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AI Knowledge Workspace - Detailed Project Roadmap

Overview

This roadmap provides a comprehensive, step-by-step plan for building a production-grade AI-powered knowledge workspace with document ingestion, semantic search, and LLM-powered chat capabilities.

Phase 1: Project Foundation & Setup

1.1 Initialize Next.js Project

  • Create Next.js 14 project with TypeScript
    • Command: npx create-next-app@latest . --typescript --tailwind --app --no-src-dir
    • Configure: App Router, TypeScript strict mode
  • Install core dependencies
    • React 18, Next.js 14
    • TypeScript, ESLint, Prettier
  • Set up project structure 
    /app
  /(auth)
  /(dashboard)
  /api
/components
  /ui (shadcn components)
/lib
/types
/hooks
/utils

1.2 Configure TailwindCSS & shadcn/ui

  • Install and configure TailwindCSS
  • Initialize shadcn/ui
    • Command: npx shadcn-ui@latest init
    • Configure: TypeScript, TailwindCSS, App Router
  • Install base shadcn components
    • Button, Input, Card, Dialog, Sheet, Tabs, Avatar, Badge, Progress, ScrollArea, Separator, Skeleton, Toast (Sonner)
  • Set up theme configuration (light/dark mode)
  • Create layout components (Header, Sidebar, Footer)

1.3 Environment Configuration

  • Create .env.local template
    • Next.js variables
    • Supabase credentials
    • API keys (OpenAI, Anthropic, Groq, VoyageAI)
  • Set up .env.example with placeholder values
  • Configure environment variable validation with Zod

1.4 Git & Version Control

  • Initialize git repository (if not exists)
  • Create .gitignore (Next.js, node_modules, .env.local)
  • Set up initial commit structure
  • Create development branch strategy

Phase 2: Supabase Setup & Database Schema

2.1 Supabase Project Setup

  • Create Supabase project
  • Get project URL and anon key
  • Install Supabase client libraries
    • @supabase/supabase-js
    • @supabase/ssr (for Next.js)
  • Configure Supabase client utilities
    • Create /lib/supabase/client.ts (browser client)
    • Create /lib/supabase/server.ts (server client)
    • Create /lib/supabase/middleware.ts (middleware client)

2.2 Enable PostgreSQL Extensions

  • Enable pgvector extension in Supabase SQL editor 
    CREATE EXTENSION IF NOT EXISTS vector;
  • Verify extension installation

2.3 Database Schema Design

2.3.1 Users Table (extends Supabase auth.users)

  • Create profiles table 
    CREATE TABLE profiles (
  id UUID PRIMARY KEY REFERENCES auth.users(id),
  email TEXT,
  full_name TEXT,
  avatar_url TEXT,
  created_at TIMESTAMPTZ DEFAULT NOW(),
  updated_at TIMESTAMPTZ DEFAULT NOW()
);
  • Set up Row Level Security (RLS) policies
  • Create trigger for automatic profile creation on signup

2.3.2 Documents Table

  • Create documents table 
    CREATE TABLE documents (
  id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
  user_id UUID REFERENCES auth.users(id) ON DELETE CASCADE,
  title TEXT NOT NULL,
  file_name TEXT,
  file_type TEXT,
  file_size BIGINT,
  storage_path TEXT,
  status TEXT DEFAULT 'pending', -- pending, processing, completed, failed
  metadata JSONB,
  created_at TIMESTAMPTZ DEFAULT NOW(),
  updated_at TIMESTAMPTZ DEFAULT NOW()
);
  • Add RLS policies (users can only access their own documents)
  • Create indexes on user_id, status
  • Create index on created_at (not yet implemented)

2.3.3 Document Chunks Table (with Vector)

  • Create document_chunks table 
    CREATE TABLE document_chunks (
  id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
  document_id UUID REFERENCES documents(id) ON DELETE CASCADE,
  user_id UUID REFERENCES auth.users(id) ON DELETE CASCADE,
  chunk_index INTEGER NOT NULL,
  content TEXT NOT NULL,
  content_tokens INTEGER,
  embedding vector(1536), -- Adjust based on embedding model
  metadata JSONB,
  created_at TIMESTAMPTZ DEFAULT NOW()
);
  • Add RLS policies
  • Create vector index for similarity search 
    CREATE INDEX ON document_chunks USING ivfflat (embedding vector_cosine_ops)
WITH (lists = 100);
  • Create indexes on document_id, user_id
  • Create index on chunk_index (not yet implemented)

