Atlas Copco, each possess enduring structural advantages.

Let’s take a closer look at what makes them stand out.

Copart (CPRT) The Network Effect in Wreckage

Copart is a textbook example of how even scrapyards can build a network effect moat. Its digital salvage auction platform connects insurers, auto body shops, junkyards, exporters, and rebuilders in a high-frequency marketplace optimized by decades of data.

The more sellers list with Copart, the more buyers show up. The more buyers show up, the higher the clearing prices, and the better the economics for insurers. This self-reinforcing loop is tough to replicate. Logistics, local yards, title expertise, and proprietary bidding algorithms reinforce the advantage.

Returns on capital consistently exceed 20%, margins are stable, and expansion abroad (notably in the UK and Germany) opens runway for growth. In a world shifting to electric vehicles (which may be harder and more expensive to repair), total loss frequency could even rise benefiting Copart further.

The fundamentals speak for themselves:

✅ Growth & durability
✅ Standout margins
✅ Capital efficiency
✅ Zero leverage, zero dilution

And the last 10 years of shareholder returns tell the same story.

Deere & Company (DE) The Embedded Ecosystem on the Farm

With a 180+ year history, Deere is an equipment manufacturer but it’s also a data-rich, recurring revenue ecosystem. Its moat stems from a blend of brand loyalty, dealer relationships, and increasingly, software embedded in its machinery.

Precision agriculture, where every tractor and combine uploads agronomic data to the cloud, creates software-like switching costs. Farmers using Deere’s Operations Center and subscription-based features (like yield mapping or automated guidance) are unlikely to rip and replace with a competitor, especially when dealers provide localized service, parts, and financing.

Recurring parts and service revenue, which now make up nearly 40% of profits, stabilize the business across cycles. Deere is transforming from an OEM to a platform company with industrial-grade retention.

For those watching the technicals, the setup looks primed and the past 10-year CAGR doesn’t disappoint either.

LIFCO AB (LIFCO) The Serial Acquirer with Swedish Discipline

A serial acquirer powerhouse from Sweden, LIFCO AB owns around 200 businesses, acquired one at a time, usually under the radar, and often in niche verticals where competition is limited and pricing power is durable.

Its decentralized model, Constellation Software style, allows subsidiaries to retain independence while benefiting from capital, procurement, and governance best practices. Most importantly, LIFCO is highly selective. It avoids bidding wars, prioritizes high ROCE, and rarely overpays.

Though organic growth slowed recently, LIFCO’s track record over the past two decades is enviable: double-digit top line growth (+15% over the last 5 years → 5% organic + 10% from M&A), EBIT margins >15% and EBITDA margins at 25%, returns on capital well above peers (ROCE >20%), and zero dilution.

The business reinvests prudently and composes its value slowly but reliably. It is a textbook compounder and the Sweden’s answer to Danaher or Constellation Software, but in steel screws, dental handpieces, and waste handling systems.

Heico (HEI) & TransDigm (TDG) Aerospace Moats at 30,000 Feet

Heico and TransDigm are often spoken of in the same breath and for good reason. Both dominate niches in aerospace parts and subsystems, with business models that benefit from regulatory entrenchment, high switching costs, and aftermarket pricing power.

Heico specializes in FAA-approved replacement parts that offer airlines a lower-cost alternative to OEM components. Its moat is built on regulatory certifications and a disciplined acquisition strategy targeting niche, engineering-intensive companies with products that have multi-decade long lifespans.

What I find most compelling about Heico isn’t just its competitive position but its leadership. The Mendelson family has run the company for decades, fostering a famously conservative, long-term-oriented, and customer-focused culture that prizes steady, sustainable growth. I unpack this in detail in my latest 🔗 Deep Dive Brief: Heico.

TransDigm, by contrast, takes a more aggressive tack. Led by renowned capital allocator Nick Howley, it deploys significant leverage to fund large, transformative acquisitions. The culture is unapologetically profit-driven and highly decentralized, zeroing in on proprietary, mission-critical aerospace parts where it enjoys >90% sole-source revenue and extraordinary pricing power.

Its focus is on components that are essential yet represent a small fraction of the total system cost (seat belts, valves, actuators, connectors), making price increases palatable. Once a part is designed into an aircraft, it tends to stay there for decades, creating high-margin, recurring replacement revenue.

Both companies operate with gross margins north of 50% and return capital to shareholders via buybacks and debt optimization. The aftermarket dominance, combined with long product cycles and regulatory hurdles, create formidable moats in an industry that prizes reliability and certification over novelty.

Probably the two highest quality compounders in the aerospace industry and they’ve proved it to shareholders. Below, HEI and TDG returns over the last 8 years vs QQQ:

Atlas Copco (ATCO) Quiet Dominance in Compression and Vacuum

Sweden’s Atlas Copco is perhaps the ultimate industrial compounder.

Its businesses involve compressed air, vacuum technology, and industrial tools. It might seem mundane, but they are mission-critical to semiconductor fabs, hospitals, automotive plants, and nearly every manufacturing process globally. Roughly 40% of revenue is recurring, through service, consumables, and rental.

What sets Atlas apart is its obsession with niche leadership. Like a platform company, it has mastered the art of identifying sub-industries where it can dominate and acquires or builds its way to #1 or #2 positions. Its ROCE has averaged above 30%, and even as it scales globally, margin stability and capital efficiency remain exceptional.

Atlas’s decentralized, entrepreneurial structure, paired with world-class capital allocation, ensures that even as it grows to a $78B giant, it still behaves like a nimble acquirer of niche moats.

Final Thoughts: Moats Built in Metal

Moats in the industrial world are harder to build and often harder to erode.

They come from entrenched physical asset networks, decades-long customer relationships, regulatory know-how, and operational excellence.

They are hard to find but they do exist. And when paired with intelligent capital allocation, they can generate extraordinary long-term returns.

Copart, Deere, LIFCO, Heico, TransDigm, and Atlas Copco are prime examples. Each operates in a large market yet has carved out a defensible niche, protected by structural advantages competitors struggle to replicate.

If the past two decades is any indication, these companies are likely to keep compounding quietly, reliably and moated.

Thanks for following along,
—Nikotes

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The real opportunity lies in the digital infrastructure enabling Japan's next economic phase. The analog world is ending, and the companies building the digital bridge are trading like it's still 2008.

I would even go as far as to say that missing Japan's SaaS revolution might be this decade's equivalent of missing China's manufacturing boom or India's IT services explosion. The main difference? This time, you're getting it at a discount.

In the second part of this series, I will uncover one case study on one of the most successful pure-play SaaS companies in Japan I recently added to the watchlist at the 🔗 Portfolio Corner.

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After digging deeper through podcasts, Japan business literature, Japanese companies’ IR websites, and some wonderful information shared by great investors experts on X (e.g. 🔗 Made In Japan), my view is also that this time really looks different.

