A new paid coaching program aims to help high school students critically engage with AI-generated projects by emphasizing real-world testing and transparent decision-making. Students will build products using AI tools, then gather user feedback to refine their work, with progress tracked through a dashboard that highlights their reasoning—such as why they accepted or challenged AI suggestions. The approach seeks to move beyond polished outputs by documenting coaching discussions and adjustments made in response to actual user input, rather than relying on AI-generated summaries. The initiative raises questions about how to measure independent judgment in AI-assisted work and invites discussion on potential blind spots in the method.
When a student builds something with AI, the finished product only tells us so much. It might work well, but that doesn’t show us what the student understood, which decisions they made, or whether they questioned any of AI’s suggestions. For transparency, I’m starting FirstShip, a paid one-on-one coaching program for students in grades 9–11. I’m preparing the first cohort, so I don’t have student outcomes to share yet. I’d like to discuss the educational approach behind it. The program focuses on two things. Putting students’ work in front of real users. Students use AI to build a product, then find out whether people actually use it and return to it. They talk to users, look at feedback and usage data, and decide what to change. That gives them something outside the AI conversation to test their assumptions against. Making students’ decisions visible to parents. Through a weekly dashboard, parents can follow the work, user feedback, and the reasoning behind key decisions. What did the student accept or question from AI? Why did they choose one approach over another? What happened when they tried it, and what changed their mind? Private coaching conversations stay private. The challenge is that a decision log could become another polished output generated by AI. My proposed approach is to have students explain their reasoning during coaching sessions and revisit earlier decisions as real feedback comes in. I’d want the dashboard to reflect those discussions, rather than simply collect written summaries. The program details, my background, and pricing are at firstship.space. I’m sharing the link so the context and commercial interest are clear. What would you consider convincing evidence that a student is exercising their own judgment when working with AI? I’d particularly welcome thoughts on what this approach could miss or get wrong. submitted by /u/Chemical_Emu_6555 [link] [comments]
