Citrini: Monkeys Are The Next Bottleneck | Citrini on AI Drug Discovery Experiment & Reflexive Financing Risk to AI Buildout & Hardware Trade

The AI investment landscape has shifted from a broad infrastructure-heavy strategy to a more selective focus on agentic utilities and tangible economic outcomes. While hyperscalers continue to drive massive capital expenditure, the market now demands evidence of paid usage and sustainable revenue growth. Drug discovery serves as a primary case study for this transition; using AI to design scorpion antivenom demonstrates that while models can compress dry-lab research timelines from months to days, physical bottlenecks in preclinical testing and toxicology remain significant constraints. Investors should prioritize companies that facilitate these experiments, such as contract research organizations, rather than betting on speculative biotech firms. Ultimately, the next phase of the AI trade depends on whether frontier model spending translates into tangible enterprise productivity and whether the current valuation of infrastructure reflects realistic long-term demand.