Planning for AI: The Blueprint

“In Vibe Coding, documentation isn’t just a record of what you built. It is the source code for the AI that builds it.”

This guide integrates advanced prompting techniques, critical gaps, and tool-specific workflows into a complete blueprint for AI-assisted development.

The Core Insight: Docs Are Your Source Code

In Vibe Coding, the relationship between code and documentation is inverted.

1. The Planning Loop

The process follows a strict cycle to minimize hallucinations and rework.

1. Plan: Define what to build (PRD, User Stories).
2. Discuss: Validate with AI before coding.
3. Implement: AI generates code from the context.
4. Verify: Tests and reviews confirm intent.

2. The Golden PRD Template

This is a Project Requirements Document optimized for Large Language Models. Code blocks are ready to copy-paste.

Copy-Paste Template

# [Project Name] - Product Requirements Document
 
## Role
You are a senior [React/Python] engineer building a production application.
You write clean, maintainable code with proper error handling and strict types.
 
## Objective
[One clear sentence. What does this do?]
*Example: "Build a budgeting dashboard that visualizes monthly spending by category and allows users to track transactions."*
 
## Tech Stack (Strict Constraints)
- **Frontend:** [React 18, TypeScript, Tailwind CSS]
- **Backend:** [Supabase, PostgreSQL]
- **State Management:** [Zustand]
- **Auth:** [Supabase Auth]
- **Testing:** [Vitest, React Testing Library]
 
⚠️ CRITICAL: Do NOT suggest alternatives. Use exactly these technologies.
 
## User Stories
### Primary Flow
1. As a [user], I want to [action] so that [outcome].
2. As a [user], I want to [action] so that [outcome].
 
### Secondary Flows
1. As a [user], I want to [action] so that [outcome].
 
## Data Model
\`\`\`typescript
interface User {
  id: string;
  email: string;
  created_at: Date;
}
 
interface Transaction {
  id: string;
  user_id: string;
  amount: number;
  category: string;
  date: Date;
}
\`\`\`
 
## UI Requirements
### Pages
1. **Dashboard (/dashboard)**
   - Monthly spending chart
   - Recent transactions list (last 10)
   - Quick-add button
2. **Transactions (/transactions)**
   - Filterable table (search, category, date)
   - Bulk delete capability
3. **Settings (/settings)**
   - Edit profile
   - Export data as CSV
 
## Non-Functional Requirements
- **Mobile-responsive:** Breakpoints: 640px, 768px, 1024px.
- **Performance:** Lighthouse >90, LCP <2.5s.
- **Accessibility:** WCAG 2.1 AA (Contrast, Keyboard nav).
 
## Success Criteria
- [ ] User can add transaction in < 10s.
- [ ] Dashboard loads in < 2s.
- [ ] Zero console errors.
- [ ] TypeScript strict mode: zero `any` types.

3. Essential Strategies (Often Missed)

Validating these areas upfront saves hours of debugging later.

Error Handling Strategy

Don’t just say “handle errors.” Define the behavior.

• API Errors: 401 → Redirect to login. 500 → Show support contact.
• UI Errors: Form validation → Inline red text. Data fetch fail → Retry button.
• Messages: “Email already registered. Try logging in.” (Not “Error 409”).

State Management

• Global (Zustand): User auth, Theme.
• Server (React Query): Transactions (cache 5 mins), Profile (cache 10 mins).
• Local (useState): Form inputs, Modal open/close.

Testing Requirements

• Unit (Vitest): Utilities, Hooks.
• Integration (RTL): Form submissions, critical flows.
• E2E (Playwright): Happy path user journey.

4. Advanced Prompting Techniques (2025)

These research-backed techniques separate working code from hallucinations.

1. Decomposition

Break big problems into steps.

✅ Good: “Let’s build step-by-step: 1. Schema. 2. API. 3. UI. Confirm step 1 before moving to step 2.”

2. Constraint Anchoring

Negative constraints prevent weird library choices.

✅ Good: “Do NOT use external CSS libraries. Use ONLY Tailwind utility classes. Do NOT use inline styles.”

3. Self-Criticism & Reflection

Force the AI to audit itself.

✅ Good: “Before finalizing, check for: 1. Accessibility issues. 2. TypeScript safety. 3. Performance bottlenecks.”

4. Few-Shot Learning

Show, don’t just tell.

✅ Good: “Format errors exactly like this example: { type: 'error', code: 'INVALID_EMAIL' }”

5. Role Specification

Be specific about the “Persona”.

✅ Good: “Act as a code reviewer. Criteria: 1. Strict Typing. 2. Error Handling. 3. Accessibility.”

5. The Context File (.cursorrules)

Stop repeating yourself. Every AI IDE supports a persistent context file.

• Cursor: .cursorrules
• Windsurf: .windsurfrules
• Generic: .PROJECT_CONTEXT.md

Template for Context File

# Project Context
 
## Tech Stack
- Frontend: React 18 + TypeScript + Tailwind CSS
- Backend: Supabase (Postgres + Auth)
- Query: React Query v5
- State: Zustand
 
## Strict Rules
1. NEVER use `any` type - use `unknown` if truly unknown.
2. ALWAYS handle loading and error states.
3. ALWAYS use environment variables for secrets (`process.env.NEXT_PUBLIC_...`).
4. NEVER commit `.env.local`.
5. ALWAYS use `cn()` for conditional classNames.
 
## Common Patterns
- **Fetching:** Use `useQuery` with `staleTime`.
- **Forms:** Use `react-hook-form` + `zod`.

6. Tools for AI-Optimized Planning

Use tools that “speak” the language of AI (Markdown, JSON, Code).

7. Planning Checklist

Before you start coding, do you have:

• Objective: One clear sentence?
• Tech Stack: Explicit constraints (No “modern tools”, list specific libraries)?
• Data Model: TypeScript interfaces or SQL schema?
• User Stories: Primary flows defined?
• Visuals: Wireframe directly (Excalidraw) or Mermaid diagram?
• Discuss Phase: Did you ask the AI to critique your plan first?

8. Common Mistakes

The Philosophy

Planning IS the product. 30 minutes of planning saves 2+ hours of debugging. Explicit constraints = fewer hallucinations. Data models upfront = no structural surprises.

Your AI agent is only as good as the information you give it.