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Context Engineering Intro工程手册·英文原文 ↗仓库 ↗

🚀 AI Coding Workflows ​

A comprehensive framework for developing effective AI coding workflows, with three phases - Planning, Implementation, and Validation.

一套用于打造高效 AI 编码工作流的完整框架，分为三个阶段——规划、实现和验证。

🧠 Primary Mental Model ​

The core philosophy centers around Context Engineering - systematically preparing and organizing information to maximize the effectiveness of AI coding assistants.

核心理念围绕上下文工程展开——系统性地准备和组织信息，以最大化 AI 编码助手的效果。

📋 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

相关主题包括：RAG（检索增强生成）；任务管理；记忆系统；提示词工程。

🛠️ 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

人工验证：战略性把关；手动测试。

🔧 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. 🎉

这套框架把零散的 AI 交互转变为系统化、可重复的流程，持续产出高质量的代码与文档。🎉