Chirag Jain

A Unified Framework for Training, Trajectory Improvement, Optimization, and Evaluation of Agentic AI Systems

The talk introduces an innovative framework for training AI agents using trajectory deep reinforcement learning (GRPO) and active intelligent memory utilization. By treating entire decision trajectories as the core unit of learning, it addresses challenges such as trajectory blindness and high supervision costs, thereby enhancing agent performance and understanding. This framework supports continuous experiential learning without extensive human oversight and incorporates a modular evaluation methodology for assessing enterprise agentic platforms. The framework aims to improve the efficiency, adaptability, and risk management of AI systems, driving wider adoption in enterprise environments.