Kitchen table
A chatbot answers your question and stops. An agent gets a job. 'Plan the class trip' means it looks up the museum's opening hours, checks the bus timetable, counts the pocket money, notices the museum is shut on Monday, and picks Tuesday instead – step after step, checking its work as it goes. It is the difference between asking a friend what to cook and having a friend who goes shopping, cooks, and washes up. Exciting, and it had better wash up properly.
Whiteboard
A model plus a loop plus tools plus state, and the model is the smallest part. The harness is where reliability is won or lost: what the agent may touch, how many turns it gets, what it does when a tool fails, when it must stop and ask a human, how its work is verified before anything irreversible happens. Plan for partial failure as the normal case. An agent that cannot be interrupted, resumed and audited is a demo, whatever the launch post says.
Boardroom
This is the shift from AI that advises to AI that acts – booking, filing, purchasing, reconciling – and that is where the real value is, because advice still needs someone to act on it. It is also where the governance questions begin in earnest: an agent holds credentials, touches systems of record and leaves consequences, so it deserves the controls you would give a new employee – limited permissions, an audit trail, a probation period, and someone accountable for what it does. Autonomy is granted in degrees, and earned.
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