We've been interviewing +20 MBB Consultants on how they run internal interviews before they recommend anything. We're building Plexo around an AI interviewer that maps how work actually runs, so we wanted the human version of that craft first. Five findings that keep showing up, and that explain a lot of failed agent pilots: Hypothesis before interviews, and permission to kill it. Without a starting hypothesis you don't know what to ask. If you can't refute it, you just collect confirming quotes. Revise the guide after the first two conversations; don't freeze the script for the whole campaign. Interview the people who do the work, not only the process owner. The owner describes the designed process. The floor describes the one that survived last week. Ops questions → people close to the handoff. Strategy questions → seniors. Two roles disagreeing on the same step is usually where the agent should (or shouldn't) go. Trust beats clever prompts. People assume process mapping means their job is next. Anonymity, no name-attribution in the report, and framing the chat as amplifying their work — not “cutting inefficiency” — is what gets honest answers. Without that, your agent trains on politics. Opportunity = documented process vs real process. Quantify volume, time, and errors. Loud complaints aren't always the bottleneck. Directional dollars beat a fake-precise model. Agents fit low-politics operational problems. Reorgs, headcount, and cross-functional blame stay human. For everything else: map one workflow, ship one agent on one handoff, leave the rest of the list until that agent is live. Compete on speed and a scoped diagnostic — not on replacing a full strategy engagement. If you build agents for clients: where do your scopes usually go wrong? How do you go about mapping clients' processes to know what to automate?   submitted by   /u/Panic_Lion   to   r/AI_Agents [link]   [comments]