Introducing AgentKit, new Evals, and RFT for agents

OpenAI has announced a suite of tools aimed at streamlining the development and deployment of AI agents, according to the OpenAI Blog. The release includes AgentKit, a framework for building and orchestrating agents; expanded evals capabilities for testing agent performance; and reinforcement fine-tuning (RFT) tailored for agent-based systems. AgentKit provides developers with modular components to construct agents that can execute multi-step tasks, while the new evals allow for standardized benchmarking of agent behavior across diverse scenarios. RFT extends OpenAI’s fine-tuning techniques to optimize agent policies, potentially improving decision-making in complex environments. For developers and solopreneurs building AI workflows, these tools address the gap between prototyping and production: AgentKit reduces boilerplate code, evals offer reliable testing, and RFT enables targeted performance adjustments. The announcement underscores OpenAI’s push to make agent development more accessible, though practical adoption will depend on integration with existing stacks and the maturity of the tools.