@Veejay Madhavan This is an invite-only program. We are paying you to post our viral videos, plus we are giving out affiliate commission, so yes, you can double dip. You can apply here, but first watch the video, please. The video is on this page: https://getmakerai.com/clipping

@Richard Gati This is an invite-only program. We are paying you to post our viral videos, plus we are giving out affiliate commission, so yes, you can double dip. You can apply here, but first watch the video, please. The video is on this page: https://getmakerai.com/clipping

@Billy Duque Followed back on Instagram. Make sure to let people know that you followed them as well. Thank you so much.

@Jeff Bode Followed back on FB. Make sure to let people know that you followed them as well. Thank you so much.

@Nicole Bridges @Bryan Mills

https://www.skool.com/aivibecoding/win-i-honestly-didnt-expect-this?p=07b38508

@Renette Kruger re, this is a great first project and honestly one of the best use cases for AI right now. The "ask the expert's brain" app is a proven model, you already named Tony's version, and your client is sitting on exactly what makes it work: a big library of her own content. Most people trying to build this have to go find content. She already has it. That's the hard part solved. 1. Realistic for a beginner with Lovable? Yes. This is very doable. You're not building the AI from scratch, you're connecting proven pieces together, and Lovable handles the heavy lifting. Don't let the "RAG" talk scare you off. 2. Simplest MVP? Start with text only. A clean chat interface where a student types a question and gets an answer trained on her material. No video, no fancy dashboard, no login tiers. Just one thing that works: ask a question, get an answer that actually sounds like her. Get that live, put it in front of 5 of her students, and let their questions show you what to build next. Resist the urge to add everything at once. That's where 99% of people get stuck. 3. Is RAG the right approach? Yes, RAG is exactly right for this and it's simpler than it sounds. Plain English: you load her books, transcripts, and course notes into a knowledge base, and when a student asks something, the app pulls the relevant pieces of HER content and uses those to answer instead of guessing like generic ChatGPT. 4. Has anyone built this with course content? All the time. This exact pattern, PDFs and transcripts feeding a chat trained on one person's voice, is one of the most common things being built right now. You're not in uncharted territory. 5. Biggest challenges to know going in? → Content quality in = answer quality out. Messy, scattered files give messy answers. Spend your time organizing her material before you build. → Keep it sounding like HER. The goal isn't a smart answer, it's an answer her students recognize as her voice and method.