Prompt libraries rot. Build evaluation sets instead.
A prompt that worked last quarter is a liability this one. What to keep instead, and how to know when the output has drifted.
01 — Why libraries rot
Models change, offers change, and the person who wrote the prompt has left. What survives is not the instruction but the example of a good answer.
02 — What to keep instead
Twenty cases with the output you would accept, and the rule that decides pass or fail. When the model or the offer changes, you re-run them and see the damage in an hour.
Olga Bialkovich Founder · AI and marketing strategy Olga founded the lead-generation product that now runs as U [in] AI, and she sets the direction of the lab: which parts of marketing are worth automating, and which stay with people. Her working claim is a practical one — a system built around the right profile and the right message takes up to 60% out of the cost of finding customers and partners. 
U [in] AI founder Olga Bialkovich publishes new article on AI agent consistency in Unite.AI
Another conversation around U [in] AI has made its way into the international AI media space.
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Three agents, one lead flow: the math behind −62%
We rebuilt qualification for an agri-tech distributor. Every number, every hand-off, every mistake on the way.