Hello everyone! I just got done with the 7-day AIS challenge and started building my very own Executive Assistant (EA). I love how easy it was to copy Nate's prompt and paste it into Claude Code without having to worry about the process of building the EA from scratch. However, I was thinking about the structure that it employed and wondered about making certain changes to fit how I want the EA to help my personal needs. Since the EA is most likely going to end up being different for everybody since we all have different preferences and ways in which we structure our lives, I was curious to learn about how you all changed the folder structure to fit your needs (including any sub-agents you added in the process). You do not have to go in detail if you do not want to, any ideas help!

I am new to this world so im unsure which direction to go in but so far i am trying to build an AI-powered business audit system that does not guess, hallucinate, or give generic advice. The goal is for the AI to look at a real business and identify real bottlenecks, missed revenue opportunities, operational leaks, and growth opportunities before suggesting any solutions. I do not want it to just say things like “run ads,” “post more content,” or “improve your website” without evidence. I want the AI to first understand: 1. What the business actually does 2. Who the customer is 3. How the business currently gets customers 4. Where revenue is being lost 5. What the industry pain points are 6. What competitors are doing better 7. Where customers are confused, dropping off, or not buying 8. What operations may be wasting time or money 9. What offers, upsells, premium tiers, or campaigns could realistically increase revenue 10. What changes would create one of these outcomes: - More customers - Customers worth more - Lower costs - Better retention - More efficient operations My question is: What would be the best process, framework, data sources, prompts, or workflow to create an AI business audit system that can diagnose a business accurately before recommending solutions? I’m especially looking for advice on: - What information the AI should collect first - How to verify problems instead of assuming them - How to separate real business issues from surface-level observations - What frameworks consultants or operators use to diagnose businesses - How to turn the audit into practical recommendations like marketing campaigns, upsells, premium offers, automation, cost cutting, or operational improvements - How to make the output useful enough that a business owner would say, “Yes, that’s a real problem in my business” Has anyone built something like this, or can point me toward the right structure? Feel free to tell me of this is a waste of time and pivot to specifics more valuable i am open to suggestions

After following Nate and the general AI industry for the past year, starting to build and practice and do the coursework, I finally locked in my first client!! I can't claim victory on an amazing sales strategy as that part was a God thing but the preparation and skills offered through a lot of Nate's content made it possible. I'm 38. I have a full-time job and a toddler and it was still possible. You can do it!!!

Are most of you still typing everything out, or are you starting to talk to your AI using tools like Glaido (https://app.glaido.com) or other voice-to-AI tools?

I’ve been thinking about this a lot lately. AI right now feels like the internet in its early days, but with one key difference: AI is touching nearly every industry at once. The people who adopt early are gaining a serious competitive edge. What are your thoughts ?