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Evaluating the AI user vs evaluating the AI application — different sides of the same coin
| Feature | SigRank | Braintrust |
|---|---|---|
| What it evaluates | The human operator — how efficiently you use AI | The AI application — prompt quality, model selection, output accuracy |
| The question | Who is the best AI user? | Is my AI app producing good outputs? |
| Headline metric | Yield (Υ) = (cache_read × output) / input² | Eval scores (accuracy, factuality, semantic similarity) |
| Leaderboard | Yes — operators ranked by Yield, class tiers | No — experiment comparison dashboard (your runs vs your runs) |
| Audience | AI operators (developers using AI tools to code) | AI engineers (developers building AI applications) |
| Data source | Operator's AI coding session telemetry (token counts) | Application eval datasets + production traces |
| Scoring method | Computed from token telemetry — deterministic, objective | LLM-as-judge, code-based scorers, human review |
| MCP integration | Yes — SigRank MCP tools for AI assistants | Yes — Braintrust MCP server for coding agents |
| Privacy | Token counts only — never prompt content | Full prompt/response content in eval datasets |
Braintrust is a serious AI evaluation platform. It helps you define what "good" looks like for your AI application, run experiments, score outputs with LLMs or code, and catch regressions before they reach production. It's the right tool if you're building an AI product and need to evaluate the AI's outputs.
SigRank evaluates a different thing: the human operating the AI. Not "is this output good?" but "is this person good at using AI?" Yield (Υ) measures how efficiently an operator uses tokens — rewarding context reuse, meaningful output, and minimal waste. It's the difference between evaluating the tool and evaluating the person wielding it.
They're complementary. If you build AI apps, use Braintrust to evaluate your app's outputs. If you use AI to code, use SigRank to measure your own efficiency and see how you rank against other operators. Both have MCP servers — you can wire both into your coding agent.
Evaluate the operator, not just the app.
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