A Framework for Building Micro Metrics for LLM System Evaluation
Briefly

System prompts can cause significant issues in production environments, such as mismatched language responses leading to user confusion. The case of a chatbot responding in English after several turns in German exemplifies the complexities of managing AI platforms. Building AI applications involves numerous challenges, especially with large-scale user interaction. Determining what constitutes a 'good' response from a language model remains a subjective and philosophical issue, complicating user experience. Monitoring and managing responses is crucial in AI-driven platforms to avoid misunderstandings.
When you're building an LLM application, what actually makes a good LLM response? It's a pretty philosophical question, because it's actually hard to get people to agree what good means.
We released a change in our system prompts for how we interact with models. Somebody was prompting a model in a non-English language... By conversation turn number five, the model responds in English.
Read at InfoQ
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