AI Generated Explainer Ebook Maker

I’m Novi, founder of AiPowerCoach, a company that helps professionals adopt AI systems they can actually rely on. In November 2025, I was preparing a PowerPoint presentation to train professionals on essential AI skills. Halfway through, I stopped. Something felt off. In a world where AI can respond, adapt, and reason, a slide deck felt strangely passive. I was explaining how to work with AI using a tool that couldn’t interact, couldn’t check understanding, and couldn’t adapt to the person in front of it. I kept thinking: this should be possible with AI itself. Not as a demo. Not as a free-form chatbot conversation. But as a structured learning experience that could guide someone step by step. That thought was the seed. How I discovered a bigger problem: As I explored that idea, a small but persistent problem kept showing up. Every AI learning experience depended heavily on the person using it. Some people progressed smoothly. Others got lost quickly. The difference wasn’t intelligence or motivation. It was whether they knew how to work with AI. People hesitated. They second-guessed their inputs. They weren’t sure whether they were doing things in the right order. At that point, I didn’t have a theory. I just had a sense that the interaction itself was fragile. From passive slides to active AI learning AI, unlike slides, can listen. It can ask follow-up questions. It can check whether someone understands. It can slow down or move forward. That opened a new possibility: learning with AI instead of learning about AI. But if this was going to replace passive teaching, it had to behave consistently. Especially if a trainer wanted to guide a group, or if people were learning on their own. Without consistency, there is no shared experience. And without a shared experience, learning breaks down. The missing implementation in AI interaction design I started looking for existing work on AI interaction design. What I found was mostly conceptual. Good ideas. Useful principles. Very little that actually ran. There was no concrete way to make a chatbot follow a written scenario and guide a user toward a precise outcome, consistently. No execution model you could hand to several people and expect the same result. No structure that could be reused without rewriting everything. That gap became the problem worth solving. What an S-File really is: The first real constraint I worked on was simple: multiple people should be able to go through the same AI-guided session and progress through it without drift. To make that possible, the AI had to follow rules. That led to the S-File. An S-File is an execution contract: something the AI agrees to run, step by step, without improvising. It’s closer to a small application than a prompt. It defines activities, transitions, validations, and boundaries.