A confluence of structural reforms, demographic necessity, and a massive technological catch-up is creating what I believe to be one of the most compelling, under-the-radar investment opportunities for the next decade, particularly within the country's (still) nascent Software-as-a-Service (SaaS) sector.

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The Multi-Billion Digital Gap Creates Generational Opportunity

While Warren Buffett continues doubling down on Japanese trading houses with "no plans to sell" for the next 50 years (true story, source: 🔗 Investopedia), there's a better story unfolding behind the scenes of Japan's massive economy.

The other day I read a piece on Japanese software business culture, that made me laugh. Picture this: “Taro, a mid-level manager in Tokyo, starts his morning paying with his phone at a modern POS system, then walks past a cash-only stationery shop, arrives at work to input data from faxed orders into a cloud accounting platform, and ends his day at a government office where digital ID cards coexist with paper forms.”

This isn't contradictory, it is Japan's reality, and it potentially represents one of the most undervalued investment opportunities in global tech today.

The Numbers Don't Lie

Japan ranks 31st globally in digital competitiveness. For the world's fourth-largest economy, I’d would call it embarrassing but I prefer seeing it as an opportunity.

Consider the scale: Japan's 99.7% Small and Medium Enterprise (SME) market has only 30-ish% SaaS adoption. Around 70% of manufacturing orders still arrive by fax. The Japanese SaaS market sits at roughly $11 billion, representing just 4% of total IT spending versus 15-18% in the US. That's a $200+ billion addressable market sitting there, waiting.

But here's where it gets interesting (and urgent): Japan's Ministry of Economy projects an $80 billion annual economic loss by 2025, dubbed the "2025 Digital Cliff", if legacy systems aren't modernized. Nearly 60% of critical systems will be over 20 years old by then, with the expertise to maintain them retiring en masse.

The government is concerned and throwing money at the problem. The Digital Agency launched with a $660 million grant program, 130 cloud migrations completed, and aggressive “My Number” card adoption (71% increase in cardholders in a single year). This isn't gradual change – it's systematic transformation.

The Small-Cap SaaS Goldmine

While true that Berkshire and other big financial institutions can't touch small caps due to size constraints, this creates a structural advantage for everyone else. Japanese small-cap SaaS companies are trading at steep discounts versus US counterparts, despite comparable growth rates and superior retention metrics.

The recurring revenue model works differently in Japan. That consensus-driven decision-making process that seems slow? It creates customer stickiness that US SaaS companies can only dream of. Once adopted, these solutions become deeply integrated into workflows, generating extraordinarily low churn rates and high lifetime values.

The financial dynamics looks compelling:

• Overall SaaS market growing 10-13% CAGR through 2032

• High-growth segments (cloud integrations, accounting) hitting 35-45% CAGR

• Operating leverage accelerating as fixed costs spread across growing subscriber bases

• 200% increase in companies achieving 20%+ ROIC over the past decade

Framework for Success: The Localization Moat

Foreign investors, like me, have consistently underestimated that getting into Japanese SaaS and making it right isn't just about translation. It's about deep localization: understanding nemawashi (consensus-building), integrating with legacy hanko stamp workflows, and building solutions that align with monozukuri (craftsmanship) principles. 🔗 Source: Podobas

Companies like Money Forward (3994.T) and Freee (4478.T) are more than accounting platforms as they provide a cultural Japenese bridge between analog business practices and digital efficiency. This creates defensive moats that global competitors struggle to breach.

The thing is that this localization creates both opportunity and limitation. While domestic focus limits international expansion potential, it also means these companies are perfectly positioned to capture Japan's massive digital transformation without foreign competition.

The Counterargument (And Why It's Wrong)

"But Japan's been promising digital transformation for decades"

While true, this doesn't change the fact that three catalysts make this time different:

1. Demographic crisis: 30% of the population is over 65, creating 11 million worker shortfall projections

2. Government mandate: Digital Agency is encouraging change but also mandating it

3. Economic necessity: The $80 billion Digital Cliff is a present reality

"Cultural resistance will slow adoption!"

Yes, initial adoption might take longer; but once implemented, and it is already underway, software solutions achieve retention rates that could make the competitive US SaaS sector weep with envy.

The Active Catalyst: M&A Acceleration

The Kaonavi acquisition by U.S.-based private equity firm Carlyle Group (🔗 Source) for $325 million in December 2023 wasn't just a one-time thing, but a preview of what’s coming. Large Japanese and International corporations with business in the country are racing to acquire digital capabilities, while private equity recognizes the undervaluation gap.

This creates multiple exit pathways for investors: strategic acquisitions by domestic giants, private equity buyouts, or international expansion as these companies scale their localized advantages.

Investment Framework: What to Look For

Quality indicators:

• Vertical specialization (healthcare, construction, logistics)

• High customer retention rates (>95%)

• Recurring revenue models with predictable cash flows

• Strong balance sheets with low debt

• Management teams with both technical and cultural expertise

Red flags:

• Heavy dependence on project-based revenue

• Aggressive international expansion without domestic scale

• Underinvestment in cybersecurity (critical as threats increase)

• Weak pricing power in the SME segment

The Reality Check

I’d argue finding these opportunities is not without risks. Talent scarcity remains severe (2.3 million digital worker gap by 2026), integration with legacy systems creates implementation complexity, and the SME market's price sensitivity limits monetization potential.

But the thing is these challenges create the very inefficiencies that generate outsized returns for patient capital and the market has been pricing in all these problems (with pretty low multiples) while ignoring the solutions.

The Takeaway

Japan's SaaS transformation is a multi-year structural shift backed by government mandate, demographic necessity, and a multi-billion cliff in economic urgency. The small-cap segment offers exposure to this transformation at valuations that make little sense relative to fundamentals.

The real opportunity lies in the digital infrastructure enabling Japan's next economic phase. The analog world is ending, and some of the companies building the digital bridge are trading like it's still 2008.

I would even go as far as to say that missing Japan's SaaS revolution might be this decade's equivalent of missing China's manufacturing boom or India's IT services explosion. The only difference? This time, you're getting it at a discount.

In the second part of this series, I will uncover one case study on one of the most successful pure-play SaaS companies in Japan I’ve recently added to the Watchlist, available in the 🔗 Portfolio Corner.

Thanks for following along,

—Nikotes

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By Nikotes, author of Expanse Stocks

Investing humbles you. You can do all the research, build a solid thesis, follow the numbers, and still get it wrong.

I’ve made plenty of mistakes over the years. Some technical, some emotional, and some I didn’t even spot until later. But the biggest lesson since I started trading in 2018, and investing a few years after, is this: the only real failure is not learning.

