The AI Agent Hype Trap: 95% of Projects Still Don't Make Money
English translation · Original Chinese version available via 中文 toggle.
Agents that demo beautifully often fail the business test: who pays, how much, and which cost line moves? MIT NANDA's 2025 enterprise survey and field anecdotes on PMF vs toolchain tourism.
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The AI Agent Hype Trap: 95% of Projects Don't Make Money
The awkward demo moment
An agent writes code, calls tools, runs workflows — the demo wows. Then ask:
- Who pays?
- How much?
- Which P&L line improves?
Teams go vague. That's the trap.
Evidence stack
MIT Project NANDA — The GenAI Divide: State of AI in Business 2025 highlights a GenAI divide: pilots everywhere, scaled ROI rare. Agent projects amplify the pattern because infra costs and failure modes are hidden in demos.
Three self-deception modes
- Toolchain tourism — new framework weekly, no recurring user
- Internal automation vanity — saves minutes, not headcount or revenue
- Agent = feature — bolted onto SaaS without pricing power
What real PMF looks like
| Signal | Weak | Strong |
|---|---|---|
| Buyer | Engineer enthusiasm | Budget owner with KPI |
| Metric | "Hours saved" (unaudited) | Cost, revenue, or risk $ |
| Retention | Conference spikes | 90-day workflow embed |
Builder checklist
- Price outcomes, not tokens
- Instrument human override — that's where margin lives
- Kill demos that can't name willingness-to-pay in one sentence
FAQ
Q1: Are agents fake? A: Capability is real; distribution and unit economics aren't solved by default.
Q2: Best near-term wedge? A: Narrow vertical workflows with audit trails and existing software budgets.
Dr.Jingle · Opinion · Not investment advice.
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