Generative AI APIs challenge traditional synchronous access patterns due to their longer response times. Asynchronous AI: event callbacks, such as webhooks and streaming responses, provide ways to improve developer experience and the robustness of applications we build on top of AI APIs.

Phil Leggetter

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Generative AI APIs often experience significant latency, making traditional synchronous responses impractical. To address these challenges, event-driven architectures and asynchronous techniques such as event callbacks, webhooks, and streaming protocols like SSE or WebSockets are suggested. These methods can improve both developer and end-user experiences by accommodating the longer response times typical in AI applications. Discover why reshaping developer experiences with asynchronous AI is essential as these APIs become more integral to business operations.

Asynchronous AI: Why Event Callbacks Are the Future of GenAI APIs

Synchronous responses only work when things are fast #

Why Asynchronous AI is the answer for many GenAI APIs #

Tools need to perform predictably within the operating context they’re used, and also be used only in operating contexts where they can be useful.
If a tool like an LLM cannot respond within a predicable and reasonable response window, it’s great to find other ways of interacting with them to create predicability and reliability. That’s, in fact, a core purpose of engineering.
It’s also good to consider if they’re the right tool to be used to solve a problem.