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How to Know When an AI Agent Can Work Unsupervised — Evan Kormos, Coinbase
5d ago · English audio
Evan Kormos, a player-coach at Coinbase with 15 years in enterprise financial services, lays out a practical way to bring agents into policy-driven, regulated workflows. He models processes as DAGs and loops, explains why a loop is only as trustworthy as its check, and shows how evals and traces become a new confidence mechanism. Agents then move through three stages: fully supervised, then sampled, then humans…
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Outlier score
This score was measured on Sun, 25 Oct 2026 12:13:19 GMT. Current view counts may differ.
17.1K views ÷ a 5.2K baseline = 3.3×. Compared with 38 earlier videos from the same channel, matching the format recorded at scoring time. Older-upload baseline: reference videos had at least as long to gain views. This comparison is not age-matched.
YouTube snapshot: Sun, 25 Oct 2026 15:30:44 GMT. Counters may have changed.
Read the methodologyGenerative AI & Agents
Channel-balanced percentile: 45
Comparison details
43 videos from 32 other channels, with each channel weighted equally. Same format and language, with 100,000–999,999 subscribers. Observed at 137 hours after publication, within ±27 hours.
This describes the collected sample, not all of YouTube. Updated Sun, 25 Oct 2026 15:44:36 GMT.
Niches & tags
AI evaluation, societal implications, governance and responsible deployment.
Transcripts and detailed analytics are available for recent outlier Shorts up to three minutes. Research tools