This is a reflection on where I’ve stumbled, what I’ve learned, and how those lessons have shaped my 🔗 Investment Philosophy today.

Confusing Results with Process

We all like stories where a stock doubles and everyone claims credit. But what if that gain came from a lucky earnings beat or market hype, not a solid thesis? And what if a losing position was based on sound reasoning, but just didn’t work out?

One of the most valuable shifts I’ve made as an investor is separating results from process. I can’t control market randomness. Investing is about probabilities, not certainties. What I can control is how I think, research, and invest.

It’s easy to let short-term results shake your confidence, but real progress comes from reviewing your decisions. When something works, I ask:

• Did the stock rise for the reasons I expected?

• Was my position size in line with my conviction?

• Did I miss a better opportunity?

When something doesn’t work, I try to honestly decide if my process was flawed or if it was just bad luck.

A great perspective on this came from a book I recently read: The Psychology of Money by Morgan Housel. It’s a must-read for anyone investing their own money. You can find more resources and ideas like this in the 🔗 Resources corner of Expanse Stocks (open to everyone).

Letting Losers Run

There were times I held onto underperformers simply because I was emotionally attached or too proud to admit I was wrong. Complacency played a role too.

The reality is that a stock down 30-40% is often telling you something. Sometimes the market is overreacting, but sometimes your thesis is broken. I made plenty of mistakes during the 2021 bubble, e.g. NIO and ARRY come to mind. Truthfully, I was a different investor back then (if you could even call me that, more trader/gambler than anything). Selling could’ve been less painful if I’d had a process to re-evaluate sooner.

These days, I follow a mental rule: if a position drops 20% from my cost basis (excluding broad market selloffs), I reassess the thesis. I ask questions like:

• Has something fundamentally changed?

• Is my conviction still justified?

This rule saved me from complacency recently (last year) with a high-quality name like ASML. After the drop, I re-evaluated. I chose not to sell, but it forced me to revisit my assumptions and stay intentional, not passive.

And… Not Letting Winners Run

Just as painful as holding onto losers too long is selling winners too early. It’s tempting to lock in a gain, especially if a stock pops 50+% in a short period. You feel smart. You feel in control. But in many cases, I left massive upside on the table.

I’ve got a few of these too, but one painful example was: Constellation Software. I bought it as a high-quality, high-recurring model software compounder back in Nov 2022, and when it was up ~35%, I trimmed thinking it had “run too far.” One year later, and it was up another 60%. Nothing about the business had deteriorated. On the contrary, it had strengthened.

This taught me an important lesson: great businesses often continue being great, why sell?

I’ve come to adopt a mindset of “sell only if the thesis is broken or the opportunity cost is overwhelming.” Gains alone aren’t a sell signal. Now, I aim to let my winners surprise me to the upside.

To sum up both takes above and quoting Peter Lynch:

"Selling your winners and holding your losers is like cutting the flowers and watering the weeds."

Underinvesting in Highest Convictions

This is often underappreciated, and a silent killer of an investor’s portfolio returns. It’s easy to get excited about a stock and add it to the portfolio. But not sizing it appropriately, that’s a missed opportunity.

I’ve made this mistake more than once. Amazon and Constellation Software back in 2022 were two. I had high conviction and a solid setup, but I sized them modestly. Meanwhile, I added to lagging names that hadn’t earned their spot like Datadog or Snowflake, which I ended up selling back in 2024 and 2022 respectively (the latter for a 25% loss).

These experiences taught me that sizing should reflect conviction. Not every idea deserves equal weight. If I believe in a business, the allocation should show it.

Today, I run a concentrated portfolio of around 15–25 names, where conviction and quality drive position sizing, not diversification for its own sake.

Overrating Top-Line High Growth

I’ve also made the mistake of chasing exciting revenue growth without questioning the quality or sustainability behind it.

Just because a company is growing 30%+ on the top line doesn’t mean it’s creating value. If that growth comes at the expense of margins, free cash flow, or capital efficiency (low ROIC or ROIIC relative to cost of capital), it can actually destroy value. I go deeper on that here 🔗 Understanding ROIC, ROIIC, and ROCE: Measuring Capital Efficiency.

I fell into this trap during the Covid bubble by investing in businesses with impressive customer growth or flashy launches but no real moat or path to profitability. Growth for growth’s sake is tempting, but risky.

Today, I look for profitable durable growth, as I outlined in 🔗 Understanding Growth & Its Key Drivers. Not just revenue expansion, but growth supported by attractive unit economics, high returns on incremental invested capital, and disciplined execution. It’s not how fast you grow, it’s what you earn on each new dollar invested.

Ignoring Mistakes of Omission

I never bought Nvidia or Broadcom. Not because I didn’t know they existed but because I didn’t act when I had a chance.

These are the mistakes you don’t see on your portfolio statement, but they’re just as real and as important. They hide in the research you never did, the skepticism that went too far, the ideas you liked but didn’t pull the trigger on.

Now I journal more. I keep files with ideas I almost bought and revisit them regularly to spot patterns and blind spots. It’s not only about what we did; but also, what we didn’t do and why.

What These Mistakes Teach Me

Each of these experiences left a lesson; some I’ve applied, others I’m still working on:

✅ Process matters more than results
✅ Patience is powerful
✅ Position sizing is strategy, not afterthought
✅ Humility beats ego every time
✅ Reflection is essential and often overlooked

Final Thoughts: I Still Make Mistakes

It’s easy to only talk about the wins. But it’s the mistakes, when you actually learn from them, that move the needle.

I still make them. I probably always will. But I make fewer now. And more importantly, I make different ones. That’s progress.

If you’ve had your share of missteps, you’re not alone. The goal isn’t perfection. It’s being a bit better, a bit wiser, and more honest with yourself.

“If you want to become a better investor, lose money. Just not too much.”

That’s something my father, a self-made man and better investor than me, once told me.

Here’s to the lessons. And to keeping at it.

– Nikotes

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TABLE OF CONTENTS

1. Portfolio Strengths and Tailwinds

   🔐 For Paid Subscribers:

2. Risk Review & Potential Improvements

3. Portfolio Rebalancing Ideas

4. Factor Exposure, Macro Regime & Stress Testing Results

5. Portfolio Scorecard: A Company-by-Company View

6. Final Take: What we believe in, What’s our edge as individual investors

To Our Expanse Readers,

Welcome to the mid-year review for 2025.

The first half of this year has once again echoed the tone set by much of this decade—a paradoxical landscape of tremendous technological momentum (AI), intertwined with persistent threads of macroeconomic and geopolitical uncertainty. Volatility has remained the norm, not the exception.

In such an environment, my 🔗 Investing Philosophy hasn’t just endured, but it’s become more relevant than ever: to patiently craft and own a concentrated portfolio of the world’s most durable, innovative, and well-managed businesses.

