Most AI teams know evaluations matter. But when you try to design them for your use case, it often starts as a blank page. Eval Sakhi is a small AI agent that turns your AI idea into a structured eval plan — defining what “good” looks like, key metrics, failure modes, and how to test before deployment. It’s not another eval tool — just a way to move from “I know this matters” to “I know where to start.”

Tempo - Align Work to Strategy — Turn Jira Data Into Strategic Clarity

Turn Jira Data Into Strategic Clarity

Here’s a strong first comment — aligned with your tone, and structured to drive interaction 👇 --- I kept running into the same problem while building AI systems: I knew evaluations mattered… but every new use case started with a blank page. What should I measure? What could go wrong? What does “good” even mean here? So I built Eval Sakhi over a weekend to structure that thinking. — Here’s a quick demo of how it works ↓

— If you want to try it, here’s a prompt you can paste: “I want to build an AI shopping assistant that looks at things I want to buy and tells me if it’s an impulse purchase or something I genuinely need. It should consider my past behavior, price, and how often I’ll actually use it.” — Would genuinely love to hear how others here are approaching evals — still figuring this out myself 🙏