My name is Edward, and I’m excited to be part of this community. I’m currently exploring ways to build multiple streams of cash flow using AI, and I’m in the early stages of learning how to use different AI platforms efficiently and effectively. While I’m still very much in the learning phase, I already see AI as a powerful tool for productivity, creativity, and problem-solving across many areas of life and business. Alongside this, I dabble in nutrition coaching, working with both athletes and everyday people who want to improve their health and performance. I’m interested in how AI can enhance coaching, education, and scalable systems that help people get better results with less friction. What brought me to this community is the opportunity to learn from people who are further along than I am. I’m here to absorb knowledge, exchange ideas, and grow my skill set. My hope is that as I learn, I’ll also be able to contribute value back to the group in whatever way I can. Looking forward to learning alongside all of you and seeing what we can build with these tools. Best regards, Edward

Hello everyone,🤝 My name is Masoud, and I’m based in the Northwest of the UK. I’m an experienced HGV driver, NOT AI or IT languages.Currently expanding my skills through online cybersecurity studies. I’m pleased to be part of the Skool community The AI Advantage , and look forward to learning, contributing, and growing alongside like, minded people. Family is very important to me—I’m a proud father of two—and I enjoy spending time outdoors whenever possible.🫶🌹☕

I am using ChatGPT (paid version) to help me with some of my designs for something, but it's not quite getting it right after hours of back and forth and explicit instructions. I am hoping that somebody here can help direct me to some AI that will help me with my visual mockups. I don't know where to go.

A lot of AI “adoption” discussions stay at the mindset level. Useful, but I’ve found progress usually comes from much more boring mechanics. What’s worked best for me so far: 1. Pick a task with a small blast radius.Summarisation, classification, first-draft support. If it fails, it’s annoying — not dangerous. 2. Define “good enough” upfront.Not “be smart”, but constraints like: cite the source, ask clarifying questions when unsure, and never take actions without human confirmation. 3. Design for being wrong.Assume the model will misunderstand. Make uncertainty visible, log failures, and do a quick weekly “what broke?” review. 4. Only then scale.If one narrow use case isn’t reliable and repeatable, adding more prompts/agents just multiplies confusion. Confidence with AI has come less from mindset shifts and more from seeing the same small workflow work 10 times in a row without surprises. Curious what others here consider a “safe first win” use case — especially ones that still hold up after the novelty wears off.