My strategy as an investor is not to predict the unpredictable swings of the market, but to identify and partner with companies possessing enduring moats advantages, exceptional capital allocation skills, and exposure to long-term secular tailwinds. This letter will provide a transparent look at how this philosophy is embodied in the Expanse 🔗 Portfolio today, review its inherent strengths and risks, and discuss my thinking on its future positioning.

💍 On a Personal Note

The close of H1 2025 also marked a life-changing event: I got married and immediately embarked on a once-in-a-lifetime adventure across Namibia, South Africa, and Mauritius 🌎. It was an unforgettable trip with my life partner, filled with new perspectives.

Honestly? I’ve never felt more grounded to continue building Expanse Stocks. So, before we dive into charts and strategy, I thought I’d share a few personal snapshots of that happiness:

Thank you for reading, for your trust, and for being part of this journey.
Let’s get into it. 👇

— Nikotes

The Expanse Philosophy in Practice: Strengths & Enduring Tailwinds

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By Nikotes, Author of Expanse Stocks

This is my second Annual Special piece since I launched Expanse Stocks last year, and it took me a while to sit down and actually write this. Not because I don’t know what I believe, but because investing, or at least good investing, isn’t rigid. My philosophy isn’t carved in stone. It’s a direction I try to orient myself toward, rather than a checklist I’ve mastered.

But as Expanse Stocks continues to grow, I think it’s worth putting pen to paper and sharing what guides the decisions behind the 🔗 Portfolio I manage and the businesses I study. If you’ve been with me for a while, you’ve probably seen these principles in action. If you’re new, I hope this gives you some context.

So, here it is. This is what I believe about investing and how I use it in my journey to life.

Why We Invest: It’s All About Compounding

Let’s start simple.

We invest to turn money into more money. At its core, investing is about compounding capital over time.

We're not just buying tickers or chasing trends; we’re buying pieces of real businesses to earn a share of their future cash flows. Ultimately, the value of any stock is the present value of those future cash flows. That’s it. That’s the game.

But because no one can predict the future with certainty, investing is really about assessing expectations. Every stock price reflects a set of assumptions. My job as an investor? Figure out whether those expectations are spot on.

My Focus: Durable Growth Meets Quality Businesses

There’s a lot of noise in the markets: SPACs, hyper-growth, deep value, cyclicals, turnarounds, moonshots… you name them. I’ve looked into many of them at some point. But I keep coming back to what consistently works: quality paired with durable growth.

Now, durable growth and business quality aren’t just about surface-level metrics—like low CapEx and high margins, or strong revenue growth and a flashy Rule of 40. For me, it is a more holistic combination of traits:

• Owner-operator, capable and ethical management
  → See my piece on: 🔗 A Leap of Faith with Owner-Operators

• Enduring competitive advantages (“moats”)
  → See my piece: 🔗 The Rareness of Moaty Software Companies: Selection of 6 Gems

• Strong returns on capital and reinvestment runway—the essence of Growth and Capital Allocation excellence
  → See my primer: 🔗 The Serial Acquirers Playbook —masters of Capital Allocation
  → And my two pieces on: 🔗 Understanding Growth and Its Key Drivers and 🔗 Understanding ROIC, ROIIC, and ROCE: Measuring Capital Efficiency

• Track record of consistent execution and resilience through economic cycles

• Low leverage and financial strength, aka “antifragility”
  These are businesses that not only withstand stress but often emerge stronger because of it.

These businesses don’t show up every day. But when they do, I act.

Patience as the Ultimate Edge

“The big money is not in the buying and selling but in the waiting.” — Charlie Munger

Few quotes capture the essence of investing better than this one. The real edge isn’t IQ, flashy trades, or insider info—it’s patience.

Most investors underperform not because they lack intelligence, but because they act too often, too soon. They check prices daily, obsess over macro noise, and jump from idea to idea. I say this from experience, I’ve stumbled on this very rock more than once, and I'm still learning.

But history is clear: the biggest winners in investing come from holding exceptional businesses for long stretches of time.

A few years ago, I came across an interview with Chuck Akre of 🔗 Akre Capital Management. He said something that stuck with me:

“If you have a stock that’s gone up ten times, the next time it doubles it’s gone up twenty times, and the next time it doubles after that, it’s gone up forty times. Compound interest and return is staggering.”

That perspective changed how I think about holding.

These days, I aim to own businesses as long as the thesis holds. I don’t sell just because something looks expensive. I don’t try to call the top. If it’s a great business, why not let it keep compounding?

Concentrate and Ride with Conviction

I don’t believe in broad diversification for its own sake. I’m not building an index. I’m building a focused portfolio of businesses I believe in, and when I find one, I bet accordingly.

That means some positions can easily make up 10–15% of my portfolio (and no, I don’t set hard caps). This is not foolishness, it is conviction backed by due diligence. If I’ve spent months studying a business, tracking its management, reading filings, understanding the model, and spotting something the market’s missing… why wouldn’t I let that idea matter? (As always: do your own DD).

Concentration demands emotional resilience. Your biggest positions will test you. They’ll be volatile. The market will constantly question your thesis. But I believe that to outperform, your portfolio must look different from the index, and that means, leaning into your best ideas.

Concentration also forces discipline and for you to raise the bar. You don’t buy just to fill a slot; you buy because the opportunity is compelling relative to everything else you already own.

As Charlie Munger once said:

“The wise ones bet heavily when the world offers them that opportunity. They bet big when they have the odds. And the rest of the time, they don't. It's just that simple.”

This approach isn’t for everyone. But, so far, it works for me, and over time as I get to be a better investor, I believe it will continue to work for the Expanse Stocks portfolio.

Don’t “Gotta Catch 'Em All”

There are tens of thousands of publicly traded companies around the world. I only need 15 to 25. That means my default stance is simple: Pass.

It’s harder than it sounds. There’s a natural sunk cost bias: after spending hours researching a company, it’s tempting to buy something just to justify the effort. But I’m learning to see research as a compounding asset: an investment in pattern recognition, not a trigger for action.

Skipping trends, ignoring hype, and passing on “hot” names isn’t laziness, it is discipline. The best investors aren’t the ones who chase the most opportunities. They’re the ones who know which ones to ignore.

Simplicity Over Sophistication

When I started investing back in the day, I used to build intricate (and often inaccurate) valuation models, obsess over valuation multiples and minute assumptions, and forecast multiple scenarios into the future. It felt productive, until I realized it often blurred the bigger picture.

Now, I stick to the essentials, and I first try to answer these questions:

✔ What does this business actually do?
✔ Why does it win?
✔ Can it keep winning?
✔ What am I paying for that future?

