Judging AI agent ideas by failure cost, not demo quality
Few-Garlic2725 · reddit · 2026-10-30
A developer proposes evaluating AI agent ideas by failure cost: not "can the agent do it?" but "what happens when the task is done late, wrong, or not at all?" Mild annoyance means the agent isn't worth much; delayed revenue, compliance exposure, churn, missed SLAs, or another hire signals a real business case.
He argues this separates automation toys from paid capabilities—building the interface around an agent is easy now; the hard part is proving failure is expensive enough, and asks how to test failure cost before building.
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