Async and Concurrency Architecture: Fixing AI's Synchronous Blocking Patterns to Improve System Throughput
There is a very common problem with AI-generated code: The code runs, but slows down as soon as multiple users access it. Especially in Python Web projects, even when using FastAPI and functions are written as async def, operations such as database queries, HTTP requests, and large language model (LLM) calls may still block synchronously. The key issue is: async def is merely the entry point of an asynchronous function — it does not automatically turn the synchronous code inside it into asynchronous code. For systems that heavily rely on external I/O — such as web services, knowledge bases, and agent platforms — establishing a unified async and concurrency architecture is an important foundation for improving system throughput. ...