The more I simplify, the clearer the path becomes. Only then, I ask deeper questions and create my investor’s checklist:

✔ Is the company reinvesting a meaningful % of profits?
✔ Are those reinvestments generating high returns?
✔ Are these drivers sustainable over time?
✔ How is shareholder dilution or buyback activity affecting the results?

Because investing isn’t about predicting next quarter’s EPS, it’s about recognizing durable patterns and backing them with conviction.

Never Selling? Not Quite.

If a company is executing, compounding value, and the original thesis holds, why sell? Taxes, friction costs, and reinvestment risk can quietly erode long-term returns.

But “never selling” doesn’t mean “buy and forget”, it means “buy and monitor”. I stay close to the companies I own. If something changes materially—management missteps, a key leader departs, the moat erodes, or capital allocation goes off track—I’ll reassess the entire position.

I like this mantra, but I’m still learning to stay true to it. In tough drawdowns, it’s easy to waver. I’ve made my fair share of mistakes under pressure, and it’s an area where I’m actively trying to improve.

Also, there’s nuance in how I manage positions.

Sometimes I’ll trim—not because I’ve lost conviction, but because a holding has grown beyond comfort or valuation stretches too far. In a concentrated portfolio, balancing conviction with risk management matters.

And yes, I do sell/trim when I find something better. If a new opportunity offers a stronger mix of quality, valuation, and long-term upside, I’ll make the switch. But it has to clear a high bar.

So no, I’m not married to “never sell.” I’m committed to thoughtful ownership. Great businesses deserve time to compound. But when the facts change, or the risk-reward does, I act. The goal isn’t to never sell. It’s to avoid selling for the wrong reasons.

Being an Individual Investor

Most people assume the pros have the edge—they have more data, more analysts, more connections. But knowing more isn’t the same as doing better. In fact, too much information can become noise.

The truth is individual investors enjoy a few rare advantages:

🔹 No one to answer to. We don’t report to committees. We’re not judged on quarterly returns. That’s freedom.

🔹 We can wait. Where institutional capital often needs results in months, we can wait years for a thesis to play out. In a short-term world, long-term patience is an edge.

🔹 We can fish in overlooked ponds. Many of the best compounders are “boring” or too small to move the needle for billion-dollar funds. But for us, they’re just right.

🔹 We set our own boundaries. We get to define our circle of competence. We can ignore the noise and only swing at fat pitches.

And maybe the most underrated advantage? We can stay humble. No pressure to prove ourselves. No need to outsmart the market every day. We just have to stay curious, rational, and patient.

In the end, I’ll take clarity, temperament, and independent thinking over raw IQ—any day.

Final Thoughts: This Is a Journey to Life

I’m not a perfect investor, not even close. I’ve made plenty of mistakes (and I’m already working on a piece reflecting on some of my biggest ones). But I’ve come to love the process: researching, learning from other investors, listening to management interviews and watching businesses evolve in real time.

Over time, the philosophy I’ve described here will continue to evolve, too. But the core will remain the same:

✅ Focus on quality and durable growth
✅ Wait patiently for the right opportunity
✅ Act with conviction when it comes
✅ Keep things simple—don’t overthink it
✅ Embrace patience as your edge
✅ Stay humble, always

That’s how I invest at Expanse Stocks. It’s not flashy, it’s not fast. But it’s thoughtful, disciplined, and built for the long game. And that’s how I’ll continue to approach every decision.

If this resonates with you, I encourage you to explore next my Stock Picking Methodology, available in the 🔗 Portfolio corner (for paid subscribers).

The Ultimate Goal: Investing for Life, Not Just Returns

One of the guiding principles of my investing philosophy is the idea that money is a tool, not a goal.

This mindset allows me to reframe financial planning around time, health, and happiness; not just net worth and returns.

I see financial success through the lens of life experiences that create lasting value—moments that enrich us and compound in personal fulfillment. That’s why I embrace planning life’s most meaningful experiences during the stages when they can be most fully enjoyed—especially while health, curiosity, and energy are on your side.

For me, that time is now. I’m 32 (soon to be 33), and I know these are some of the most vibrant years of my life.

This philosophy calls into question traditional retirement models, which often over-prioritizes delayed gratification. Too many people over-save and under-live, passing away with unused wealth and unfulfilled dreams.

For me, the true return on investment is a life well lived, not just a portfolio well managed.

That’s why my financial strategy is about balance: investing wisely for long-term security while also allocating capital toward what matters most. For me, that means, traveling, exploring, learning, sharing quality time with family and the people I love.

What does investing mean for you?

Thanks for following along,
— Nikotes

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Welcome Explorer!

On this occasion, I’m bringing you an interesting topic:

1. What is a moat?

2. What are some rare software companies with truly durable moats?

   I will discover 6 gems that, in my opinion, have the traits of moaty software.

Let’s dive in!

📰 What’s New at Expanse Stocks?

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💸 General Investing
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📚 Resources for Investors
📢 Latest Stock News
💬 Join My Chat → [📎 Learn more]

🔐 Paid Subscriber Exclusives

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👀 Recent Releases!

• 💸 Understanding Cash on Cash Returns

• 🔎 Deep Dive Brief: Constellation Software Capital Allocation Outlook - Part #1

👀 Coming Soon

• 💎 Unlocking Japan - Part #1: The Overlooked SaaS goldmine

• 💎 Unlocking Japan - Part #2: A Hidden Gem

Moats: Foundations of Long-term Excellence

When seeking long-term investments, understanding a company’s economic moat—a term popularized by Warren Buffet many years ago—becomes essential. A “moat” represents a sustainable competitive advantage, enabling a business to fend off rivals and maintain profitability. Morningstar defines five primary sources of moats (link for more details):

• Network Effects: The value of a product or service increases as more people use it. Think of social networks or payment systems like Visa, where widespread adoption creates a cycle of growth and more relevance.

• Intangible Assets: Brands, patents, and proprietary knowledge can provide pricing power or exclusivity. Examples include pharmaceutical patents or software with unique functionality.

• Cost Advantages: Companies with lower production costs, achieved through scale or efficiency, can undercut competitors while maintaining healthy margins.

• Switching Costs: High switching costs arise when customers face significant expense, disruption, or risk to move to a competitor. Software ecosystems, for instance, often lock users into platforms they’ve invested time and resources to master.

• Efficient Scale: Some industries favor a few dominant players due to the high costs of duplicating infrastructure or specialized capabilities, such as pipelines or niche software for regulated industries.

The Challenge of Moats in Software

Despite high growth and attractive margins, the software industry is difficult for establishing durable moats. Technology evolves rapidly, and innovative new players can disrupt incumbents overnight. The main traits that make software attractive—low capital intensity and scalability—also lower entry barriers, inviting competition. Unlike traditional industries with physical infrastructure, software companies must fight to sustain their relevance as competitors constantly improve or imitate their offerings.

