Dr. Rajiv Chandegra is a London physician, chief executive of Annicha Labs, and co-founder and clinical product lead of Donna, a healthcare workforce-management platform. His work applies clinical experience and complexity science to a central challenge in AI: building systems that adapt when people, organizations, and real-world conditions change.
In 2012, Chandegra co-authored a clinical case report while affiliated with Hereford County Hospital’s cardiology department. He subsequently worked as a general practitioner and expanded into healthcare policy, consulting, nonprofit publishing, and technology. He remains a practicing London general practitioner.
Chandegra became a founding member of the Tattva Fellowship and has served as a director of Tattva Network since 2019 and Annicha Group since 2022. At Annicha Labs, he helped build Donna to address fragmented healthcare operations through workforce management, automation, and training oversight. His writing on policy tradeoffs examines opportunity costs, unintended consequences, and how institutions distribute the burdens of their decisions.
- Adaptive engineering: Chandegra argues that agent roles, coordination patterns, and workflows should sometimes emerge and reorganize during execution.
- Complicated versus complex systems: Predictable problems reward fixed workflows, reproducibility, and clear accountability. Healthcare organizations and cross-institutional collaborations change through interactions among their participants, making rigid orchestration increasingly brittle.
- Horizontal intelligence: Improving coordination among agents can matter more than making each agent individually stronger. Chandegra emphasizes local interaction, emergent specialization, and decentralized cooperation among software, people, and institutions.
- Accountability in self-organizing systems: Adaptation introduces real hazards: opaque behavior, weak selection pressures, homogeneous agents, and stable outcomes that remain harmful or inefficient. In medicine especially, governance and auditability cannot disappear as systems become more flexible.
At AI Engineer World’s Fair 2026, Chandegra advanced this vision of AI systems that reorganize around changing human environments while retaining meaningful safeguards.
