Practical notes on using AI in a real small business. No hype, no jargon. Just what works, what doesn't, and what we'd tell a friend who runs the place.
The pressure to "do something with AI" pushes a lot of teams into the wrong first move — a flashy demo that never touches real work. The better starting point is dull on purpose: find one task your team already hates, that happens often, and that follows the same shape every time. We walk through how to spot it, how to size it, and how to know in a week whether it was worth doing.
Short, specific reads for the person actually deciding what to do next. Written from real engagements, not a content calendar.
The build works. The launch goes fine. Then reality drifts — a form changes, an edge case shows up, nobody owns it. Here is what keeps an automation alive past the honeymoon.
You do not have a platform team, and you should not pretend you do. A plain framework for deciding when an off-the-shelf tool wins and when a small custom build actually pays for itself.
A good pilot is small, time-boxed, and tied to a number you already track. We share the one-page brief we use to keep pilots honest — and the exit criteria that let you stop one without it feeling like failure.
You can get real value from AI without handing your customer records to a vendor for training. A practical look at retention settings, data boundaries, and the questions to ask before anything sensitive goes near a prompt.
Clean inputs, clear ownership, a place for the output to land. The unglamorous groundwork is what separates a tool people use from a tool people quietly abandon.
Hours saved is the easiest metric to inflate and the hardest to defend. How to baseline the before, count the after, and report a number you would stand behind in front of your CFO.
One practical note when we have something worth sending — never on a schedule for its own sake. No pitches, no funnel. Unsubscribe in one click.