To The Moon

Broadcom’s Quiet Empire The first wave of artificial intelligence created a simple investment story: buy the companies building the fastest chips and enjoy the ride. The second wave is becoming far more complicated — and, in my view, far more interesting. AI is now colliding with economic reality. Hyperscalers are discovering that training and deploying large language models at global scale requires far more than raw compute power. It demands lower energy costs, faster connectivity, optimised architectures, and infrastructure capable of moving staggering amounts of data without collapsing into latency chaos. That shift is precisely why I believe Broadcom has quietly become one of the most strategically important companies in the entire AI ecosystem. Broadcom is no longer simply benefiting

Why the Most Important AI Infrastructure Battle May Be Happening Far Below Big Tech’s Pay Grade For the past two years, the AI investment boom has revolved around giants. $NVIDIA(NVDA)$ sold the shovels, $Microsoft(MSFT)$ rented the mine, and $Amazon.com(AMZN)$ charged everybody extra for bringing their own wheelbarrow. Yet while Wall Street obsessed over trillion-dollar firms, a quieter shift began unfolding underneath them. DigitalOcean was never supposed to become one of the defining AI stocks of 2026. It lacked the scale, balance sheet and political gravity of hyperscalers. For years, it occupied a fairly unglamorous corner of the cloud market serving startup

Reinvention in Plain Sight Alphabet is no longer the market’s favourite ‘obvious’ company, which is precisely why I find it compelling. At just under $4.7 trillion in market capitalisation and trading near its highs, it looks fully appreciated on the surface. A trailing P/E of roughly 29 and a forward multiple above 30 do not scream bargain. Yet those numbers obscure a deeper transition: Alphabet is shifting from a predominantly advertising-driven enterprise into a vertically integrated AI infrastructure company. This is not a cosmetic pivot. It is a structural rewrite of how revenue is generated, how costs are controlled, and how competitive advantage is sustained. The market, in my view, is still pricing Alphabet as a highly efficient incumbent rather than a company attempting to control

A Utility Hiding in Plain Sight I think the mistake most investors are making with Cellebrite is not analytical—it’s categorical. The market is still trying to decide whether this is SaaS, AI, or cybersecurity, when in reality it is drifting into something closer to sovereign digital infrastructure. That framing matters upfront because it reframes everything else: revenue durability, pricing power, and competitive risk. Governments do not treat digital forensics as discretionary spend. They treat it like evidentiary plumbing—if it fails, the consequences are legal, not just operational. The broader 'DiSaaSter' narrative—that AI compresses software value by commoditising features—has merit in horizontal SaaS. But it is being applied far too bluntly. Cellebrite is not selling convenience; it

The AI Boom’s Most Uncomfortable Question Super Micro Computer has become the stock market equivalent of a Formula One car being rebuilt while still racing at 300 kilometres per hour. One side of the market sees an AI infrastructure champion powering the next phase of Nvidia’s Blackwell rollout. The other sees a company drowning in legal risk, collapsing margins, and geopolitical scrutiny. Personally, I think both camps are right — and that is precisely what makes $SUPER MICRO COMPUTER INC(SMCI)$ one of the most fascinating stocks in the market today. Most AI commentary still treats Nvidia as the sole protagonist of the artificial intelligence boom. Yet the uncomfortable truth is that GPUs are useless without the server infrastructure surrounding

Energy First, Compute Second I see Arm Holdings as the market’s clearest bet that AI’s next constraint will not be compute, but energy. At roughly $211, with a trailing P/E approaching 280x and a forward multiple still above 100x, the stock is not reflecting what the business is—it is reflecting what the infrastructure will demand. If energy becomes the bottleneck, Arm is essential. If it does not, the valuation begins to look like a very expensive assumption. AI’s real ceiling isn’t compute—it’s electricity From Architect to Toll Collector I find the most misunderstood part of Arm’s story lies in its transition from licensing intellectual property to selling higher-value compute subsystems. Historically, $ARM Holdings(ARM)$ was the architect—desig

The Market’s First Real AI Reckoning I see Microsoft not as a participant in the AI trade, but as its first genuine stress test—where ambition, capital, and monetisation collide in plain sight. After a sharp stumble in early 2026, $Microsoft(MSFT)$ has become the market’s most consequential question mark. It is no longer enough that the company leads in AI. What matters now is whether that leadership produces incremental profit, or simply gets absorbed into an already dominant ecosystem. That distinction is where the entire debate sits. The Hidden Risk: Giving AI Away Too Cheaply AI dominance means little if pricing power quietly evaporates I believe the real battleground is not technological leadership, but pricing architecture. Microsoft is embe

Replying to @Ah_Meng:You’ve captured it well—Tesla’s vision is undeniable 🚀, but scaling robots and autonomy demands real-world supply chains, utilisation, and cost discipline that valuation currently overlooks 📊🤖 //@Ah_Meng:Excellent piece indeed! Tesla valuation has gone hardwired for the longest time now… retailers nowadays just blindly follow the cult leader Elon and when Elon says jump, they simply asked, “how high?” It’s a time of excess where real valuations are thrown out of the window. I readily admit Elon’s visions but he has an execution problem. Tesla, robots… materials, lots of them. Where better to do them but in China 🇨🇳? We can be ambitious, but supply chain issues

Zuckerberg is no longer being judged on earnings beats—he is being judged on whether $40 billion in AI spending will compound like AWS or combust like the metaverse with better branding Meta is once again doing what it does best: making investors richer, twitchier and occasionally behave as though a 30% profit margin is some sort of corporate distress signal. This time, the market’s anxiety is not about user growth, regulators or TikTok-inspired existential dread. It is about capital allocation—specifically Meta’s decision to drive annual capital expenditure towards roughly $35–$40 billion in AI infrastructure, data centres and computing power. For context, this is not a modest budget increase. It is one of the largest strategic spending surges in modern Big Tech, and a dramatic pivot from

A Valuation That Assumes the Ending I see Tesla in May 2026 as the market’s boldest intellectual gamble—a company priced not on what it earns, but on whether it can industrialise autonomy before reality reasserts itself. At roughly $381 per share and a market capitalisation near $1.4 trillion, Tesla is being valued less as a business and more as a thesis. The numbers themselves are almost mischievous. A trailing P/E above 340 and a forward multiple near 180 would be ambitious even for a pure software firm, let alone a company still generating the majority of its revenue from manufacturing. Yet Tesla sits here comfortably, as if gravity were more of a suggestion than a law. The tension is unmistakable. The financials describe a company still wearing steel-toe boots. The valuation assumes it