Stop Shipping Hallucinations: Automating RAG Faithfulness with Spring AI 1.2

If you’re still "vibe-checking" your RAG outputs in 2026, you’re not an engineer; you’re a gambler. Enterprise-grade AI isn't about getting a cool demo—it's about proving your model isn't hallucinating before a single customer sees the response.

Want to go deeper? javalld.com — machine coding interview problems with working Java code and full execution traces.

Why Most Developers Get This Wrong

The "Looks Good" Trap: Relying on manual spot-checks. If your test suite doesn't have a quantitative threshold for "truthfulness," you're just waiting for a production incident.

Confusing Retrieval with Accuracy: Just because your vector search returned the right snippets doesn't mean the LLM didn't hallucinate a "no" into a "yes."

Ignoring the Context Window: Developers often forget to verify if the LLM actually used the retrieved documents or just hallucinated from its own training data.

The Right Way

The industry standard in 2026…