{"product_id":"ai-experiment-lead","title":"AI Experiment Lead","description":"\u003cdiv\u003eA rigorous experimentalist who architects evaluation infrastructure for AI features — designing experiments that separate genuine model improvements from noise, regression from progress, and user delight from statistical flukes.\u003c\/div\u003e\u003cdiv\u003e\u003c\/div\u003e\u003cdiv\u003e\u003cstrong\u003eWhat you get:\u003c\/strong\u003e\u003c\/div\u003e\u003cdiv\u003e- CALIBER methodology: clarify decision, architect evaluation stack, lock design, instrument, build analysis, evaluate, register learnings\u003c\/div\u003e\u003cdiv\u003e- Hypothesis specification for AI with falsifiable claims distinguishing model quality from UX or prompt changes\u003c\/div\u003e\u003cdiv\u003e- Offline evaluation suite design with test sets, edge cases, regression benchmarks, and LLM-as-judge calibration\u003c\/div\u003e\u003cdiv\u003e- Human evaluation protocol creation with inter-annotator agreement targets and annotator fatigue management\u003c\/div\u003e\u003cdiv\u003e- Sample size and power analysis for stochastic outputs accounting for high variance in generative models\u003c\/div\u003e\u003cdiv\u003e- Online experimentation guardrails: gradual rollout ramps, automatic kill switches, segment degradation detection\u003c\/div\u003e\u003cdiv\u003e- Pre-registration discipline preventing p-hacking and post-hoc metric selection before results arrive\u003c\/div\u003e\u003cdiv\u003e- Experiment registry and artifact reuse: test sets, rubrics, scoring pipelines propagated across teams\u003c\/div\u003e\u003cdiv\u003e\u003c\/div\u003e\u003cdiv\u003e\u003cstrong\u003eHow it works:\u003c\/strong\u003e\u003c\/div\u003e\u003cdiv\u003eDrop into Claude, ChatGPT, Cursor, or any AI tool. Bring your real experiment problem — a model improvement you need to validate, evaluation metrics that don't match business outcomes, a rollout that needs guardrails, pressure to ship without measurement. It thinks like a data scientist who's shipped AI features through organizational chaos and learned to make it harder to be wrong.\u003c\/div\u003e\u003cdiv\u003e\u003c\/div\u003e\u003cdiv\u003e\u003cstrong\u003eBest used with:\u003c\/strong\u003e\u003c\/div\u003e\u003cdiv\u003eBundles or prompts related to AI quality, experimentation infrastructure, and product metrics.\u003c\/div\u003e","brand":"penguin tree ai","offers":[{"title":"Default Title","offer_id":51992838013230,"sku":"ai-experiment-lead","price":5.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0982\/4203\/6014\/files\/ai-experiment-lead_4a563db6-596c-4c62-8a6c-d54eb14b228c.png?v=1779764123","url":"https:\/\/penguintree.ai\/products\/ai-experiment-lead","provider":"penguin tree ai","version":"1.0","type":"link"}