How to become one of the top 1% Vibe Coding experts in the world within 6 months? (Attached is a complete nanny level roadmap) To be honest, many people think Vibe Coding is just downloading an AI tool, inputting a vague requirement, and then waiting for a miracle to happen. That's not called mental programming, that's called buying lottery tickets. Using this gameplay, you will only fall into a vicious cycle of fixing bugs and creating new ones. True Vibe Coding is a very hardcore building system, with the core being four words: scratch first, then do. If you want to truly turn your ideas into profitable products that can go live, don't go to those theoretical tutorials that will never produce a finished product. Take this 6-month nanny level roadmap directly, it's all plain language, just follow it. 1. In the first month, beginners love to skip the basics when they lay a solid foundation, but as soon as the code reports an error, they will catch it blindly. You don't need to be proficient in programming, but you must understand jargon. You need to understand the operating mechanism of the web, as well as the front-end, back-end, and API. You must master Git, it is the only lifeline when your code crashes. Finally, lock up a set of technology stacks. It is recommended to add Next.js, Supabase, and Vercel, don't mess around blindly. 2. In the second month, choose the right weapon and use Lovable directly for rapid prototyping based on zero foundation. Basic developers choose cursor with closed eyes and are proficient in multi-agent parallelism. Hardcore geeks use Claude Code to take over your entire codebase. Remember an iron rule, every project root directory must create a rule file to establish rules for AI in advance. 3. In the third month, master the architecture and prompt words. Don't let AI write code right away. It is necessary to first write a product requirement document, clarifying the target users and success criteria. Learning to feed clean structured documents to AI can save it half of its mistakes. Large projects must be developed using specification driven approaches, allowing specification documents to guide AI rather than relying on your imagination to perform on the spot. 4. In the fourth month, build a real business project and stop writing bad weather forecast apps. Go solve the real pain points of vertical industries. Establish an error prevention loop: always let AI come up with the plan first, then let it write code after you approve it, and after finishing it, throw it to another large model for security review. And it is necessary to let AI write test cases first, which is the only antidote to prevent code collapse. 5. In the fifth month, advanced MCP and true masters of contextual magic know how to feed data to AI. You must master the MCP protocol to enable your AI to directly connect with the external world. For example, allowing AI to directly read Figma design drawings and write frontend, or directly operate databases. At the same time, learn to control the token budget, use expensive models for large tasks, use cheap models for small tasks, and timely compress long conversations to prevent bankruptcy. 6. The final step of professional deployment and monetization in the sixth month is to push the product to the market. The front-end is thrown to Vercel, and the back-end is connected to Supabase, with monitoring and tracking errors. Next, choose your money making path: either work as an independent hacker to develop vertical SaaS and sell subscriptions, or take the project to big companies to earn high salaries, or help traditional enterprises build automated workflows to earn consulting fees. Finally, let me reiterate that most people only click on "bookmark" after reading it, but those who can truly make a difference only do three things: do it without following the tutorial, publicly share their construction process, and have to create a live product with a real website every month. Action determines the upper limit, go pick a pain point and start working quickly.