Moreover, customer loyalty in software can be fragile. While some applications benefit from high switching costs or network effects, others—particularly in consumer-facing markets—can lose users quickly if a competitor offers a better experience or lower prices. Even moats built on patents or intellectual property may erode as new technologies make older solutions obsolete.

However, moats can still emerge in specific niches where companies align their strengths with unique market needs. In these spaces, enduring moats are often built on a combination of switching costs, network effects, and intangible assets, as we’ll see in the following case studies of “moaty” software companies.

Electronic Design Automation: Cadence Design Systems (CDNS) & Synopsys (SNPS)

The semiconductor industry relies heavily on Electronic Design Automation (EDA) software for chip planning, design, and implementation. Cadence and Synopsys dominate this space, benefiting from switching costs and a subtle network effect.

Semiconductor companies cannot risk switching to unproven tools. Their engineers often invest years mastering these platforms, embedding years of legacy designs and intellectual property into Cadence and Synopsys systems. The cost and risk of migration deter competitors, creating a sticky customer base.

Moreover, their wide adoption standardizes knowledge, making expertise in these tools a valuable asset for job-seeking engineers.

The moat is amplified by the non-cyclical nature of EDA demand. Unlike hardware, EDA spending continues regardless of economic fluctuations. This paired with a growing need for specialized chips, positions these companies as indispensable partners for leading tech firms.

Cadence and Synopsys are the perfect examples of “moaty” software compounders creating value for their shareholders:

And delivering sustainable growth for decades:

Logistics Optimization: Descartes Systems Group (DSG)

Descartes makes supply chain logistics easier to manage thanks to their modular SaaS solutions covering global trade compliance, routing, and shipment tracking.

Its network effect connects 200,000 parties globally, allowing seamless communication across different transport modes (by air, sea and land) and regulatory boundaries. Switching costs are hard to replicate for competitors, due to data migration risks, retraining, and operational downtime.

Descartes’ neutrality— being unaffiliated with any specific carrier—strengthens its value proposition, cultivating trust among manufacturers, shippers, and suppliers alike. During the pandemic, its adaptability became even more evident, as companies leaned on its platform to navigate supply chain disruptions effectively.

This “quiet” under-the-radar Canadian $10B small-to-mid cap is a prime example of a pure software solutions company with multiple moats. Its ability to deliver exceptional compounded returns to shareholders over the years makes it a “sleep-well” attractive investment:

Read more

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Welcome back and Happy Holidays!

Thank you for joining me on this Christmas Specials.

This year has been a rewarding one for investors, particularly those investing in US equities, with the SPY and QQQ delivering impressive back-to-back +20% annual returns. Incredible, right?

Well, maybe not so surprising when you take a closer look. The underlying driver behind this stellar performance has been strong EPS growth, which US markets have consistently outpaced compared to global counterparts like Europe, China, and the rest of the world 👇

As simple as it may seem, EPS Growth is a one of the main drivers of market returns, and the U.S. has dominated this metric for years (especially since the start of the Covid pandemy back in 2020).

What lies ahead in 2025?

While historical data can be fascinating, it offers limited predictive power. Some sources, like the one presented by Carson Investment Research, point to double digits SPY returns since 1950 after two consecutive +20% years:

But the reality is that markets are inherently unpredictable, and past performance isn't a blueprint for the future.

For long-term investors, the focus should be on multi-year horizons and underlying fundamentals. Meanwhile, swing traders should stick to technical setups, market momentum, and sentiment.

The takeaway? Avoid relying on 1-year market predictions based on historical data. This approach is flawed and can lead to misplaced confidence.

So, any Picks for 2025?

I can't predict what next year holds, but I can share my preferences. These are grounded in a blend of fundamentals, market context, and technical analysis.

So, let’s dive into my Top 5 Picks for 2025! 🎅

…and two extras:

• Swing Pick: I’ve added a 6th pick—a high-beta small-cap stock for swing traders. It’s backed by an exceptional chart setup and comes highly recommended by a trusted friend in the Stocktwits community.

• Bonus - “Trifecta” Pick: At the end of the article, you’ll find my 7th pick for Premium Subscribers—a trifecta of three stocks, similar yet distinct, operating in the same industry with strong secular tailwinds. Among them, I uncover a small-to-mid-cap hidden gem for long-term investors. This promising name has recently earned a spot in my portfolio. It’s also featured in my Hidden Gems - Special Edition (exclusive to Paid Subscribers)—don’t miss it!

📰 What’s New at Expanse Stocks?

📊 Quarterly Update - Portfolio Composition (by Industry and Geography) + Valuation Metrics → 🔗 Behind-The-Scenes [Free access]

📚 Articles

🔎 Deep Dive Briefs
⛅ Cloudflare | 👷‍♂️ Parsons | 𓇲 MPS | 🥼 Medpace | 🔌 Arista | 🛒 Amazon | 🤖 ASML | 🦎 Topicus | 💡 Lumine | ✈ HEICO | 🧙‍♂️ CSU Part #1

💸 General Investing
💎 Hidden Gems Series
✨ Annual Specials – Annual Letters, Investing Philosophy, Industry Write-ups & Top Picks of the Year
📚 Resources for Investors
📢 Latest Stock News
💬 Join My Chat → [📎 Learn more]

🔐 Paid Subscriber Exclusives

💼 Portfolio Corner – Holdings, valuation models, trades, performance & more!
🤫 Exclusive Sections – From select articles, Deep Dive Briefs & Hidden Gems

👀 Recent Releases!

• 💸 Understanding Cash on Cash Returns

• 🔎 Deep Dive Brief: Constellation Software Capital Allocation Outlook - Part #1

👀 Coming Soon

• 💎 Unlocking Japan - Part #1: The Overlooked SaaS goldmine

• 💎 Unlocking Japan - Part #2: A Hidden Gem

🎮 Nintendo (NTDOY)

Nintendo made my October Monthly Specials edition earlier this year, and although the stock has already started to break out from its multi-year base and still believe there is plenty of fuel left going into 2025. Let’s see why.

Technical setup

• Breaking out from its large Cup & Handle pattern, similar to past setups.

• Price above the rising 50-week MA as the stock breaks out from its mature base.

• MACD is setting up for a momentum boost just like in past cycles, pending upcoming news—which I’ll discuss later.

Fundamentals: Key Valuation metrics (LTM)

• 28% ROIC | 27% Operating Margin | 26.7% FCF Margin | 27.6 OCF/Sales

• No debt, with ¥2,163.13B in Cash and a ¥9,415.2B MC

These metrics are impressive, especially considering that Nintendo is in the final phase of its console cycle. The Switch, now 8 years old, has sold over 145 million units, far surpassing its predecessors, and achieving a longer and more profitable sales cycle.

