[Full Workshop] Building Metrics that actually work — David Karam, Pi Labs (fmr Google Search)
Jul 29, 2025 · 40:28
Achim and David Karam, former Google Search leaders now at Pi Labs, argue that building reliable AI evaluations requires a multi-signal scoring system rather than single LLM-as-judge metrics. They walk through designing custom metrics starting with simple correlated signals, using a copilot to generate and iterate on dimensions like 'includes insights' or 'title length,' then calibrating them against ground truth thumbs up/down data from users. The workshop demonstrates applying this to a meeting summarizer, integrating the scoring system into Google Sheets to score 120 examples and produce a confusion matrix showing alignment with human feedback. They also show how to use the same scoring system for model comparison (e.g., GPT-1.5 vs 2.5) and online best-of-N sampling, which boosts response quality by generating multiple responses and selecting the highest-scored one.
