The attention divergence
Q2 was the quarter AI infrastructure took centre stage. Chips, compute and the physical build-out behind the data centre had the spotlight, the audience and the market's full attention. Every headline and every trade seemed fixed on the hardware behind the AI show, while other themes, energy scarcity, power demand, hard assets and the metals behind the build-out, defence and security, digital assets and peptides, were left waiting in the wings. The Strait of Hormuz reopened, but the supply-chain dislocations it triggered have yet to fully normalise.
Bitcoin fell around 20% in June to a low near $56k, its weakest in roughly 21 months, with a record $4.5bn pulled from Bitcoin funds over the month, before recovering to around $61.5k. By early July, gold and Bitcoin were stabilising in tandem, an early signal that the debasement trade into hard assets is re-establishing its bid.
Two new themes emerged during Q2. The first was the increasingly attractive supply-demand dynamic for regulated peptide manufacturers, as the oral transition accelerated prescriptions from 200,000 to 300,000 per week and regulatory changes prepared to shut the grey market of unregulated compounders. The second was physical-AI sensing, where capabilities in real-world perception are shaping up as a future bottleneck in the robotics build-out, much as memory is to AI chips today. Both themes were added to the Conviction list during the quarter.
The SaaS reset also crystallised. This is not an upgrade cycle; it is a rebuild. The market is separating the software businesses that can reconstitute as AI-native platforms from those that cannot, and the dispersion in valuations across the sector reflects that sorting in real time.
How the Conviction Ideas performed in Q2
H1 2026: +7% | Q2 2026: +12%
The quarter's gains were concentrated in three corners of the book. Semiconductor infrastructure led, with fab-equipment orders surging as the AI build-out accelerated and over a hundred fabs now under construction globally. Wearable silicon and edge-inference hardware delivered a re-rating as diversification away from smartphones translated from narrative into real product launches, partnerships and revenue. Physical-AI sensing had one of the cleanest news-flow quarters in the portfolio, with product launches, defence clearances and regulatory tailwinds combining to reframe the category from niche automotive component to essential infrastructure for robotics and autonomy.
The downside came from two familiar places. Precious metals retraced as a hawkish Fed repricing and a firmer dollar weighed on the debasement trade through the back half of Q2, though the structural bid from central-bank buying held and by early July gold was finding support at higher levels. Chinese consumer internet hit fresh lows as heavy AI investment and new geopolitical complications weighed on the sector, though the underlying shift toward AI and cloud infrastructure continued to accelerate. After two years up 47%, the book remains deliberately conservative and diversified, built to do its job whichever way the market turns.
The second-half setup
Heading into Q3, the setup rhymes with 2000: the new economy against the old, a handful of AI giants against everything else, and gaps like this get more violent the closer they run to the top. The lean is into the neglected side of the book: trimming the purest AI and semiconductor exposure and adding to commodities, gold and digital-asset themes, with rate cuts and currency debasement likely providing a tailwind.
Two other topics are on the desk for the summer. The first is the market impact of the developing Super El Nino, as soft commodity prices start to move. The second is the interest-rate path, where the direction increasingly points to cuts despite the Fed's hawkish posture under its new chair. Both will be explored over the quieter weeks ahead.
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Selling the Picks Instead of Digging for Gold
Meta is increasingly taking a different approach to the AI race. Rather than competing head-on to build the leading frontier model, it is positioning itself to monetise the infrastructure already in place. The launch of Meta Compute marks a shift toward selling excess AI computing capacity, turning billions of dollars of existing investment into a potential new revenue stream.
The strategy comes at an interesting point in the cycle. Compute remains one of the scarcest resources in AI, with demand still outstripping supply despite record levels of investment. Rather than viewing spare capacity as a sign of overbuilding, the market is beginning to see it as an asset that can generate attractive returns while supporting Meta's own AI ambitions.
The result is a business with multiple ways to win. Advertising continues to fund the AI investment cycle, while compute infrastructure is emerging as a potential profit centre in its own right. If AI demand remains constrained by capacity rather than models, Meta increasingly looks less like a social media company and more like an AI infrastructure platform.
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