Agent Optimization: Discover better agent configurations automatically

Agent Optimization, now available in beta for eligible customers within the AgentControl platform, automates the improvement of agents by generating and testing combinations of models, prompts, and hyperparameters against predefined acceptance criteria. This method expands beyond the limitations of manual iteration, as it explores configurations not previously considered, thus potentially finding optimal solutions that are more efficient and cost-effective. Two modes of optimization are offered: Exploratory mode for mapping behavior across diverse inputs and Expected Output mode for refining performance without losing established functionality. Once a successful configuration is identified, it can be seamlessly promoted to production, allowing for gradual implementation and performance tracking through AI Insights. The ultimate goal of AgentControl is to enable agents to autonomously identify and apply improvements based on real-world performance, minimizing the need for manual intervention.