We want our middle managers to start building their own custom AI prompts and mini-workflows, but they are stuck waiting for IT to do it for them. How do we use Kolb's Experiential Learning Theory to move our managers from passive spectators to active experimenters who own their own automated workflows?

Question

Tyler Smith · Accepted Answer

You cannot train your team to build AI workflows by having them watch a slide presentation or read a software manual. To build true capability, you must guide them through the four distinct stages of Kolb's Experiential Learning Theory: Concrete Experience, Reflective Observation, Abstract Conceptualization, and Active Experimentation. Start by pushing them directly into a low-risk Concrete Experience. In your next departmental alignment meeting, have every manager log into an AI tool and attempt to write a basic prompt to automate a simple, daily task, such as drafting a meeting agenda. Do not worry about perfection; just get them hands-on. Next, move to Reflective Observation. Have the managers share what worked and what failed. Let them discuss why certain prompts produced hallucinated or useless results. This leads naturally to Abstract Conceptualization, where you introduce the core principles of prompt engineering, such as providing context, defining a role, and setting formatting rules. Finally, transition them into Active Experimentation. Challenge each manager to pick one highly repetitive task on their personal weekly to-do list and commit to using an AI prompt to assist with it for the next two weeks. Have them report their findings at your next Level 10 Meeting™. By turning training into a continuous, experiential cycle of doing, reflecting, learning, and testing, you remove the fear of technology and build a team of self-sufficient operational innovators.