# 🚀 AI Coding Workflows A comprehensive framework for developing effective AI coding workflows, with three phases - **Planning**, **Implementation**, and **Validation**. ## 🧠 Primary Mental Model The core philosophy centers around **Context Engineering** - systematically preparing and organizing information to maximize the effectiveness of AI coding assistants. ## 📋 Phase 1: Planning ### 1. 🎨 Vibe Planning Use the `/primer` slash command to kickstart your exploration: - **New projects**: Research online resources, similar projects, explore architecture and tech stack options - **Existing projects**: Analyze and understand the current codebase using the **Codebase Analyst** sub-agent - Focus: Unstructured exploration of ideas, concepts, and possibilities ### 2. 📝 Create INITIAL.md (PRD) Generate a detailed Product Requirements Document: - **New projects**: High-level MVP with supporting documentation references - **Existing projects**: Focused, detailed requirements with integration points ### 3. ⚙️ Context Engineering Components Prepare these essential elements using slash commands: - **RAG** (Retrieval-Augmented Generation) - **Task Management** - **Memory Systems** - **Prompt Engineering** #### 🛠️ Supporting Tools: - Archon - PRP Framework - Web Search - GitHub Spec Kit ### 📊 Plan of Attack Use the `/create-plan` slash command to generate a structured implementation strategy based on your INITIAL.md and context engineering setup. ## ⚡ Phase 2: Implementation ### 🎯 Execute Task by Task - Use the `/execute-plan` slash command to systematically work through your plan of attack - Follow the structured plan created during planning - Leverage the context engineering foundation ### 🔍 Trust but Verify Monitor the AI assistant to ensure it: - Uses MCP servers correctly - Reads/edits appropriate files - Leverages task management properly - Produces clear "thinking" tokens showing understanding ## ✅ Phase 3: Validation ### 📊 Code Review Process **AI Assistant Validation**: - Performs automated code review using the **Validator** sub-agent - Runs unit tests - Runs integration tests **Human Validation**: - Strategic oversight - Manual testing ## 🔧 Key Components ### 🌐 Global Rules - Subagents coordination (**Codebase Analyst** & **Validator**) - Slash commands integration (`/primer`, `/create-plan`, `/execute-plan`) - Consistent workflows across phases ### 🎯 Slash Commands Reference - **`/primer`**: Initialize vibe planning phase with exploration prompts - **`/create-plan`**: Generate structured plan of attack from PRD - **`/execute-plan`**: Systematically implement the created plan ### 🤖 Sub-Agents - **Codebase Analyst**: Specializes in understanding and analyzing existing codebases - **Validator**: Focuses on systematic code review and quality assurance ### 🏆 Success Factors - **Structured approach**: Each phase builds on the previous - **Context preparation**: Thorough setup enables better AI performance - **Iterative refinement**: Trust but verify at each step - **Tool integration**: Leverage specialized tools for specific tasks This framework transforms ad-hoc AI interactions into a systematic, repeatable process that consistently produces high-quality code and documentation. 🎉