Is it possible with current technology to build an AI version of someone like Alex Hormozi using data from his YouTube channel, books, etc., and a chatbot to talk to that AI version? Is there a straightforward way to build the database for that?

I haven't done it because I find there's very little business utility—these tools tend to work only about 80% of the time and the response quality is pretty poor, so most of this functionality is below the level where businesses would pay for it. My channel is all about businesses, strategies, and systems that businesses will actually pay money for. That said, I could definitely show the simplest, straightforward way to get up and running with this on your own, whether you want it as a hobby project or see an opportunity to monetize it. Here’s how retrieval‑augmented generation works: you feed a bunch of text into a database; the database indexes the text—turning it into numbers, essentially a high‑dimensional vector representation. When you ask a question, the system searches that database for snippets of text similar to your query (like Googling over your own data), retrieves those matches, and inserts them into the prompt for a large language model. The model then answers based on both the retrieved data and its own built‑in intelligence. To illustrate, I drew a quick diagram: RAG stands for retrieval‑augmented generation. Retrieval is just Googling over your own dataset—user inputs a query, the query searches the database, we find however many matches we want, we insert those matches into the LLM’s prompt, and the LLM answers the question. There are many ways to implement this, but the simplest way I’ll cover is using the OpenAI Assistants playground. In the playground you define the assistant’s instructions, then under Tools you enable File Search, upload a text file (I used one of my blog posts, stripped of formatting), and the system automatically creates a vector store and handles the embedding and retrieval for you. As a demo, I asked the assistant, “What are three components to a great high‑ROI automation?” It returned: a clear deliverable, it solves a hot‑button pain point, and you can template most of it. I also showed how to define a “pressing problem” as anything that impacts your ability to generate revenue, and the assistant gave a relevant answer. The result is your own RAG‑enabled chatbot. There are various services—like Chatbase, Botpress, or others—that let you run assistants through their back ends, or they may have their own RAG implementations to charge you for. You can embed this onto your website or service in many ways. I don’t sell it to businesses because I don’t find it very valuable for them, but chatbots are growing in popularity and functionality, so there’s definitely potential there. Hopefully that answers your question—thanks for asking it!