Resources
Positions I end up explaining on most first calls, written out properly so the call can start further along. No client stories and no numbers I have not measured, which rules out most of what gets published about this subject.
Definitions
A chatbot answers questions, an assistant helps a person do their work, and an agent finishes a defined job on its own. The practical test that separates them takes about a minute: ask whether the thing can act inside your systems, whether it writes down what it did, and whether it stops when it is out of its depth. Anything that fails those three is a chatbot, however it is described in the deck.
Design
An agent should stop and fetch a person on three triggers: when its confidence in its own answer is low, when the cost of being wrong is asymmetric, and when the request falls outside the list of things it was told it handles. The failure that actually hurts a business is rarely the agent getting something wrong. It is the agent getting something wrong quietly, and nobody finding out for six weeks.
Voice
An AI receptionist is worth having when you are losing calls you could have converted, and it is worth nothing otherwise. Whether the technology works is settled; it does. The question is whether missed calls are actually costing you money, whether the caller can tell they are speaking to software, and whether a named person picks up when the call stops being routine.
Delivery
An agent is in production when it keeps working on a day nobody is watching it, and when you can prove afterwards what it did. A demo shows the happy path, which is roughly a third of the work. The rest is access limited to what it actually needs, the cases nobody thought of, a record you can read back, monitoring that notices silence, and a named person who owns the outcome after everyone has gone home.
More are planned. I would rather publish pieces worth reading than pieces that exist to fill a page, so they arrive when they are finished. Ask me something and it may well become the next one.
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