2.3.4 Conversations Table

  • Create conversations table 
    CREATE TABLE conversations (
  id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
  user_id UUID REFERENCES auth.users(id) ON DELETE CASCADE,
  title TEXT,
  model_provider TEXT, -- openai, anthropic, groq
  model_name TEXT,
  system_prompt TEXT,
  temperature DECIMAL(3,2) DEFAULT 0.7,
  use_memory BOOLEAN DEFAULT true,
  created_at TIMESTAMPTZ DEFAULT NOW(),
  updated_at TIMESTAMPTZ DEFAULT NOW()
);
  • Add RLS policies
  • Create indexes on user_id, created_at

2.3.5 Messages Table

  • Create messages table 
    CREATE TABLE messages (
  id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
  conversation_id UUID REFERENCES conversations(id) ON DELETE CASCADE,
  user_id UUID REFERENCES auth.users(id) ON DELETE CASCADE,
  role TEXT NOT NULL, -- user, assistant, system
  content TEXT NOT NULL,
  tokens_used INTEGER,
  model_used TEXT,
  latency_ms INTEGER,
  retrieved_chunk_ids UUID[],
  metadata JSONB,
  created_at TIMESTAMPTZ DEFAULT NOW()
);
  • Add RLS policies
  • Create indexes on conversation_id, user_id, created_at

2.3.6 Evaluation Logs Table

  • Create eval_logs table 
    CREATE TABLE eval_logs (
  id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
  user_id UUID REFERENCES auth.users(id) ON DELETE CASCADE,
  conversation_id UUID REFERENCES conversations(id) ON DELETE CASCADE,
  message_id UUID REFERENCES messages(id) ON DELETE CASCADE,
  request_data JSONB,
  response_data JSONB,
  tokens_input INTEGER,
  tokens_output INTEGER,
  provider TEXT,
  model TEXT,
  latency_ms INTEGER,
  error TEXT,
  created_at TIMESTAMPTZ DEFAULT NOW()
);
  • Add RLS policies
  • Create indexes on user_id, created_at
  • Create index on provider (not yet implemented)

2.4 Supabase Storage Setup

  • Create storage bucket: documents
  • Configure bucket policies (authenticated users can upload/read their own files)
  • Set up storage RLS policies
  • Configure file size limits and allowed types

2.5 Database Functions & Triggers

  • Create function to update updated_at timestamp
  • Create trigger for documents.updated_at
  • Create trigger for conversations.updated_at
  • Create function to count chunks per document (chunk_count column exists but no function)
  • Create function to get conversation token usage

2.6 Drizzle ORM Setup (Optional but Recommended)

  • Install Drizzle ORM: npm install drizzle-orm drizzle-kit @supabase/supabase-js
  • Create /lib/db/schema.ts with all table definitions
  • Create /lib/db/index.ts for database client
  • Set up Drizzle migrations
  • Generate initial migration from schema

Phase 3: Authentication Implementation

3.1 Supabase Auth Configuration

  • Configure Supabase Auth settings (email/password enabled)
    • Enable email/password
    • Enable magic link (UI implemented, see auth-form.tsx)
    • Configure OAuth providers (Google, GitHub) if needed
    • Set up email templates
  • Configure redirect URLs for auth callbacks (implemented in auth-form.tsx)

3.2 Auth UI Components

  • Create /app/(auth)/login/page.tsx
    • Email/password form
    • Magic link option (implemented in auth-form.tsx)
    • OAuth buttons (if enabled)
    • Error handling
  • Create /app/(auth)/signup/page.tsx
    • Registration form
    • Terms acceptance
    • Email verification notice
  • Create /app/(auth)/callback/route.ts for auth callback handling
  • Create /app/(auth)/logout/route.ts for logout

3.3 Auth Middleware & Protection

  • Create /middleware.ts for route protection
    • Protect dashboard routes
    • Redirect unauthenticated users to login
    • Handle auth token refresh
  • Create /lib/auth/get-user.ts utility
  • Create /lib/auth/require-auth.ts utility for server components

3.4 User Profile Management

  • Create /app/(dashboard)/settings/profile/page.tsx
    • Display user info
    • Update profile form
    • Avatar upload
  • Create API route: /api/user/profile/route.ts
    • GET: Fetch user profile
    • PATCH: Update user profile

