How do you test an LLM application before release?
You test an LLM application before release with a domain-specific eval suite that runs automatically on every change, plus adversarial, retrieval and load testing. Build the eval set from real queries in your domain, each with an expected answer or scoring rule, and measure accuracy, hallucination rate, factual consistency and toxicity rather than relying on generic benchmarks. Wire it into CI so a lower score after any prompt, model version or retrieval change blocks the deploy, the same way a failing unit test would. Providers update models often, so this regression gate matters as much as the first run. Add red-teaming for prompt injection, jailbreaks and data leakage. If the application uses RAG, audit context relevance, faithfulness and completeness separately to find where answers drift from their sources. Run throughput and tail-latency tests under realistic load to find the breaking point. After launch, compare live outputs against the eval baseline so quality drift raises an alert before users notice.
