Hey everyone! We get a LOT of new members every day, and many of you jump in with enthusiasm… and then immediately get swarmed by: • bots with stock profile photos • “DM me for mentorship” sales funnels • vague success promises • people who don’t even use AI but want to pitch things This post is for the real humans who genuinely want to learn, build, and grow with AI. Here’s your starter roadmap 👇 1️⃣ First rule: Learn to spot bots & funnels This community is incredible — when you know how to filter it. Red flags to watch for: • “Drop YES and I’ll help you make income fast” • “DM me” within 2 messages • Lifestyle promises (“I made 20k in 2 days!”) • Zero real builds, zero screenshots, zero proof • Over-friendly messages from accounts created 1 week ago Legit members don’t chase you. They build in public. ⸻ 2️⃣ Second rule: Follow people who show their work If someone doesn’t post: • what they built • how they built it • what went wrong • what improved their workflow …they’re not someone you need to learn from. I personally follow only those who provide actual value: builders, testers, thinkers, problem-solvers. Start small. Follow intentionally, not emotionally. ⸻ 3️⃣ Third rule: Start with ONE person’s breadcrumbs This community hides its best knowledge in the comments, not just the posts. Pick one skilled member and go through: • their posts • their comments under other posts • their replies to questions You’ll find frameworks, prompts, thinking patterns, debugging strategies, and logic you can actually use. If you want a beginner → advanced path, my posts follow that structure: starting simple and getting progressively more technical. ⸻ 4️⃣ Fourth rule: Don’t hoard — apply Don’t be a collector. Don’t fill your Google Drive with 200 prompts you’ll never touch. Instead: • learn one thing • apply it instantly • build something small • break it • fix it • repeat This is the fastest way to grow your actual skillset. ⸻ 5️⃣ Fifth rule: Show your journey

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If l have been blinded side it’s not my intention But the value of community is key And conversations of sharing Finding your feet Help with teaching and understanding of complexities Setting up clones Experts at Hand Dean/ Tony and the many many more in our community Learning a new language connections in and out Makes every day a better one from the last YOU ALL ROCK

The following prompt is designed to be copy-pasted directly into Claude or ChatGPT and will generate a full learning system tailored to the user’s level. Prompt: You are a senior Prompt Engineering instructor and curriculum architect for institutional training. Your task is to design a structured, scalable learning framework that enables professionals and teams to master prompt engineering across multiple AI models (ChatGPT, Claude, Gemini, etc.). Purpose:To empower individuals and organizations to use AI strategically—enhancing productivity, decision-making, and innovation through intelligent prompt design. Objectives: - Build foundational understanding of prompt engineering as a strategic skill. - Teach how to design, structure, and iterate prompts tailored to different AI models. - Develop institutional capacity for AI literacy, experimentation, and deployment. - Provide visual frameworks (tables, diagrams, bullet maps) to support clarity and retention. - Include curated links to authoritative sources (articles, videos, papers) for deeper learning. - Ensure the curriculum is modular, adaptable, and trackable across departments. Structure: 1. Institutional FoundationsWhat is prompt engineering and why it matters for organizations Strategic benefits: efficiency, insight generation, scalable creativity Core principles: clarity, context, constraints, roles, iteration 2. Model-Specific StrategiesOverview of major LLMs: ChatGPT, Claude, Gemini, etc. How each model interprets prompts differently Best practices and limitations per model 3. Prompt Architecture for TeamsDesigning prompts for workflows, reports, analysis, and ideation Role-based prompting, chain-of-thought, multi-turn design Institutional use cases and examples 4. Interactive Labs & Feedback LoopsHands-on exercises for individuals and groups Reflective questions and peer review formats How to analyze and improve prompt outcomes collaboratively 5. Resource LibraryCurated links to trusted sources: articles, videos, research papers Recommended tools for testing, benchmarking, and documentation 6. Intelligence Tracker & Reporting