Phase 4: Document Upload & Storage

4.1 File Upload UI

  • Create /components/documents/upload-zone.tsx
    • Drag-and-drop area
    • File input
    • File type validation (PDF, TXT)
    • File size validation
    • Multiple file support
    • Upload progress indicator
  • Create /components/documents/upload-button.tsx
  • Integrate with shadcn Dialog/Sheet for upload modal

4.2 Upload Server Action

  • Create /app/actions/documents/upload.ts
    • Validate file type and size
    • Generate unique file name
    • Upload to Supabase Storage
    • Create document record in database
    • Return document ID
  • Add error handling and validation

4.3 URL Ingestion

  • Create URL input component (integrated into /components/documents/upload-document-button.tsx)
    • URL input form
    • URL validation
  • Create /app/actions/documents/ingest-url.ts (implemented as ingestUrl function in upload.ts)
    • Fetch URL content
    • Extract text (using cheerio - see lib/ingestion/url-ingestion.ts)
    • Create document record
    • Trigger ingestion pipeline

4.4 Document List Component

  • Create /components/documents/document-list.tsx
    • Display documents in table/card view
    • Show: name, size, upload date, status
    • Status badges (pending, processing, completed, failed)
  • Create /components/documents/document-card.tsx
  • Add pagination
  • Add filtering by status
  • Add sorting options

4.5 Document Management Actions

  • Create /app/actions/documents/delete.ts
    • Delete from storage
    • Delete from database (cascade to chunks)
  • Create /app/actions/documents/reindex.ts
    • Reset document status
    • Trigger re-ingestion
  • Add confirmation dialogs for destructive actions

Phase 5: Document Ingestion Pipeline

5.1 PDF Parsing

  • Install PDF parsing library
    • Option A: pdf-parse
    • Option B: pdfjs-dist (PDF.js)
    • Option C: llama-parse (if available)
  • Create /lib/ingestion/pdf-parser.ts
    • Extract text from PDF
    • Handle multi-page documents
    • Extract metadata (title, author, pages)
    • Error handling for corrupted PDFs

5.2 Text Processing

  • Create /lib/ingestion/text-processor.ts (text processing is integrated into chunker.ts and pipeline.ts)
    • Normalize whitespace (handled in pipeline)
    • Remove special characters (optional)
    • Split into paragraphs (handled in chunker)
    • Calculate token counts (handled in chunker with tiktoken)

5.3 Chunking Strategy

  • Create /lib/ingestion/chunker.ts
    • Implement recursive chunking
    • Configurable chunk size (tokens/characters)
    • Overlap between chunks
    • Preserve sentence boundaries
    • Handle markdown/structured text
  • Create chunking utilities
    • Token counting (tiktoken or similar)
    • Text splitting with overlap
    • Metadata preservation per chunk

5.4 Embedding Generation

  • Install embedding libraries
    • OpenAI SDK: openai
    • VoyageAI SDK (if using)
    • HuggingFace transformers (if using BAAI/bge)
  • Create /lib/embeddings/openai.ts
    • Generate embeddings using OpenAI text-embedding-3-small or text-embedding-ada-002
    • Batch processing support
    • Error handling and retries
  • Create /lib/embeddings/voyage.ts (optional)
  • Create /lib/embeddings/huggingface.ts (optional)
  • Create /lib/embeddings/index.ts (unified interface)

5.5 Ingestion API Route

  • Create /app/api/documents/[id]/ingest/route.ts (implemented as /app/api/ingestion/process/route.ts)
    • Accept document ID
    • Fetch document from storage
    • Parse document (PDF/text)
    • Chunk content
    • Generate embeddings (batch)
    • Store chunks in database with vectors
    • Update document status
    • Return ingestion result
  • Add progress tracking (optional: WebSocket or polling)

5.6 Background Processing (Optional Enhancement)

  • Set up background job processing
    • Option A: Vercel Cron Jobs
    • Option B: Queue system (BullMQ, etc.)
  • Create ingestion queue worker
  • Handle retries and failures

5.7 Ingestion Status Updates

  • Create real-time status updates using Supabase Realtime
  • Update UI when document status changes
  • Show progress bar during ingestion

