AI can make you sound fluent in a domain you don’t understand. People who actually know find out very quickly. Credibility gone in the token exhaust of an LLM prompt.
Most of my work at Jeavio now puts me across the table from people who are subject matter experts. My job is to support them in figuring out an AI strategy that works. I need to learn about their world fast. So I do what we all do now. I ask Claude to write me a brief.
What comes back is fluent, citable, and plausible-sounding. That is the problem. The brief describes a clean, general version of the domain. My client lives in a messier, specific one. The framing is often “a view from nowhere”, lacking context and subtlety. It also falls apart under the mildest scrutiny.
Everyone is worried that AI will replace knowledge work. From where I sit, the AI won’t replace you. It will get you fired.
The well-known phrase “The map is not the territory” is relevant here. LLMs are great at building maps. Flattening topographical details into pleasing shapes. But their output can be far removed from what is happening on the ground.
So the scarce skill is taste. Taste is a constraint, not a capability. Figuring out what output from the AI is relevant and how to use it to do useful work. To do so well requires restraint and a willingness to close the laptop and talk to a human.
Enthusiastically credulous use of AI is a problem I have seen show up in all phases of client engagements. Product managers creating AI-generated PRDs bloated with features no one asked for. Engineers embellishing their code, laying the ground for technical debt later.
I don’t think this is a hopeless situation. Working well with AI involves understanding where it can add value and where you have to roll your sleeves up and jump right in.
Today, I still use Claude to write briefs and to get me oriented. But then I interview the experts, ask lots of (sometimes very dumb) questions. I focus on the tribal knowledge, the context that doesn’t appear in documents or wiki pages. Only then do I hand it back to the model and let it do what it is good at: collating what I have gathered and drawing me a sharper map.
Maps are the easy part. The accurate ones still need someone who has walked the territory. To be human in an AI-mediated world is to become an explorer.