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In this comprehensive episode, Citrini returns to discuss his "26 Trades for 2026" thematic watchlist, marking a pivotal shift from AI's hardware-focused "phase one" to "phase two" - where companies begin utilizing AI to streamline operations and increase margins. The conversation explores Citrini's high-conviction "AI Bureaucracy Alpha" framework, identifying firms positioned to significantly reduce headcounts through automation. (10:30) Beyond labor optimization, the interview delves into critical supply chain bottlenecks including advanced packaging and custom silicon, while examining commodities like natural gas and copper where AI data center demand could create supply squeezes. (27:00) The discussion concludes with Citrini's "Post-Traumatic Supply Disorder" theory, highlighting cyclical sectors showing extreme capital discipline after years of market trauma.
Citrini is an anonymous investor and analyst who has built a reputation as a leader in thematic equity research. His Citrini Research publication focuses on identifying emerging investment themes before they gain widespread attention, while the Citrindex tool tracks custom indexes and baskets with rigorous performance metrics. Since inception in 2023, the Citrindex has delivered 217% returns versus 69% for the S&P 500, demonstrating his ability to identify profitable thematic opportunities ahead of the market.
Jack Farley is the host of Monetary Matters, focusing on investment themes and market analysis. He conducts in-depth interviews with leading investors and analysts to uncover actionable insights for ambitious professionals seeking to master their investment approach.
There's a massive disconnect between what AI can accomplish today and what organizations are actually using it for. (10:00) While companies experiment with basic tasks like using ChatGPT to summarize PDFs, AI agents can now perform complex work like logo alignment and document formatting in seconds for a fraction of a penny. Fortune 500 companies are still paying highly educated employees $150,000+ annually to do work that AI can complete instantly because internal bureaucracies haven't caught up to technological capabilities. This creates an opportunity to invest in companies with bloated organizations that show intent to cut costs through AI implementation.
As Moore's Law hits physical limits, the semiconductor industry has shifted from making chips smaller to connecting multiple "chiplets" together through advanced packaging. (33:57) TSMC is the only company doing this at scale and is completely capacity-constrained, while companies like Google's TPUs, Meta's custom chips, and NVIDIA's Blackwell all compete for the same packaging capacity. This bottleneck creates opportunities in companies like Intel (for their eMib and Foveros packaging technology), Amcor, and specialized tooling companies like KLIC that provide the "duct tape" holding chips together.
Natural gas faces unprecedented demand pressure from two massive infrastructure buildouts: AI data centers and LNG export terminals. (50:19) While nuclear and solar are ideal long-term solutions, the urgent need to "build machine god now" means most data centers run on natural gas. Simultaneously, the US is transitioning from importing to becoming the world's largest LNG exporter. This dual demand creates potential for natural gas producers like EQT and Comstock to negotiate fixed-price contracts with hyperscalers, similar to how independent power producers like Vistra gained growth investor attention.
Companies in cyclical industries that were burned by previous capacity expansion cycles now exhibit extreme capital discipline despite rising demand. (60:00) Memory companies like Micron and SK Hynix, and gas turbine manufacturers like GE Vernova experienced massive losses after building capacity for perceived secular demand that then collapsed. Now, when demand returns, these companies are "once bitten, twice shy" - they're letting backlogs grow and average selling prices increase rather than immediately rushing to build new capacity, creating superior margin profiles.
The AI supply chain creates ongoing opportunities in specialized materials and components where single companies hold dominant market shares. (44:00) Companies like Resonac (nonconductive film for memory stacking), Ajinomoto (ABF substrate with 90% market share), and Natobo (T-glass fiber) trade like boring chemical companies but become massive winners when supply shortages emerge. The key strategy involves monitoring news alerts for shortage announcements in Taiwan and Japan, then quickly identifying which companies have high market shares in those specific materials.