HEY THERE
I’m Sean Shoemaker, MSN, RN, a registered nurse with more than a decade of experience across multiple specialties and healthcare settings, and the founder of The AI Preceptor.
When I started learning and using AI, it felt a little like a scavenger hunt. There was plenty of information available, but it was spread across courses, webinars, videos, articles, research, and tool reviews. It was difficult to sort through, and harder still to see how it connected to healthcare.
As I gained experience and developed skills, I started creating resources to help others make sense of AI. People found them helpful and asked for more, and that inspired me to create The AI Preceptor. The initial plan was a series of introductory guides that organized the information in one place, explained it in plain language, and gave people a clearer place to start. In many ways, I was creating the kind of resource I wished I had when I was learning.
But as I continued teaching, sharing information, helping others with their projects, and talking with healthcare professionals about AI, their questions changed the direction of The AI Preceptor. What they were asking for was not what I was creating, and that changed the approach.
People often want a "win" before they want a course. Most of the questions I hear are about something they need to get done: Can AI help with this? Which tool should I use? It did not work, now what? They want to see AI help with their own work first, and learn from there.
People are starting from very different places. Experience, confidence, access to tools, digital skills, and feelings about AI are all different. Those differences should be considered when teaching AI and should help shape how it is offered.
AI skills and digital skills are not always connected. Using AI with a spreadsheet, presentation, document, screenshot, or research requires some comfort with those tools. When those tools are part of the task, the teaching should include them too, not only how AI can support them.
AI will keep evolving. Models, features, and responses change, so what people learn should not depend on one prompt or one tool. The learning should include how to approach the task, how to evaluate the response, how to troubleshoot, and what to do next.
Those are some of the lessons that helped shape The AI Preceptor.
In healthcare, when someone starts on a new unit, steps into a new role, or learns a new way of working, they are often paired with a preceptor.
A preceptor helps connect knowledge to practice. They show you around, answer questions, share what experience has taught them, help you work through problems, and support you as you become more comfortable and independent.
The AI Preceptor brings that same approach to AI education: practical guidance, healthcare examples, troubleshooting, and support when something does not go the way you expected.
I teach nurses and healthcare professionals how to use AI, so I want to be transparent about how I use it in my own work.
I may use AI to organize ideas, explore different explanations, test prompts, compare approaches, identify gaps, troubleshoot responses, and help with editing or formatting.
I also use AI thoughtfully, with attention to privacy, security, and the type of information involved. What is appropriate depends on the tool, the setting, and the guidance or protections that apply.
AI-generated content is never simply passed along as my finished work. I review it, question it, revise it, and shape it so the final result reflects my own ideas, experience, judgment, and voice.
The experience behind The AI Preceptor does not come from AI. It comes from nursing, teaching, and the time I have spent learning, testing, and working with AI tools.
AI supports some of the work I do. It is not the work that I do.
The goal is to help you use AI to support the work you’re already doing, with less time spent figuring out the tool and more time getting the benefit from it.
The starting points come from what nurses and healthcare professionals say they struggle with, and you can get oriented through the free resources before ever opening an AI tool. Using technology at work every day is not the same as being taught those skills or feeling confident with them. That is a training gap, not a deficiency. The same is true of titles. Professional expertise, digital confidence, and AI experience do not always develop at the same pace. A role or title may reflect deep knowledge and responsibility without showing what opportunities someone has had to practice with unfamiliar digital tools or AI. That is not a criticism of anyone. It is a reminder that almost everyone is learning this technology in real time.
Learn practical ways AI may support clearer communication, more efficient workflows, and work you can confidently review and stand behind. When AI saves time or improves quality, it is because of what you bring: the goal, the context, the guardrails, and the judgment about what fits. There is still so much of you in that work.
The focus is not on mastering one tool but on habits you can carry across tools, roles, workplaces, and future changes in technology. Two healthcare professionals in the same specialty can have different access to AI tools and approved uses. That is why the focus is on skills that can transfer as tools, policies, and access change. The tools belong to the workplace. The skills belong to you. And the same skills that teach you to use AI teach you to evaluate it: you learn to ask what a new tool is designed to do, where it may not fit, what its limits are, and what still requires human review.
AI may support certain nursing and professional tasks, but it does not replace clinical assessment, professional accountability, or organizational requirements. A consistent review habit can support safer, more thoughtful use as tools change.
AI continues to evolve in healthcare. A strong foundation allows you to adapt confidently, strengthen your current role, and stay prepared for what comes next.