Make your LLM app a Domain Expert: How to Build an Expert System — Christopher Lovejoy, Anterior
Jul 28, 2025 · 19:18
Christopher Lovejoy, a medical doctor turned AI engineer at Anterior, argues that building a domain-native LLM application requires a system for incorporating domain insights rather than relying solely on model sophistication. Anterior's Adaptive Domain Intelligence Engine uses domain expert clinicians to review AI outputs, generate metrics, define failure modes, and suggest improvements. This process improved Anterior's clinical reasoning tool from 95% to 99% accuracy on medical necessity reviews for health insurance providers covering 50 million lives. By enabling same-day iteration—production cases reviewed, failures categorized, domain knowledge added—the system solves the 'last mile problem' of giving models nuanced understanding of customer workflows. Lovejoy emphasizes that the limitation is not model reasoning but encoding domain-specific context, and the winning vertical AI team will build the best system for this translation.
