Abhi Desai: Agents at Scale for Marketing - Troubleshooting with AI Reasoning

Real time systems generate a constant stream of events, yet most AI models are still designed to run offline and produce reports rather than actions. This gap between prediction and decision is where many production systems fail. Developers often have accurate models but no safe, reliable way to use them in live environments. This talk focuses on how to design AI driven decision systems that act on live events with low latency and high reliability. It explains how models connect to event streams, APIs, and rule engines, and how decisions flow through real software systems. The emphasis is on architecture and system behavior rather than algorithms or math. Using real examples from large scale retail and marketing platforms, the session highlights common failure modes such as delayed signals, noisy data, unstable actions, and lack of explainability. It then shows practical design patterns like guardrails, decision thresholds, rollback strategies, and continuous monitoring that allow AI systems to operate safely in production. The ideas and patterns discussed translate directly to WebRTC, telephony, and real time communication systems where decisions such as routing, prioritization, or optimization must happen quickly and predictably. Attendees will leave with a clear reference architecture and practical guidelines they can apply to their own real time systems.