Sync vs. async vs. event-driven AI requests: what works in production

Re:Sync vs. async vs. event-driven AI requests: what works i... by vishaal_007 on Tuesday January 27, 2026 @10:35AM (#46781371)

In practice, event-driven starts to feel like overkill when requests are short-lived and failures are cheap. If a call is fast, idempotent, and the user isn’t waiting on partial output, a simple sync request is usually the clearest solution.

Queue-based async still works well for batch jobs, offline processing, or anything where latency and ordering aren’t user-visible. The event-driven approach mainly pays off once you have long-lived or interactive requests where failures can happen mid-response and you care about what the user actually sees.

[ Parent | on HN ]

Re:Sync vs. async vs. event-driven AI requests: what works i... by aparnavalsan43 on Tuesday January 27, 2026 @10:42AM (#46781470)

That makes sense. How do you decide early on which requests are likely to “grow into” needing an event-driven approach, versus staying simple sync or queue-based long term?

[ Parent | on HN ]

Re:Sync vs. async vs. event-driven AI requests: what works i... by vishaal_007 on Tuesday January 27, 2026 @10:45AM (#46781519)

In our experience, it usually comes down to whether the request has user-visible state over time. If the response is something you can treat as atomic and either succeed or fail cleanly, it tends to stay simple.

The requests that “grow” tend to share a few signals early on: they stream partial results, they take long enough that the frontend needs progress updates, or failures start happening after something has already been shown to the user. Another common signal is when retries stop being transparent and you start needing to explain to users what actually happened.

Once those patterns show up, teams usually end up reworking the flow anyway. The event-driven approach just makes that lifecycle explicit earlier, instead of letting it emerge implicitly and painfully over time.

[ Parent | on HN ]