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How I Built an AI Idea Library Using No-Code and Vibe-Code

As a software builder, I’m often stuck on one question: What should I build? The problem isn’t a lack of ideas — it’s the worry no one will need them after I build. I wanted a library of buildable AI product ideas pulled from real user need…

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As a software builder, I’m often stuck on one question: What should I build? The problem isn’t a lack of ideas — it’s the worry no one will need them after I build. I wanted a library of buildable AI product ideas pulled from real user needs, so I created solopreneur.global — for myself and anyone facing the same dilemma.



My Build Playbook: Steps & Tools

I split the work into two parts and spent about 2 weeks in total.



1. n8n workflow to analyze community conversations

The workflow ingests Reddit threads about user pain points related to AI products, filters for strong signals and high engagement, then uses AI to draft complete “idea cards”: original post summary, problem statement, solution outline, core features, business model, and go-to-market notes. The workflow runs automatically each day, so the idea library expands continuously.



2. A web app vibe-coded on top of a Next.js boilerplate

I first stored identified ideas in a spreadsheet, but it didn’t scale as the volume increased. So, I decided to vibe-code a minimal web app to display, categorize, and continuously publish the growing library.



Unlike a vibe-coding project built from scratch, we started with a Next.js boilerplate as the foundation. On one hand, it already includes common services—user management, payments, blogging, and analytics—so we just plug in the keys and do a quick test pass. On the other, the boilerplate provides a solid software architecture (clear layering, multilingual routing, and robust support for desktop and mobile, etc.), which lets the AI follow that structure when adding new features, preserving consistency and maintainability.



For this build I used Claude Code. My preferred workflow is: use Plan Mode to have the AI produce an overall design and implementation plan; once I review and approve it, let the AI implement the entire module end-to-end. The process is highly efficient with almost no rework.



If you’re curious about Claude Code but haven’t tried it yet, I recommend the official video tutorial: Claude Code: A Highly Agentic Coding Assistant.



Happy to share more in details, just let me know.

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