start-evals

What problem does it solve?

Reduce overengineering and uncertainty when validating AI features by providing a concise, repeatable evaluation starter that emphasizes error analysis over premature automation. The approach helps teams quickly surface failure modes with a small, high-value set of tests so they can iterate product and model improvements faster.

Core Features & Use Cases

• 20-test starter kit: Generates 15 happy-path and 5 edge-case test cases suitable for spreadsheet-driven QA.
• Pragmatic workflow: Includes a spreadsheet template, run-and-record guidance, and a Week 1 workflow to get results in 30–90 minutes.
• Scale and next steps: Guidance to graduate from 20→50→200+ tests, options to build an LLM-as-judge, and optional project creation for tracking.
• Use cases: Validating product recommendations, customer support assistants, summarization features, and retrieval-augmented generation systems.

Quick Start

Type /start-evals "AI product recommendations" to generate 20 spreadsheet-ready test cases, pass/fail criteria, and an actionable evaluation workflow.