Phase 6: Vector Search Implementation

6.1 Vector Search Utilities

  • Create /lib/vector/search.ts
    • Function to generate query embedding
    • Function to perform similarity search
    • Configurable top-k results
    • Filter by user_id and document_id
    • Return chunks with similarity scores

6.2 Search API Route

  • Create /app/api/search/route.ts
    • Accept query string
    • Generate query embedding
    • Perform vector search
    • Return results with metadata
    • Include document references

6.3 Hybrid Search (Optional Enhancement)

  • Implement keyword + vector hybrid search
  • Combine BM25 and vector similarity scores
  • Create /lib/vector/hybrid-search.ts

Phase 7: Chat Interface (Frontend)

7.1 Chat Layout

  • Create /app/(dashboard)/chat/page.tsx
    • Main chat interface layout
    • Sidebar for conversations
    • Main chat area
    • Sources panel
  • Create responsive layout (mobile-friendly)

7.2 Conversation List

  • Create /components/chat/conversation-list.tsx
    • List of user conversations
    • Conversation titles
    • Last message preview
    • Timestamp
    • Create new conversation button
  • Create /components/chat/conversation-item.tsx
  • Add conversation search/filter

7.3 Chat Messages Display

  • Create /components/chat/message-list.tsx
    • Display messages in chronological order
    • User messages (right-aligned)
    • Assistant messages (left-aligned)
    • Streaming message support
    • Markdown rendering for assistant messages
  • Create /components/chat/message-bubble.tsx
  • Create /components/chat/message-avatar.tsx
  • Add copy button for messages
  • Add timestamp display

7.4 Chat Input

  • Create /components/chat/chat-input.tsx
    • Textarea with auto-resize
    • Send button
    • Keyboard shortcuts (Enter to send, Shift+Enter for new line)
    • Character/token counter (optional)
    • Disable during streaming
  • Create /components/chat/input-toolbar.tsx (settings are loaded from user settings, not in toolbar)
    • Model selector
    • Temperature slider
    • Settings button

7.5 Streaming Response Handler

  • Streaming implemented directly in /components/chat/chat-interface.tsx (no separate stream-handler.ts)
    • Handle Server-Sent Events (SSE)
    • Parse streaming chunks
    • Update UI incrementally
  • Streaming logic implemented in chat-interface.tsx (no separate use-chat-stream hook)
    • React hook for streaming
    • State management
    • Error handling

7.6 Sources Panel

  • Create /components/chat/sources-panel.tsx
    • Display retrieved chunks
    • Show document names
    • Highlight relevant text
    • Link to source documents
    • Collapsible/expandable

Phase 8: RAG Chat Backend

8.1 Chat API Route

  • Create /app/api/chat/route.ts
    • Accept POST request with:
      • conversation_id (or create new)
      • message content
      • model preferences
    • Retrieve conversation history
    • Perform RAG retrieval
    • Build prompt with context
    • Call LLM provider
    • Stream response
    • Save messages to database
    • Log evaluation data

8.2 RAG Retrieval Logic

  • Create /lib/rag/retrieve.ts (integrated into chat API route)
    • Generate query embedding
    • Perform vector search (top-k)
    • Filter by user's documents
    • Rank and re-rank results
    • Format chunks for prompt

8.3 Prompt Building

  • Create /lib/rag/prompt-builder.ts
    • System prompt template
    • Context injection
    • Conversation history formatting
    • Token counting
    • Context window management

8.4 LLM Provider Integration

8.4.1 OpenAI Integration

  • Create /lib/llm/openai.ts
    • Initialize OpenAI client
    • Chat completion with streaming
    • Handle errors and retries
    • Token counting

8.4.2 Anthropic Integration

  • Create /lib/llm/anthropic.ts
    • Initialize Anthropic client
    • Messages API with streaming
    • Handle errors and retries

8.4.3 Groq Integration

  • Create /lib/llm/groq.ts
    • Initialize Groq client
    • Ultra-low-latency inference
    • Model selection (Llama 3, Mixtral)

8.4.4 Unified LLM Interface

  • Create /lib/llm/index.ts
    • Unified interface for all providers
    • Provider selection logic
    • Fallback mechanism
    • Consistent response format

8.5 Conversation Memory

  • Create /lib/chat/memory.ts
    • Fetch conversation history
    • Manage context window
    • Summarize old messages (optional)
    • Maintain conversation state

