# Bangstack: Requirements-to-Code Model

## The Vision

Bangstack enables **product owners** to build complex, custom applications by describing what they want in plain English, while **AI handles all technical implementation details**.

### Your Role: Product Owner
- Describe user journeys and features in plain English
- Give feedback on generated implementations
- Make product decisions
- Ensure the app works as expected

### AI's Role: Technical Implementer
- Translate requirements into technical specifications
- Maintain internal system architecture (YAML)
- Generate all implementation code
- Handle refactoring and updates
- Ensure automatic context propagation

## The Core Problem This Solves

**Problem**: Building complex applications requires:
1. Detailed technical specifications
2. Careful coordination between components
3. Manual updates when adding new features
4. Deep technical knowledge

**Solution**: Automatic context propagation through event-driven architecture:
- Add Klarna → all components that need to know about it automatically update
- Add wishlist → cart, analytics, database all become aware
- Change payment flow → email templates, confirmation pages update automatically

## How It Works

### The Three-Layer Architecture

```
Layer 1: Requirements (You maintain)
   ↓
Layer 2: Internal YAML (AI maintains)
   ↓
Layer 3: Implementation Code (AI generates)
```

### Layer 1: Requirements File (`requirements.md`)

You write what you want in plain English:

```markdown
# E-commerce Store Requirements

## User Journeys

### Customer Checkout Flow
1. Customer browses products
2. Customer adds items to cart
3. Customer selects payment (PayPal, Klarna, or Credit Card)
4. Customer completes purchase
5. Customer receives confirmation email

## Payment Requirements
- Support PayPal, Klarna, and Stripe
- Show clear error messages on failure

## Design Preferences
- React with TypeScript
- Tailwind CSS
- Primary color: Blue
```

**That's it.** No YAML, no schemas, no technical specs.

### Layer 2: Internal YAML (AI Maintains)

From your requirements, AI generates and maintains:

**`.bangstack/internal/workflows.yaml`**
```yaml
workflows:
  customer_checkout:
    actor: customer
    steps:
      - id: browse_catalog
        component: catalog
        emits: product_viewed
      - id: add_to_cart
        component: cart
        emits: product_added_to_cart
      # ... etc
```

**`.bangstack/internal/events.yaml`**
```yaml
events:
  product_added_to_cart:
    description: Customer added product to cart
    payload:
      product_id: string
      quantity: number
      price: number
```

**`.bangstack/internal/components.yaml`**
```yaml
components:
  cart:
    description: Shopping cart management
    emits:
      - product_added_to_cart
      - cart_viewed
    consumes:
      - product_viewed
```

**`.bangstack/internal/stack.yaml`**
```yaml
stack:
  checkout:
    services:
      stripe:
        type: payment_processor
        config:
          api_key: "{{ env.STRIPE_SECRET_KEY }}"
      paypal:
        type: payment_processor
      klarna:
        type: payment_processor
```

**You don't need to look at these files unless you want to.**

### Layer 3: Implementation Code (AI Generates)

From the internal YAML, AI generates:

```
src/
├── models/
│   ├── Product.ts
│   ├── Cart.ts
│   └── Order.ts
├── routes/
│   ├── products.ts
│   ├── cart.ts
│   └── checkout.ts
├── services/
│   ├── PaymentService.ts
│   └── EmailService.ts
├── integrations/
│   ├── StripePayment.ts
│   ├── PayPalPayment.ts
│   └── KlarnaPayment.ts
├── pages/
│   ├── HomePage.tsx
│   ├── CartPage.tsx
│   └── CheckoutPage.tsx
└── components/
    ├── ProductCard.tsx
    └── PaymentSelector.tsx

migrations/
├── 001_create_products.sql
├── 002_create_carts.sql
└── 003_create_orders.sql

tests/
├── checkout-flow.test.ts
└── payment-processing.test.ts

docs/
├── API.md
└── DEPLOYMENT.md
```

## The Development Workflow

### Initial Build

```bash
# 1. Write requirements
vim requirements.md

# 2. Analyze and clarify
bangstack analyze requirements.md
# AI asks questions, you answer

# 3. Generate everything
bang generate

# 4. Run the app
npm run dev
```

### Iterative Refinement

**Scenario 1: Small UI Change**

```bash
$ bang chat

You: The checkout button should be green
AI: ✓ Updated CheckoutPage.tsx
    Refresh to see changes.
```

