Continual Learning from User Interactions: Build Agents That Improve Over Time

Inside the event

What if your AI agents could continuously improve by learning from how people actually use your product? Most approaches to improving AI agents focus on agent trajectories alone. But what about everything happening in your application while users interact with those agents? In this webinar, we're introducing Continual Learning with CopilotKit and a new approach built around Full-Stack Trajectories, combining Agent Trajectories and Product Trajectories to capture a more complete picture of how agents and users interact. We'll explore the architecture, demonstrate what we've been building behind the scenes, and show how these combined signals can help improve the agents you've already built. Here's what we'll cover: The Vision: Why we're building Continual Learning and the limitations of learning from agent trajectories alone. Full-Stack Trajectories: How combining Agent Trajectories and Product Trajectories provides richer context for learning. Live Demo & Technical Deep Dive: An exclusive first look at what we've built, including the architecture and how it works. Early Access: Where we are in development, what's coming next, and how you can get involved. Live Q&A: Join Atai Barkai (CopilotKit CEO) and Sam Julien (Head of Product) for technical questions and an open discussion. The goal? Make your existing agents better by learning from real user interactions and product behavior, without replacing your models or rebuilding your application. Be among the first to see what we're building and learn how to get early access.