How to Build an "AI Employee": From a One-Off Prompt to an Automated System

"Our team uses AI every day," plenty of business owners say. But when Callan Faulkner, a guest on the AI Explored podcast, dug deeper, she found a different picture: a sales rep finishes a call with a client, then spends an hour "chatting" with ChatGPT or Claude to draft a proposal — and the result is decent, but next time the same process starts from zero. No reusable instructions, no library of past winning proposals, no template for handling objections ever gets saved.

In Faulkner's view, getting a one-off result and building a genuine "AI employee" are entirely different skills. An AI employee is a trained, reusable AI system that performs a specific business function at a human level or better. Her company, The Uncommon Business, generates roughly $40 million a year in revenue with a team of just 50 — a ratio that would have required a far bigger team just a few years ago.

The process starts with three steps: first, identify daily or weekly tasks that make money but don't "light up" the person doing them, or deliver less than $50 an hour in value. Next, document that process in detail — if the documentation isn't good enough for a human, it isn't good enough for AI either. Faulkner recommends doing this as a conversation: explain the situation to the AI, then have it ask "five deep questions" about that exact process.

The resulting instructions are saved as a "skill" — a persistent, reusable set of guidelines. As Faulkner puts it, "the skill is the AI employee." Layered on top of that are the company's knowledge base (pricing, processes, brand voice, past wins and losses) and the ability to connect to external systems, such as a CRM or email.

The most critical step is testing. Faulkner advises wringing every last drop out of each "skill": reviewing the output, manually fixing anything that's off, and feeding those corrections back to the AI with a request to update the instructions. One of her most valuable "skills" — a copywriting skill that replicates brand voice — took 15 hours to get right, but that's still far faster than the three months it would take to train a person to the same level.

Only a "skill" that's passed testing gets put on an automated schedule, running without human involvement. Her "Instagram researcher" skill, for instance, checks competitors' Instagram pages every Monday at 6 a.m., analyzes what's going viral, and automatically logs content ideas into the team's working database — a task the team used to do manually every Monday.