Market Context and Thoughts

• On Nintendo’s Moat:

  This legendary entertainment firm has one of the strongest "IP franchise" moats alongside Disney, and it’s gearing up to launch its new Switch 2 console in Q1 2025.

• On Nintendo’s cyclicality and Business Model transition:

  Often seen as a cyclical video game/console business with low recurring revenues, leadership has been steadily shifting the model toward more reliable, recurring revenue streams with their Nintendo Account system, supporting cross-platform customers, and subscription-based Nintendo Switch Online service (Source: Medium).

  Additionally, leadership has ambitious plans to further capitalize on their IP franchises through new film releases and amusement parks.

🧠 FINAL TAKE:

• Quality company, undervalued, with strong margins, high ROIC, and plenty of cash on hand. Their business model is shifting toward increasing recurring revenue from video game franchises and consoles, with some of the strongest IP franchises still under-monetized.

• Good opportunity for both, swing trading going into 2025 and long term investment, supported by the technical setup, fundamentals and the upcoming console release.

🐶 Zoetis (ZTS)

Another name that made it to my October Monthly Specials edition earlier this year. The stock has been 'dead money' for over three and a half years, but this is shaping up to be a 'golden opportunity' heading into 2025. The stock is nearing the end of building a solid multi-year base, while the business continues to grow its EPS at a low double-digits rate and has successfully reaccelerated its FCF/Share growth over the past three years, all while the stock price remains stuck. Let’s dig deeper.

Technical setup

• 50-week MA and 200-week MA flattening out as price is moving sideways and comfortably sitting on both MAs.

• Stock price has been attempting to break a strong multi-year resistance level, 195$-200$, while forming a solid rounded base (blue curve) which started to form right after the downfall of the Covid-2021 peak.

• MACD with the positive divergence from 2022 and now going above the zero line as it keeps building upward momentum.

Fundamentals

• 8.8 EV/Sales (NTM) vs 10.1 EV/Sales (5Yr Avg)

• 21.8 EV/EBITDA (NTM) vs 23.5 EV/EBITDA (5Yr Avg)

• 24% ROIC vs 23.3% ROIC (5Yr Avg)

• EPS continue to grow at a steady 12% CAGR and FCF/Share reaccelerating substantially since the 2022 bottom while price continue to consolidate

  

Market Context and Thoughts

• On market fears:

  With Trump’s election, many investors have panic-sold pharma stocks, fearing changes to pro-pharma regulations and government spending. However, not all campaign promises are realized, and changing the status quo is harder than it seems. With just four years in office, Trump’s remaining term is unlikely to bring drastic changes, potentially creating opportunities for long-term investors as markets often stabilize over time.

• On Zoetis’ Business Opportunities and Moat:

  Animal health market is expected to grow at 5% CAGR for the next 10 years, and new potential multi-billion markets (renal, cardiology, allergies) are emerging for this pharmaceutical leader with pricing power and a moat in intangible assets (Patents, Brand, Scale).

  Source: Zoetis Investors Presentation (September 2024)

🧠FINAL TAKE:

• Quality stock trading below its 5-year average valuation, nearing the end of its multi-year consolidation phase, while key metrics for future price appreciation like FCF/share or EPS Growth keep improving.

• Good opportunity for both, long investment or swing trade, at these levels based on fundamentals and technical setup.

💻 Synopsys (SNPS)

Although it may seem surprising, given the stock's poor performance this year compared to its peers in the semiconductor and software sectors, this pick is driven by its technical pattern, the underlying fundamentals, and the secular tailwinds ahead. The company operates in a critical market dominated by an oligopoly, with Synopsys and Cadence Design Systems at the helm. Let’s take a closer look 👀

Technical Setup

At first glance, the current setup may not seem ideal, but with a proven compounder that rarely dips below its 50-week MA, recoveries often come quicker than expected. Here’s a closer look at why this might be another promising opportunity 👇

• Price Action

  The stock has been consolidating, and the 50-week MA has flattened as it has struggled to reclaim this level for several months.

• MACD

  While the MACD has been trending downward and lingering below the zero line, there are early signs of momentum beginning to turn upward with some parallels from H2 2023 chart pattern (circled in orange).

• Volume

  Selling pressure has been gradually declining since the July peak, with the major exception being the post-Q3 2024 earnings release, which triggered an overreaction in volume.

• Historical Patterns

  Highlighted in violet, the pattern from H2 2023 offers interesting parallels. When the price dipped below the 50-week MA previously, it didn’t stay there for long. The stock recovered support, reclaimed the 50-week MA, and resumed its upward trajectory. Back in H2 2023, after consolidating for about two years, this pattern preceded a +68% yearly rally once the MACD crossed above the zero line.

Market Environment and Commentary

• SNPS sold off after a decent Q3 2024 report and a prudent FY2025 outlook due to a mix of factors as explained by their management team: “impact of a shorter fiscal period for FY2025 (1 week shorter), market uncertainty and pragmatic view of China, readying our company for the largest acquisition in our history (ANSS acquisition expected for H1 2025)”

• Although the stock is not specially cheap, it’s trading below its 5-year average P/E ratio and the opportunities ahead, despite the above factors, are as bright as ever with the rise of AI and the need of custom ASIC chips design.

• Their competitor, Cadence Design Systems recently highlighted some interesting trends for the semiconductor industry and chips design on their investor call. Their CEO noted:

  “Generational trends such as hyperscale computing, autonomous driving, and 5G, are all accelerated by the AI super cycle…”

  “… executing to our intelligent system design strategy that triples our TAM opportunity while significantly expanding our portfolio across core EDA, IP, and system design and analysis. I'm excited about AI's incredible promise and how rapidly it is becoming an integral part of the design workflow, with customers steadily increasing their investments in AI-driven automation.”

🧠FINAL TAKE:

• EDA, IP, and system design and analysis are dominated by an oligopoly, with Synopsys as a key player. Their solutions are essential to chip manufacturing, and their market and applications are expanding, accelerated by the AI super cycle and major growth trends in computing, autonomous driving, and 5G.

• The potential acquisition of Ansys is Synopsys’ wild card. If approved, it would further expand their moat and TAM, though it can create short-term stock price pressures.

• Solid opportunity for a long-term investment, backed by secular trends and a critical role within an oligopoly essential to the semiconductor industry. Technical setup has potential for a swing trade too, showing signs of repair and preparing to gain momentum once again.

💸 Adyen (ADYEN)

Another name that featured in my Monthly Specials series for December, this one is an “easy” pick. Not much has changed in terms of its technical setup and fundamentals since I highlighted it last month—except for one key development: the stock has moved higher recently and is now on the verge of breaking out from a bullish multi-year inverse head-and-shoulders pattern. Here’s why it’s a Top Pick:

Technical Setup

Adyen’s stock collapsed in August 2023 following its H1 2023 earnings release, driven by disappointing sales growth and compressing margins. This decline pushed the stock back to pre-pandemic levels. However, over time, this has created a very interesting technical setup, as explained below:

• Inverse Head and Shoulders (Weekly Timeframe):

  • Left Shoulder: Formed after the end of 2021, establishing a key support level around the €1200 range.

