I run a two-person design studio, and we subcontract the overflow. Last spring a subcontractor invoiced us for a site build that was half finished. The missing half only showed up when a client clicked through it live. We ate the rework cost because proving incompleteness would have meant a line-by-line audit worth more than the invoice itself. Now swap both studios for software agents. One agent commissions a task while another reports it finished, and money moves on that report. A plain smart contract cannot look at the deliverable at all. It depends on an outside report, and that reporter is the middleman where the trustless part stops. That is the gap @GenLayer built Intelligent Contracts to close. Being Python programs, they can pull the deliverable themselves and put the question to a language model: does this match what was actually ordered? The leader validator proposes a verdict, then the rest of the set re-runs the same check on its own models. Payment settles only when those independent reads converge. Their answers do not need identical wording. The Equivalence Principle asks whether the separate reads point at the same conclusion, and a split sends the job to a fresh leader or a bigger appeal panel. The film shows the shape of it in one minute: a booking page gets fetched, a model weighs the refund question, and the validator set lands on one answer. That final card about contracts that follow rules versus contracts that understand them finally landed for me here. Following is easy when done means a checkbox, while understanding is what done actually requires. In your own work, who currently referees the gap between "done" and "actually done": a client, a platform, or plain silence? I read every answer.