evaluate.sh

The Problem

Building reliable evaluators is the bottleneck of modern AI development. Every new task, domain, or capability requires carefully designed evaluation criteria—and writing them by hand is slow, expensive, and error-prone. As models become more capable, the evaluation gap only widens.

Our Approach

We are building tooling to automatically generate evaluators given a problem specification. Describe what you want to evaluate, and the system produces a structured, executable evaluation pipeline: scoring rubrics, test harnesses, edge cases, and adversarial inputs—all derived from the problem definition itself.

The goal is to make evaluation as easy as writing a prompt. No more hand-rolling graders. No more evaluation gaps blocking iteration cycles.

Why This Matters

Without good evaluators, you can't reliably improve systems. Without reliable improvement, you can't ship with confidence. Automated evaluator generation closes this loop—letting teams move faster while maintaining rigor.