Episode Details

What actually IS ground truth? And who makes it? In this episode, we finally answer the questions we've been hinting at all season: the human work that powers machine learning models, why it matters infinitely more than fancy algorithms, and what happens when your foundation is contaminated. This is the poison gold episode—where four hours of human attention powered 14 months of measurement. 00:00:00 - Where does ground truth come from? 00:02:30 - The single most leveraged artifact 00:04:15 - The 719 touches: hand-tagging at scale 00:10:00 - Why labeling is the real return on investment 00:14:45 - When poison contaminates the gold --- Sources & further reading: • game-senser-fable repo — docs/podcast/LEARNING-CONTEXT.md §§1.2, 3.3 (the • golden session; the prefilled labeler autopsy) • game-senser-fable repo — GAPS.md (the circular-GT premise autopsy) • game-senser-fable repo — HUMANINPUTLOG.md (the 4-hour session; the unused outcome • labels; the rally-67 catch) • game-senser repo — app/labeler (the prefill mechanism, cited via GAPS.md) This podcast episode was fully generated by AI — research, script, voices, and production. Built with Claude, Piper TTS, and automated pipeline tooling.