The post explains a workflow for building applications with AI assistance: start by giving the idea to an LLM and first ask for a plainâEnglish requirements document; then generate code in iterative steps that can be reset or reverted back into a new requirements draft if needed, allowing you to keep progress while debugging. It highlights the benefit of modular plugin architectureâeach plugin lives in its own file, has descriptive metadata (name, type, description), and exposes a simple init function that receives the application object so it can hook into events, UI, and other helpers; this structure keeps context size manageable for the AI and lets you add or drop plugins without breaking the core app. The post then assigns homework: design a dragâandâdrop visual programming language using functional reactive operators (e.g., Rx.js) in vanilla JS, embed it in a modal search box with Bootstrap CDN, and progressively let the AI move the code into the visual environment until the language is selfâcontainedâan exercise meant to demonstrate how AI can help build complex, extensible systems.






