**Scenario 2: Add New Feature**

```bash
You: Add wishlist functionality for logged-in users

AI: Adding wishlist feature...
    ✓ Updated internal specifications
    ✓ Generated 7 new files
    ✓ Updated 3 existing files

    Changes:
    - New database table: wishlists
    - New API: /api/wishlist
    - New page: /wishlist
    - Heart icon on product cards

    Run: npm run migrate && npm run dev
```

**Scenario 3: Modify Existing Flow**

```bash
You: Add a shipping address step before payment selection

AI: Updating checkout flow...

    ✓ Added shipping_address component
    ✓ Added collect_shipping_address step
    ✓ Updated checkout workflow order
    ✓ Generated ShippingAddressPage.tsx
    ✓ Updated cart → checkout transition
    ✓ Updated order creation to include shipping

    The checkout flow is now:
    1. Review cart
    2. Enter shipping address (NEW)
    3. Select payment method
    4. Complete order
```

## Automatic Context Propagation

This is the **magic** of Bangstack - when you change one thing, everything that needs to know automatically updates.

### Example: Adding Klarna Payment

**You say:**
```
Add Klarna as a payment option
```

**AI automatically updates:**

1. **Stack Configuration**
   ```yaml
   stack:
     checkout:
       services:
         klarna:  # NEW
           type: payment_processor
           config:
             api_key: "{{ env.KLARNA_API_KEY }}"
   ```

2. **Payment Component**
   ```yaml
   components:
     checkout:
       emits:
         - payment_method_selected  # Klarna added to choices
   ```

3. **Workflow Step**
   ```yaml
   steps:
     - id: select_payment
       choices:
         - paypal
         - stripe
         - klarna  # NEW
   ```

4. **Generated Code**
   - `src/integrations/KlarnaPayment.ts` - NEW FILE
   - `src/components/PaymentSelector.tsx` - UPDATED (adds Klarna button)
   - `src/services/PaymentService.ts` - UPDATED (handles Klarna)
   - `.env.example` - UPDATED (adds KLARNA_API_KEY)
   - `docs/PAYMENT_SETUP.md` - UPDATED (Klarna setup instructions)
   - `tests/payment-processing.test.ts` - UPDATED (Klarna test cases)

**All of this happens automatically** because:
- The event-driven architecture knows which components care about payments
- The YAML tracks component dependencies
- The code generator follows the architecture

### Example: Adding Product Reviews

**You say:**
```
Customers should be able to leave reviews on products they've purchased
```

**AI automatically:**

1. **Adds new events**
   ```yaml
   events:
     review_submitted:
       payload:
         product_id: string
         order_id: string
         rating: number
         comment: string
   ```

2. **Creates review component**
   ```yaml
   components:
     reviews:
       emits:
         - review_submitted
       consumes:
         - order_created  # Can only review purchased products
   ```

3. **Updates related components**
   ```yaml
   components:
     catalog:
       consumes:
         - review_submitted  # Show reviews on product pages

     analytics:
       consumes:
         - review_submitted  # Track review engagement

     email_system:
       consumes:
         - review_submitted  # Send thank-you email
   ```

4. **Generates implementation**
   - New database table: `reviews`
   - New API endpoints: `POST /api/products/:id/reviews`, `GET /api/products/:id/reviews`
   - New component: `ReviewForm.tsx`, `ReviewList.tsx`
   - Updates `ProductDetailPage.tsx` to show reviews
   - Adds email template for review submission
   - Creates tests for review submission

**You didn't have to specify any of this** - the AI inferred:
- Reviews need to be stored (database)
- Reviews should appear on product pages (catalog update)
- Only purchasers can review (consumes order_created)
- Analytics should track reviews (automatic event consumption)

## The Conversation Model

The key to Bangstack is that it's a **conversation**, not a one-time specification.

### Typical Conversation Flow

```
You: I want to build an online store

AI: Great! Let me ask a few questions:
    - What products will you sell?
    - How should customers pay?
    - Do customers need accounts or can they checkout as guests?

You: Selling books. PayPal and credit card. Allow guest checkout.

AI: Perfect. I'll create:
    - Product catalog for books
    - Shopping cart
    - Guest and registered checkout
    - PayPal and Stripe integration
    - Order management

    Generating... [creates everything]

    Review the app and let me know what needs adjusting.

You: [Reviews app]
    The product cards should show the author name

AI: ✓ Updated ProductCard component to show author
    ✓ Added author field to products table
    ✓ Updated product API to include author

You: Can customers filter by genre?

AI: Adding genre filtering...
    ✓ Added genre field to products
    ✓ Created GenreFilter component
    ✓ Added genre filter to catalog API
    ✓ Updated HomePage with genre sidebar

You: Perfect. Now I want customers to be able to create wishlists.

AI: [Adds wishlist feature as shown in previous examples]

You: Great! Now I want to send customers an email if items in their
     wishlist go on sale.

AI: Adding sale notifications for wishlist items...
    ✓ Created price_changed event
    ✓ Added price tracking to products
    ✓ Created wishlist_notification component
    ✓ Added email template for sale notifications
    ✓ Created background job to check prices daily

    New workflow: price_monitoring (system actor)
    - Runs daily at 9am
    - Checks for price decreases
    - Emails customers with wishlist items on sale
```

