Agents3h ago
Apple Research Generates Synthetic API Agent Data
Apple researchers developed a method to generate training trajectories for API-calling agents without using executable environments. The approach uses LLMs as digital world models to simulate stateful interactions based solely on API specifications. This removes the need for pre-populated backend databases. Developers can now scale agent training without building complex, functional testbeds first.