Fine-tune a search agent with multi-turn RL on Amazon SageMaker AI
Multi-turn RL on SageMaker lets small models match frontier reliability for search agents
“Fine-tuning offers a third path: you teach a small model your tools and environment directly. The result is a small model's speed and cost with the reliability that would otherwise require a frontier model.”
AWS describes Amazon SageMaker AI's multi-turn reinforcement learning (MTRL) capability for fine-tuning search agents, optimizing across full interaction trajectories rather than single steps. The approach addresses the cost and latency penalty of frontier models by training smaller specialized models to internalize tool-use behavior specific to an environment. Relevant to practitioners building agentic retrieval systems, but this is a product feature tutorial rather than a broader industry signal.