Joby's Electric Air Taxi Flew Over Manhattan. Passengers Are Years Away.
Joby pulled off a splashy Manhattan demo, but FAA certification and the hard economics of eVTOL still stand between the company and fare-paying riders.
A discussion circulating on Reddit r/artificial this week put a sharp point on something the enterprise AI world has been quietly dreading: when an AI agent takes a bad action — not a bad answer, a bad action — who is legally and financially responsible? The question is not hypothetical anymore. Agents are moving money, filing documents, sending emails on behalf of users, and integrating into workflows where errors have real downstream consequences.
The liability structure right now is a vacuum. AI vendors disclaim responsibility in their terms of service. Companies deploying agents argue they're just using a tool. End users assume someone upstream is accountable. In practice, when an agent approves the wrong invoice or sends a message it shouldn't have, everyone points at everyone else and lawyers start billing hours.
Whoever builds a credible, enforceable answer to this question first — whether that's an insurance product, a contractual standard, a regulatory framework, or a technical audit trail — will have something genuinely valuable to sell to every enterprise deploying agents. The agent economy's next big unlock is not a better model. It's a liability layer.
Joby pulled off a splashy Manhattan demo, but FAA certification and the hard economics of eVTOL still stand between the company and fare-paying riders.
A viral post argues the biggest productivity wins come from stable workflows around any good-enough model — not from upgrading every time benchmarks shift.
A Montana mother of six is fighting a proposed data center larger than the Grand Coulee Dam. So far, she's mostly fighting alone.