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Mayank
Agarwal
Director of Product Management, AI Products
RingCentral
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.
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18 March 2027 09:15 - 09:45
Stop babysitting your AI: Building AI agents that fix themselves
Most enterprise AI agents fail quietly, completing tasks with no awareness of their own errors. At my quantitative trading firm, I built self-improving AI systems where failure had immediate financial consequences, forcing architectures that detected mistakes, diagnosed root causes, and improved autonomously. At RingCentral, I've applied these same patterns to our AI Assistant, now serving millions of enterprise users. The core insight: self-correcting agents aren't a research problem, they're a product design problem. We'll explore the framework refined across both domains: how to build AI agents that know when they're wrong, the architecture patterns that make self-correction reliable in enterprise environments, and how to measure autonomous improvement over time. Attendees will leave with a reference architecture and a KPI framework for evaluating self-improving agents, ready to apply to their roadmaps next quarter.
18 March 2027 16:45 - 17:00
Closing remarks
Reflecting on the day's sessions and insights, our chairperson will close out the end of day one.
18 March 2027 14:30 - 15:15
Panel | Move fast and stay compliant: Shipping product in regulated industries
In regulated industries, shipping fast isn’t the hard part. Shipping fast without creating risk is. As AI moves from pilot to production, product leaders in banking, fintech and other regulated sectors face tighter controls, closer scrutiny and higher expectations from customers and regulators alike. Hear how leading product organizations are building speed into environments where every release has to stand up to review. Learn what’s changing, what’s working, and how to keep momentum without cutting corners. In this session, you’ll learn how to: - Bring risk, legal and compliance teams into the product process early, so reviews speed up delivery instead of slowing it down. - Put evaluation, human oversight and audit readiness around AI features before they reach customers. - Build a product culture where compliance and velocity work together instead of competing.