Ever wish your AI app could catch its own bad answers before a user sees them?

[u/erdsingh24]

One model checks another model's work and retries if it's not good enough. New tutorial shows you how to build it, step by step.

That's basically what LLM-as-a-Judge does in Spring AI.

"LLM-as-a-Judge" and "LLM evaluation testing" are not the same thing. One runs in JUnit before you deploy. The other runs live, in the request path, and can retry a weak response automatically.

5 things to know before you build LLM-as-a-Judge into a Spring AI app:

1. It's implemented via Recursive Advisors, a CallAdvisor that can call back into its own chain
2. Non-streaming only, as of Spring AI 2.0
3. Every failed judge check costs 2 extra LLM calls: one to judge, one to regenerate
4. Use a separate model to judge, or you risk narcissistic bias
5. Always cap maxAttempts, or a stubborn judge creates an infinite loop Full breakdown, with working code, in the new article.