Mayank Agarwal

Mayank is Director of Product Management for AI Products at RingCentral, where he leads the AI Assistant products across the company's collaboration, communication, and contact center suites, shaping how millions of enterprise users interact with AI in their daily workflows. His work sits at the intersection of agentic AI architecture and large-scale product delivery, navigating the real-world constraints of latency, reliability, cost, and trust that separate impressive demos from systems businesses actually depend on. Before RingCentral, Mayank founded an AI-first global macro trading firm where he designed and built autonomous trading systems across equities, fixed income, commodities, and currencies. There, he built multi-agent architectures where specialized agents collaborated, competed, and coordinated with each other. He also pioneered reflection agents that continuously evaluated their own strategy performance, detected signal decay, and autonomously improved without human intervention. The unforgiving feedback loop of financial markets, where poor AI decisions have immediate, measurable consequences, shaped his approach to building systems that must be not just intelligent, but self-aware and resilient. Mayank holds a master's degree from Stanford University and conducted research at the Stanford AI Lab, grounding his product leadership in deep technical fluency. His unique career arc, from high-stakes algorithmic trading to enterprise-scale AI products, gives him a rare vantage point on agent orchestration, evaluation infrastructure, and the architectural patterns that determine whether multi-agent systems thrive in production or collapse under real-world complexity. He speaks and writes frequently on AI agents, reflection architectures, and the emerging discipline of building AI products where failure is not an option.