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Jun 27 2026 · 1 min read · AI at work

How to give AI the context it needs before automating work

AI needs reusable operating memory: decisions, task rules, examples, and SOPs that define what good work means inside the business.

AI cannot do reliable work inside a business if the rules and examples that define good work only live in an operator’s head.

A recent example involved an operator bringing a virtual assistant into the sales and admin side of a service business. On paper it looked simple: give access, explain the process, and start helping. The real work was everything underneath that. Which records should the assistant touch? How should a lead be marked after follow-up? When should a same-day task be created? Where should the handoff live so nothing gets buried in a comment thread?

A good operator carries those rules without always recognizing them as operating knowledge. A new employee needs the rules to work consistently. AI needs them for the same reason.

A meeting transcript is a starting point, not the answer. Pull it into AI and ask for four things: decisions, task rules, owners, and steps worth turning into short instructions or a standard operating procedure. Review the output yourself before it becomes the standard, then save the useful pieces where the team already works.

A summary that sits unread changes nothing. One page explaining how missed calls are handled, plus one example of a clean handoff, gives the next employee and the next AI request the same standard to follow.

Start with one process that keeps getting re-explained. Turn the next conversation about it into short instructions and one worked example, then save both where people and AI can use them.

Always expect friction.

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One idea you can use, in about a minute.

New notes from real operating work, sent as they are written.