**This is how development happens** - iterative, conversational, collaborative.

## What Makes This Possible

### 1. Event-Driven Architecture

Components communicate through events, not direct references:

```yaml
# Cart doesn't "know about" checkout directly
# It just emits events that checkout consumes

cart:
  emits:
    - cart_viewed

checkout:
  consumes:
    - cart_viewed  # Automatically receives cart events
```

When you add a new consumer (e.g., analytics wants to track cart views), you just declare it:

```yaml
analytics:
  consumes:
    - cart_viewed  # Automatically starts receiving cart events
```

**No manual wiring required.**

### 2. Declarative Component Relationships

Components declare what events they produce and consume:

```yaml
components:
  checkout:
    emits: [payment_selected, order_created]
    consumes: [cart_viewed, product_added_to_cart]
```

This means:
- **Adding a new event** - all interested components automatically subscribe
- **Removing an event** - validation warns which components will be affected
- **Refactoring** - the schema tracks all dependencies

### 3. Strict Validation

The schema enforces referential integrity:
- Can't emit undefined events
- Can't consume events that don't exist
- Can't reference undefined components
- Must complete event flow (emitted → consumed)

This means **the YAML perfectly describes system connections**.

### 4. Layered Abstraction

Each layer builds on the previous:

```
Requirements → Events → Components → Workflows → Stack → Code
```

Changes at any layer propagate correctly because relationships are explicit.

## Commands You'll Use

### Daily Commands

```bash
# Make changes via chat
bangstack chat

# See what changed
bangstack diff

# Regenerate after changes
bang generate

# Run tests
bangstack test
```

### Occasional Commands

```bash
# Analyze new/updated requirements
bangstack analyze requirements.md

# Validate system design
bangstack validate

# See system overview
bangstack overview

# Export documentation
bangstack docs export

# Deploy to production
bangstack deploy production
```

## What You Never Have to Do

With Bangstack, you **never** have to:

1. **Write boilerplate code** - all CRUD operations, API endpoints, database models generated
2. **Manually wire components** - event system handles connections
3. **Update documentation** - auto-generated from YAML
4. **Write integration code** - payment processors, email services auto-configured
5. **Maintain YAML specifications** - AI handles all technical specs
6. **Track dependencies** - schema validation ensures consistency
7. **Refactor manually** - changes propagate automatically

## What You Always Control

You **always** control:

1. **What features exist** - describe in requirements
2. **How things should work** - specify in plain English
3. **Design decisions** - colors, layouts, UX flows
4. **Business logic** - approval workflows, pricing rules, etc.
5. **Final say** - review and approve all changes

## Example: Building a SaaS Application

Let's walk through building a complete SaaS app.

### Initial Requirements

```markdown
# Project Management SaaS

## Overview
A project management tool where teams can create projects, add tasks,
assign them to team members, and track progress.

## User Roles
- Admin: Manages users and billing
- Project Manager: Creates projects, assigns tasks
- Team Member: Completes assigned tasks

## Core Features
- Create projects
- Add tasks to projects
- Assign tasks to team members
- Track task status (todo, in progress, done)
- Dashboard showing my tasks

## Billing
- Free tier: 1 project, 3 team members
- Pro tier: Unlimited projects, unlimited team members
- Charge monthly via Stripe
```

