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This tag gathers mini classes around one specific topic. Start with the newest post, then use categories and related reading for context.
Addresses, amounts, and booking slots in AI memory may be stale. Memory can only flag that an address is needed; before acting, reread the value from the record that owns it, such as this order, and stop if they differ.
When AI edits drift further each round, the prompt usually isn't the problem; the feedback can't show a difference. Each round, state what to keep, one visible change, and what not to touch, then compare two versions.
A blank cell isn't zero. Before AI summarizes a spreadsheet, sort blanks into confirmed zero, unknown, and not applicable, and report the denominator and missing values with every ratio.
AI daily briefs mix meetings you accepted, requests from others, and AI's own suggestions. Ranking says what to look at first, not who is waiting on you, so mark each item's status before planning your day.
To teach AI how you work, many start by building a full knowledge base and stall on structure and tools. Start instead from the time AI got it wrong: write the fix as a specific rule, keeping only what changes next time.
Research finds AI memory stores users' mistaken views and makes later answers lean their way. Keep formatting preferences, but before big decisions have AI list its memories and exclude your past opinions.
An AI outage may be short, but workflows often stall longer. Before relying on AI, define the minimum deliverable without it, keep source data outside AI, and name who decides to switch.
An always-on assistant acts while you're away, and the vendor defines which actions are high-stakes. Before connecting main accounts, write your own list: read only, draft only, wait for your yes.