At 3:00 AM, your on-call pager fires. Users report frozen AI responses. You check logs—no timeouts, no errors. Connection pool exhaustion. A dozen disconnected browsers left upstream streams hanging. The server never closed them.

That's the incident this architecture prevents.

I'm evaluating rohitg00/ai-engineering-from-scratch as an external adopter. Its direction—"Learn it. Build it. Ship it for others"—makes streaming lifecycle management a critical integration boundary. This design is an independently runnable companion, not a claim about the repository's current implementation.

The problem is specific: a disconnected browser must not leave upstream work consuming connections . Streaming tokens is straightforward; owning their lifetime is not.

The Failure Behind the Frozen Stream

The classic mistake starts with requests.get() inside an async def endpoint. The function looks asynchronous, but the synchronous HTTP call blocks the event-loop thread.…