AI in everyday operations

Making AI part of everyday work

A tool that works in a test still has to survive a busy Tuesday, so here is how to place one AI step inside a job people already do.

Your source material decides the answer, so here is the work to do on your documents before an AI tool ever reads them.

What really changes inside a role when AI removes hours, and how to talk about it before the rumour does.

How to turn a vague sense that AI is helping into one honest number you can decide on.

AI jobs rarely fail outright, they fade. Ownership is what stops that, and it means three specific things rather than a line on a job description.

How to tell your first AI job is finished, and how to pick a second one that teaches you something the first could not.

How far a wrong answer travelled decides what it costs you, and what you should do in the hour after you spot it.

Three people have to agree the standard before an AI step touches real work, and it has to be a standard a reviewer can apply in seconds.