Golden Set

Build an eval framework from scratch for three LLM products (support bot, code assistant, summarizer). Cover architecture, shared infra, per-product customization, and six-month failure modes.

A teammate asks what 'running evals' means in the LLM context. How would an engineer explain it without jargon?

Building a golden dataset for RAG eval from scratch: walk through the steps and name the mistake that wastes the most labeling budget.

Before shipping a prompt change, the lead says 'run it against the golden set.' What is a golden dataset and why does every team need one?

The model provider just updated the model behind the API endpoint. Describe the regression testing process before allowing traffic.

Design a golden eval set for a production RAG system serving a legal research product. Explain how you build it, how big it should be, what each example contains, and what you measure with it.

Design the post-FT eval suite for a customer-support fine-tune

Which buckets MUST a post-FT eval suite include for a customer-support fine-tune?

What's the difference between iterating on prompts by 'feel' (vibes-driven) versus by eval-driven discipline and why does it matter in production?

How do you design a golden eval set for a prompt that can serve as a regression-CI gate in production?

Explain context recall in RAG evaluation and why it is more expensive than context precision

How do you integrate LLM eval into a CI/CD pipeline so regressions block merges?

Order the steps of an LLM CI/CD eval gate from trigger to decision

Compare offline and online LLM evaluation: when is each the right tool?