When I published the first article about the Neuron AI Router, I expected questions about routing rules. Which rule to use for structured output, how to write a custom one, how the round robin behaves under load. Some of those questions arrived, but the most frequent one was different, and it wasn't really about routing at all. It was about failure. What happens to my agent when the provider goes down?
It is a fair question, and if you are new to building AI applications it deserves a proper answer before we look at any code.
Here is the short version. The new fallback strategy in Neuron AI Router lets you define an ordered list of LLM providers for your PHP agent. When an inference call fails with a transient error, such as a rate limit, a timeout, or an overloaded server, the same request is automatically retried on the next provider in the list. The failover is transparent: the agent never knows it happened, and the conversation continues without losing state. The rest of this article explains why this problem exists, why the usual solutions fall short, and how to configure it.
Why LLM providers fail in production
An LLM provider is an external service you talk to over HTTP. Every time your agent thinks, it is making a network call to a machine you don’t control, operated by a company that is currently serving millions of other requests. These services fail in very ordinary ways. You hit a rate limit because your traffic spiked. The provider returns an “overloaded” error because their traffic spiked. A request times out. A deployment on their side causes a few minutes of elevated error rates. None of this means you did something wrong, and none of it is rare. If you keep an agent in production long enough, you will see all of these.
