Trading Desks to Clinical Trials: Parallels in Applied Vertical AI — Ayush Bhardwaj, Allos AI
Aug 19, 2026 · 20:02
Ayush Bhardwaj, who applied AI at a hedge fund before pharma tech startup Allos AI, argues vertical AI projects die from not being able to judge whether they work. His seven-step recipe: narrow tasks, proprietary data, expert-modeled prompts, observability, then hiring the user—a domain expert—because using LLM-as-judge is a "stupid mistake" that jargons its way out. Verifiable rewards fail in finance and pharma: no answer keys, and data is withheld—30% of firms never disclose clinical trials, and the FDA publicly reminded over 2,000 sponsors in 2026. He says 89% of enterprise AI agents never reach production; the fix is endless expert-in-the-loop learning, starting with error analysis as highest ROI. Moat is never model or infra; only curated domain expertise and proprietary data matter.
