Using Temporal to Optimize LLM Requests

Wed, 23 Sep 2026 00:00:00 +0000

When building AI-powered features, two operational concerns appear immediately: latency and cost. Calling an LLM third party service typically takes 1 to 3 seconds and incurs token costs on every request.

We recently tackled this while building AI features for Molita.co. Imagine 10 users asking the exact same question (for example, “What is Ikigai?”) at the same time. In a naive setup, your backend fires 10 simultaneous API calls, burns 10x the tokens, and risks hitting external rate limits (429 Too Many Requests).

Concurrency on Erkid Hoxholli

Using Temporal to Optimize LLM Requests