  • Head: Developed during the 2023 collapse, where the stock bottomed out at long-term support near €600.

  • Right Shoulder: Recently formed above the crucial €1200 support zone, with the stock now approaching a breakout level near €1500.

• Smaller Inverse Head and Shoulders (Highlighted in purple):

  • Over the past few months, a smaller inverse head-and-shoulders pattern has emerged, reinforcing the bullish potential.

• 50-week MA

  Price jumped above the 50 MA recently which is perking up as the stock prepares for the breakout.

• MACD

  The MACD line is gaining momentum above the zero line and points to a potential bullish reversal.

• Volume:

  • Selling volume has steadily declined, with dips being consistently bought on spiking volume—a positive indicator of accumulating demand.

  • A breakout from the bullish pattern would be further validated by a spike in buying volume.

Fundamentals

There’s a lot to like about Adyen as it continues to carve out a significant niche in the global payments landscape. Here are the key reasons:

• Simplifying Payment Complexity: Adyen addresses the headaches of managing multiple local payment providers by offering seamless payment routing, lowering merchant costs, and boosting authorization rates.

• Capital Efficiency: Its capital-light model helps to achieve sustainable growth, on Adyen’s CEO words: “We aim to maintain a sustainable capital expenditure level up to 5% of our net revenue”

• Scalable Growth: Targeting net revenue growth in the low-to-high 20% range annually through 2026, demonstrating its ability to scale fast.

• Margin Strength: With inherent operating leverage, the company aims to achieve EBITDA margins above 50% by 2026. This is industry-leading profitability.

• Solid Balance Sheet: Adyen remains net cash-positive with minimal debt, providing both stability and flexibility for reinvestment.

• Market Share Upside: Operating in a highly fragmented market, Adyen is just getting started, with significant runway to expand its market share:

"We are still the minority player across our customer base on average... There is a lot of volume for us to still win in our existing base. The business will be much bigger in the years ahead than it is today. And in doing that, we want to be sure that we have the right flexibility to invest where we can accelerate growth." — CEO comments, H1 2024 Conference Call, on the vast untapped volume within the company’s existing customer base

Price will Catch Up to Fundamentals

Since the revenue growth slowdown from the Covid-era bubble in 2021—declining from the mid-40% range to the low-20% range by H1 2023—Adyen's growth has stabilized around the mid-20% level. Meanwhile, EPS growth has maintained an impressive +33% CAGR over the past four years, even as the stock price remains stuck.

They say, “technicals follow fundamentals.” Well, Adyen might just be a prime example of what could happen… soon.

FINAL TAKE

Adyen’s stock has been building a solid multi-year base, supported by the inverse head and shoulders pattern. With fundamentals showing gradual improvement since the H1 2023 pullback, the stock is on the cusp of a breakout. I think this could be a great opportunity for long-term investors and swing traders going into 2025.

🔎 Google (GOOG)

For Google, I won’t dive into a detailed analysis because the fundamentals, technical indicators, and chart patterns speak for themselves. However, I do want to share my personal thoughts on this still underappreciated (and sometimes hated) innovation powerhouse.

While many focus on concerns about competitors stealing Google’s search market share and the DOJ's break-up potential, Google is positioning itself for a potential run into 2025. Its transformation beyond search is surprisingly underappreciated with its rapidly growing and profitable cloud services, leading video platform, and ventures into more than exciting fields like:

• AI, where Google is ahead of competition, with their proprietary TPUs powering most of their services

• Automotive autonomy, where Waymo is already the only approved vehicle with a fully autonomous system and is just starting its expansion

• Quantum computing: Google unveiled Willow earlier this week, a quantum chip that could transform industries. More details on this release here. While it's still in its early stages, the potential for real-world applications—like revolutionizing drug discovery or powering highly efficient systems—is immense in the long-term and it’s the kind of innovation that could make anyone dream.

So, my question to the fear mongers is: What’s there to fear and not be excited about? I still don’t get it.

🎢 Swing Pick: Magnite (MGNI)

High-beta Tech Play

One of the pandemic-era high flyers, this $2.2B small-cap technology company has seen a dramatic fall from its $60s heights to the single-digit range. Despite what seems like a risky or bold choice, there are some good reasons to take a closer look, specially for swing traders.

MGNI operates a global, independent sell-side advertising platform for Connected TV (CTV) channels and has recently made significant strides improvement on its fundamentals:

• Turned profitable in the last quarter after years of sluggishness in negative territory.

• Trades at a forward P/E of 19 and EV/FCF of 17.

• Achieving a 31.52% 5-year CAGR improvement in its now-positive ROIC.

However, the real appeal lies in its technical setup, which bears a striking resemblance to Cloudflare (NET), one my favorite high-growth names I highlighted in my deep dive a few months ago (link), that recently broke out from its early Stan Weinstein's Stage 2 phase. Let’s break down MGNI’s technicals.

Technical Setup

Weekly Moving Averages (MAs):

• The 50-week MA is gradually trending upward, signaling building momentum, though the stock continues consolidating near resistance.

• The price has also reclaimed its 200-week MA and is now holding steady around it.

MACD Momentum:

• After tightening since early 2024, the MACD line has turned upward above the zero line—a classic signal of a potential strong upward move.

Volume:

• Buying pressure spikes over recent months (highlighted by grey arrows) helped MGNI break out of its multi-year base and cross the key resistance at $15s, transitioning from Stage 1 to an early Stage 2 phase.

• Volume has since declined in a healthy consolidation pattern, suggesting preparation for further movement within Stage 2.

Stage Analysis:

• According to Stan Weinstein’s Stage Analysis (link), MGNI is in an early Stage 2 phase (see image attached to the chart).

  • This phase is confirmed by a rising 50-week MA, a tightening MACD curve, a successful retest of the previous mid-$15s resistance as potential support, and declining volume after the transition.

  • These features align with the "playbook" for Stage 2 transitions, setting the stage for future upside.

Although I don’t anticipate the wild price swings of the COVID era, if MGNI's fundamentals keep improving and market conditions—such as lower interest rates—align, 2025 could be a fantastic year for Magnite.

The next pick is a trifecta of stocks. Among them, I uncover for the first time a small-cap gem which comes straight from my 📎 Hidden Gems - Special Edition. I’ve recently added it to my long-term portfolio, recognizing its exceptional potential. The next details about the trifecta pick and the small-cap gem are reserved to Paid Subscribers.

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