This article shares how AI Coding accelerated development of a Mastodon web client, with a focus on prompt-driven engineering , complex interaction design , and high‑leverage refactors . It highlights prompt patterns, integration strategies, and two key features: React Query and the rich text editor . Preview : https://v0-mastodon-client.vercel.app Github : https://github.com/fh332393900/mastodon-client Model note: Most of the AI work used GPT‑5.2‑Codex . 1) Why AI Coding Here? The project evolved quickly: rich editor, federated search, emoji handling, code blocks, and multi‑language UI. AI was used as a co‑pilot for high‑impact changes , not just boilerplate. Key goals: Ship complex interactions fast Maintain correctness (state boundaries, serialization) Keep UI responsive 2) Prompting Patterns That Worked A) “Diagnose then propose” Prompt: “Explain the cause of input lag, then propose a fix with minimal changes.” Outcome: AI focused on render priorities and avoided rewriting the component blindly.…