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Environment-free Synthetic Data Generation for API-Calling Agents

Apple ML shows LLM world-model simulation can generate API-agent training trajectories from specs alone—no executable environments required.

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Apple paper: keep specs, schemas, tool config, and constraints; drop session traces. Selective shared memory beat both no memory and full history.

agent-memoryapplepersistence

16 Sept 2026

Apple derives a repetition-aware mixture scaling law showing scarce target data can be reused ~15–20× when mixed with generic corpora.

Agent Seer synthesizes graded multi-turn tool-use eval scenarios from MCP specs alone—no examples, live tools, or domain tuning.

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