How AI helps
Useful AI starts with a real work situation. Choose a path, read the practical stories, and open the Build Log when you want the technical reasoning behind the outcome.
Browse all AI at Work storiesFind the work problem you recognize
These paths are not categories for AI tools. They are common work situations. Choose the one that sounds familiar, then follow the practical stories and their technical field notes as far as you need.
Start here when a status, save, metric, or AI output looks finished but the real outcome still needs evidence.
Start by asking: Ask what has actually been observed, what is still assumed, and what would count as proof.
Start here when important work lives in comments, memory, or scattered places instead of a shared home.
Start by asking: Ask what the next person would need to know without becoming a detective.
Start here when a suggestion, dashboard, or convenient default is making a consequential choice less visible.
Start by asking: Ask which decision still belongs to a person and what evidence should be visible before it is made.
Start here when recurring manual fixes, surface complaints, or unclear instructions point to a wider workflow problem.
Start by asking: Ask what repeats, where the path really fails, and which small change would make the work easier to run.
Start here when a release, cleanup, or improvement needs a clear outcome, not only a completed-looking step.
Start by asking: Ask what should happen next, who checks it, and what result proves that the work actually landed.
Start here when first use, navigation, or a scattered model makes a simple next step harder than it should be.
Start by asking: Ask what a person needs at the precise moment they begin, arrive, or choose where work belongs.