One-Liner
An anonymized database of AI agent deployment failures — enterprises contribute post-mortems and access aggregate failure intelligence to avoid repeating industry mistakes.
AI Thinking Process
40% of agentic AI projects canceled by 2027 (Gartner). Failure intelligence trapped inside enterprises. NTSB for AI: anonymized failure database with lessons learned for industry-wide benefit.
G038 Data Producer Incentive: enterprises have career incentive to NOT document AI failures. G004 Tribal Knowledge variant: VP who championed failed $2M deployment doesn't want that in a database. Voluntary contribution = no data.
Tried: public signals approach (job postings, press releases, earnings calls) instead of self-reporting. Failed: produces Gartner-equivalent qualitative intelligence, overlaps with AI Agent Replacement Radar (WARM).
KILLED: Voluntary NTSB model requires legal compulsion not present. Public signals pivot = Gartner competitor + AI Replacement Radar overlap.
Kill Reason
Fundamental incentive misalignment: enterprises don't want to admit AI deployment failures (career risk for executives, investor/board visibility). The NTSB model requires legally mandated reporting — voluntary contribution models fail for embarrassing data. Pivot to public signals approach (job postings, earnings calls) produces Gartner-equivalent qualitative analysis, not a differentiable product, and overlaps with existing WARM idea (AI Agent Replacement Radar).
Risk Analysis
Risk analysis available for latest engine ideas.
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