### AI Analysis and Generation

```bash
$ bang analyze requirements.md

Analyzing requirements...

✓ Identified 3 actors:
  - admin (human)
  - project_manager (human)
  - team_member (human)

✓ Identified 5 components:
  - projects
  - tasks
  - team
  - billing
  - dashboard

✓ Identified 8 events:
  - project_created
  - task_created
  - task_assigned
  - task_status_changed
  - user_invited
  - subscription_upgraded
  - payment_processed
  - tier_limit_exceeded

Questions:
1. Should team members be able to create their own projects?
2. Can tasks have subtasks?
3. What happens when free tier limits are exceeded?
4. Should there be email notifications for task assignments?

$ bang refine
> 1. No, only project managers
> 2. Not initially, keep it simple
> 3. Show upgrade prompt
> 4. Yes, notify via email

$ bang generate

Generating complete SaaS application...

📁 Database (PostgreSQL)
  ✓ migrations/001_create_users.sql
  ✓ migrations/002_create_projects.sql
  ✓ migrations/003_create_tasks.sql
  ✓ migrations/004_create_subscriptions.sql

📁 Backend (Node.js + Express)
  ✓ Authentication with JWT
  ✓ Role-based authorization
  ✓ API endpoints (32 total)
  ✓ Stripe integration for billing
  ✓ Tier limits enforcement

📁 Frontend (React + TypeScript)
  ✓ Login/signup pages
  ✓ Dashboard (filtered by role)
  ✓ Project management UI
  ✓ Task board (Kanban style)
  ✓ Team management
  ✓ Billing/subscription page
  ✓ Upgrade prompts

📁 Background Jobs
  ✓ Send task assignment emails
  ✓ Process recurring billing
  ✓ Check tier limits

📁 Tests
  ✓ Unit tests for all endpoints
  ✓ Integration tests for workflows
  ✓ E2E tests for critical paths

Generated 87 files

Setup instructions:
  1. Configure environment (.env.example → .env)
  2. Run migrations: npm run migrate
  3. Seed sample data: npm run seed
  4. Start dev server: npm run dev

Your SaaS is ready!
```

### Iterative Development

```bash
$ bang chat

You: Add time tracking - team members should be able to log hours on tasks

AI: Adding time tracking feature...

    ✓ Created time_entry component
    ✓ Added events: time_logged, time_updated
    ✓ Updated tasks component to consume time events
    ✓ Updated billing to track billable hours (pro feature)
    ✓ Generated TimeEntryForm component
    ✓ Added time tracking to task details page
    ✓ Created time reporting dashboard for project managers
    ✓ Added database table for time_entries

    Generated 8 files, updated 5 files

You: Can project managers see a report of total hours by team member?

AI: Creating team member hours report...

    ✓ Added reports component
    ✓ Created TeamHoursReport page
    ✓ Added API: GET /api/reports/hours-by-member
    ✓ Added chart visualization (using recharts)
    ✓ Added export to CSV functionality

    Report shows:
    - Hours per team member
    - Breakdown by project
    - Filterable by date range

You: Perfect! Now add comments on tasks.

AI: [Adds commenting system with automatic notifications]

You: And file attachments to tasks.

AI: [Adds file upload, cloud storage integration, file events]
```

Each feature addition:
- Updates the internal YAML
- Generates new code
- Updates related components
- Maintains system integrity
- All happens automatically

## The Implementation Plan

To build this system, we need to create:

### Phase 1: Requirements Analysis Engine
- Natural language parser for requirements.md
- Question generation for ambiguous requirements
- Requirements → Events/Components mapping
- Interactive refinement CLI

### Phase 2: YAML Generation Layer
- Generate workflows.yaml from user journeys
- Generate events.yaml from actions and triggers
- Generate components.yaml from system responsibilities
- Generate stack.yaml from tech preferences
- Validate referential integrity

### Phase 3: Code Generator
- Template system for code generation
- Event-driven architecture implementation
- Service integration generation (Stripe, SendGrid, etc.)
- Database schema from components
- Frontend from workflows
- Tests from requirements

### Phase 4: Feedback Loop
- Conversation-based refinement (CLI chat)
- Diff visualization
- Incremental regeneration
- Rollback capability

### Phase 5: Deployment & Operations
- Environment management
- Deployment automation
- Monitoring and logging setup
- Documentation generation

## Next Steps

To implement this model for Bangstack:

1. **Build the requirements analyzer** - parse requirements.md and extract structure
2. **Implement YAML generator** - create internal specs from requirements
3. **Create code generation templates** - for each component type
4. **Build the chat interface** - for conversational refinement
5. **Integrate with existing commit system** - version control for changes

## Summary

**Bangstack transforms application development from**:
- Writing detailed technical specs → Describing what you want
- Manual component wiring → Automatic context propagation
- Maintaining complex codebases → Maintaining simple requirements
- Technical implementation → Product ownership

**You write in plain English, AI handles the rest.**

The YAML exists as an internal representation that ensures:
- Automatic awareness between components
- Consistent architecture
- Complete system description
- Correct code generation

But **you never have to look at it** unless you want to understand the technical architecture.

This is Bangstack's true purpose: **Enable anyone to build complex applications by describing requirements, not writing code.**
