Episode Details

B3 achieved 72% after human audit—a significant jump from V2's 46%—but fell short of the frozen 80% bar set before grading began. Using the high jump metaphor, the hosts explore why an impressive personal best still means no advancement when the line is drawn in advance, and how the system itself worked even when the pipeline didn't. A meditation on standards, measurement, and why the bar doesn't move. 00:00 - B3 Results & The Frozen 80% Line 03:45 - The High Jump: Why Personal Bests Don't Lower Bars 07:20 - V2 vs V3: Architecture Changes 10:30 - Window Placement & Rally Detection Problems --- Sources & further reading: • game-senser-fable repo — docs/podcast/LEARNING-CONTEXT.md §9 (the precondition • session and the §9.6 audit) • game-senser-fable repo — src/gstaadwindowsv3.py + src/out/gstaadwindowsv3.json (the • frozen build) • game-senser-fable repo — src/out/gstaadv3eval.json + gstaadv3humancheckkey.json + • HUMANINPUTLOG.md 2026-07-28 (every verdict, the pre-committed key, the audit) • game-senser-fable repo — src/out/saqpresence517318.json (the banked Saquarema • anatomy) This podcast episode was fully generated by AI — research, script, voices, and production. Built with Claude, Piper TTS, and automated pipeline tooling.