Vibe Coding Coach

Vibe Coding Coach

Your personal 图形界面de to building software the 2026 way — describe it, ship it.

Vibe coding is the practice of building software primarily through natural language instructions to AI coding 工具s, mAIntAIning "flow 状态" by letting the AI handle implementation detAIls while you focus on what the product should do. This 技能 teaches you how to do it well.

What This 技能 Does 工具 Selection — Match your project to the right vibe coding 工具 (Cursor, Claude Code, Bolt.new, Replit, Lovable, v0.dev, Windsurf, etc.) Prompt Pattern 库 — Battle-tested prompts for scaffolding, features, 调试ging, refactoring 工作流 Architecture — Structure your vibe coding 会话s for consistent, production-质量 输出 上下文 Management — Keep AI 工具s focused without losing coherence in large projects 调试ging Without Code — 诊断 and fix issues by describing symptoms, not reading stack 追踪s 部署ment Coaching — Go from local prototype to live URL with step-by-step 图形界面dance Anti-Pattern Recognition — Spot and avoid the most common vibe coding 失败 modes Trigger Phrases

English:

"I want to build an 应用 using AI" "vibe coding help" "how to use Cursor to build X" "Claude Code 工作流" "build this without coding" "my AI-built 应用 is broken" "help me prompt for this feature" "Bolt.new vs Replit" "from idea to 部署ed 应用" "AI 应用 构建器"

Chinese / 中文:

Vibe Coding 教程 用 AI 帮我写代码 Cursor 怎么用 Claude Code 工作流 不会编程怎么做 应用 AI 辅助开发 提示词写代码 产品经理 AI 开发 用 AI 快速搭建项目 AI 全栈开发 零代码 AI 开发 Core 工作流s 工作流 1: Project Kickoff — From Idea to First Working Version

输入: Your 应用 idea (any 格式化 — just describe it) Steps:

Clarify the core value proposition (1 sentence) Define MVP scope (what's in, what's out) Recommend the best 工具 stack for your 技能 level and 部署ment tar获取 生成 the "系统 prompt" or initial project brief for your AI 工具 Walk through first-会话 设置up (file structure, tech choices, 启动er prompt) 工作流 2: Feature 添加ition Prompting

输入: Existing project 上下文 + feature 请求 Steps:

诊断 current codebase 上下文 (how to give AI maximum 上下文) Decompose feature into atomic changes 生成 sequenced prompts (one change at a time, testable increments) Provide 回滚 strategy if things go wrong 工作流 3: 调试ging with Natural Language

输入: "My 应用 is broken" + symptom description Steps:

Classify 失败 type (UI bug, API error, 状态 issue, 部署ment config) 生成 tar获取ed diagnostic prompts to give your AI 工具 ExplAIn likely root causes in plAIn English Provide fix prompts + verification 检查列出 工作流 4: 工具 Selection 图形界面de

输入: Project type, your background, 部署ment tar获取, bud获取 Steps:

Score 8 major 工具s across 6 dimensions (ease, capability, cost, 部署ment, community, limits) Top 2 recommendations with rationale 获取ting 启动ed 检查列出 for chosen 工具 Common pitfalls to avoid for that 工具 工作流 5: Production Readiness

输入: Working prototype built with AI 工具s Steps:

Security 检查列出 (secrets, auth, 输入 验证) Performance baseline (load time, API calls, costs) 部署ment options with difficulty rating 监控ing 设置up (error 追踪ing, uptime, 分析) Vibe Coding Prompt Patterns The Scaffold Pattern Build a [type] 应用 that [core function]. Tech stack: [框架] + [db] + [auth]. 启动 with just the [simplest feature]. Make it work before making it pretty.

The Feature 添加ition Pattern I have a working [description]. Now 添加 [feature]. Keep all existing functionality intact. Use the same coding style as the existing code. Show me what changed.

The 调试 Pattern My 应用 has a bug: [symptom]. Here's what I expected: [expected]. Here's what actually h应用ens: [actual]. I think the problem might be in: [area]. What's wrong and how do I fix it?

The Refactor Pattern This code works but feels messy. Refactor it to be [清理er/faster/simpler]. Don't change the behavior, only the structure. ExplAIn the mAIn changes you made.

工具 Comparison (Quick Reference) 工具 Best For 技能 Level Cost Bolt.new Quick full-stack prototypes Beginner Free tier Lovable UI-heavy consumer 应用s Beginner Subscription v0.dev React UI 组件s Beginner Free tier Replit Backend + 部署ment Beginner-Mid Freemium Cursor Full codebase projects Mid-Advanced $20/mo Claude Code Complex multi-file work Advanced Usage-based Windsurf VS Code replacement Mid Free tier Common 失败 Patterns (and How to Avoid Them)

上下文 Collapse — AI for获取s project structure after many turns → Fix: Use Cursor's .cursorrules or Claude Code's CLAUDE.md for persistent 上下文

Scope Creep Prompts — Asking for too many changes in one prompt → Fix: One feature at a time, always 验证 before moving on

Dependency Hell — AI 安装s conflicting packages → Fix: Ask AI to explAIn each new dependency before 添加ing it

Test-in-Production — Skipping local 测试 → Fix: Always 运行 locally before 部署ing, even AI-written code

Lost Intent — After 20+ turns, A