The latest articles on DEV Community by Claudio Felicioli (@pangon). https://dev.to/pangon https://media2.dev.to/dynamic/image/width=90,height=90,fit=cover,gravity=auto,format=auto/https:%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Fuser%2Fprofile_image%2F3827355%2F1c9bae55-7428-45b7-a36f-4ca02e9031c8.jpg https://dev.to/pangon en Claudio Felicioli Mon, 16 Mar 2026 13:16:10 +0000 https://dev.to/pangon/i-built-an-ai-sdlc-scaffold-f5g https://dev.to/pangon/i-built-an-ai-sdlc-scaffold-f5g <p>GitHub: <a href="https://github.com/pangon/ai-sdlc-scaffold" rel="noopener noreferrer">https://github.com/pangon/ai-sdlc-scaffold</a></p> <p>I built an open-source repository template for AI-first software development, designed primarily around Claude Code, focused on the pre-coding phases (objectives elicitation, user stories, requirements definition, and design) that developers tend to cut short under tight time constraints. AI agents can help a lot in these phases too, not just in writing code.</p> <p>Core principles:</p> <ol> <li><p>Everything-in-repo: objectives, user stories, requirements, architecture, decisions, and task tracking all live alongside the source code.</p></li> <li><p>Context-window efficiency: instructions and project knowledge are organized hierarchically so the agent can load only what is needed. Artifact collections are indexed via markdown tables.</p></li> <li><p>Decision capture: decisions made during AI reasoning are captured and persisted as structured artifacts in the repo, so they remain reviewable, traceable, and consistently applied across sessions.</p></li> </ol> <p>I have been using this approach for my personal projects for a while and decided to package it up in a way that might be useful to the community.</p> <p>Licensed under Apache 2.0 — fork it, adapt it, build on it.</p> <p>Feedback, criticism, and contributions are very welcome. I'd love to hear what works, what doesn't, and what you'd change.</p> automation softwareengineering ai