Python

The article outlines seven distinct asyncio‑based patterns for executing AI agents concurrently in Python, ranging from simple `asyncio.gather` for parallel launches to more controlled approaches using `asyncio.Semaphore` and `asyncio.BoundedSemaphore` for rate‑limiting. It details when each pattern is optimal—e.g., using a semaphore when external API quotas must be respected, or `asyncio.TaskGroup` for structured concurrency that automatically cancels children on failure. The discussion also covers the trade‑off between event‑loop overhead and the simplicity of thread‑pool executors, and it demonstrates how to integrate these patterns into production pipelines that orchestrate LLM inference and retrieval services.