HOW TO BUILD AN AI ACCOUNT QUALIFIER THAT THINKS LIKE YOUR BEST REP

Summary from the TLDR Founders newsletter

MedScout put one of its best AEs on a projector and recorded everything. Which tabs he opened. Where he paused. What made him say "this one is interesting" versus "this one is not." That tacit knowledge usually lives in someone's head as pattern recognition and never gets documented, which is why most AI account qualifiers fail. The next time someone on your team says "we should automate qualification," the right first question isn't which model to use. It's whether anyone could write down what your best rep is actually doing.