8.6 Message Persistence

  • Create /lib/chat/save-message.ts
    • Save user message
    • Save assistant message
    • Update conversation timestamp
    • Handle errors

Phase 9: Semantic Search UI

9.1 Search Page

  • Create /app/(dashboard)/search/page.tsx
    • Search input
    • Results display
    • Filters (by document, date range)
  • Create /components/search/search-bar.tsx
  • Create /components/search/search-filters.tsx

9.2 Search Results

  • Create /components/search/search-results.tsx
    • Display matched chunks
    • Highlight matching text
    • Show similarity scores
    • Document references
    • Pagination
  • Create /components/search/result-item.tsx
  • Create /components/search/result-highlight.tsx

9.3 Search Integration

  • Connect search UI to search API
  • Add debouncing for search input (not yet implemented)
  • Add loading states
  • Add empty states

Phase 10: Analytics & Logging

10.1 Logging Infrastructure

  • Create /lib/analytics/logger.ts
    • Log request/response
    • Log tokens used
    • Log latency
    • Log provider/model
    • Log errors
  • Create /lib/analytics/log-eval.ts (implemented as logger.ts)
    • Save to eval_logs table
    • Batch logging support

10.2 Analytics Page

  • Create /app/(dashboard)/analytics/page.tsx
    • Overview dashboard
    • Charts/graphs (using recharts or similar)
    • Metrics display
  • Create /components/analytics/metrics-card.tsx
  • Create /components/analytics/usage-chart.tsx

10.3 Analytics Queries

  • Create /lib/analytics/queries.ts
    • Messages per session
    • Token usage over time
    • Model response latency
    • Provider usage distribution
    • Error rates

10.4 Analytics API Routes

  • Create /app/api/analytics/usage/route.ts
    • GET: Fetch usage statistics
    • Date range filtering
  • Create /app/api/analytics/tokens/route.ts
    • GET: Fetch token usage
  • Create /app/api/analytics/latency/route.ts
    • GET: Fetch latency metrics

Phase 11: Settings & Configuration

11.1 Settings Page

  • Create /app/(dashboard)/settings/page.tsx
    • Tabs for different settings sections
    • Model selection (implemented with Select component)
    • Temperature control (implemented with Slider component)
    • System prompt editor (implemented with Textarea component)
    • Memory toggle
  • Model selector (integrated into settings page with Select component)
  • Temperature slider (integrated into settings page with Slider component)
  • System prompt editor (integrated into settings page with Textarea component)

11.2 Settings Persistence

  • Create /app/actions/settings/update.ts
    • Save user preferences
    • Update conversation defaults
  • Create settings storage (database or localStorage)
  • Create /lib/settings/get-settings.ts

11.3 User Preferences

  • Add preferences table (optional) or use JSONB in profiles
  • Store: theme, default model, default temperature, etc.
  • Load preferences on app initialization

Phase 12: Dashboard & Navigation

12.1 Main Dashboard

  • Create /app/(dashboard)/page.tsx
    • Welcome message
    • Quick stats (document count, total chunks, conversations) - basic welcome page only
    • Recent documents (not yet implemented)
    • Recent conversations (not yet implemented)
    • Quick actions (not yet implemented)
  • Create /components/dashboard/stats-grid.tsx
  • Create /components/dashboard/recent-activity.tsx

12.2 Navigation

  • Create /components/layout/sidebar.tsx
    • Navigation links
    • User menu
    • Logout button
  • Create /components/layout/header.tsx
    • App title/logo
    • User avatar
    • Notifications (optional)
  • Create /components/layout/main-layout.tsx
    • Combine header, sidebar, main content
    • Responsive design

12.3 Empty States

  • Create /components/empty-states/no-documents.tsx (integrated into document-list)
  • Create /components/empty-states/no-conversations.tsx
  • Create /components/empty-states/no-search-results.tsx (integrated into search-results)

Phase 13: Error Handling & Edge Cases

13.1 Error Boundaries

  • Create /components/error-boundary.tsx
    • Catch React errors
    • Display user-friendly error messages
    • Log errors
  • Wrap app with error boundary

13.2 API Error Handling

  • Create /lib/errors/api-error.ts
    • Standardized error format
    • Error codes
    • User-friendly messages
  • Add error handling to all API routes
  • Add error handling to Server Actions

13.3 Loading States

  • Create /components/loading/spinner.tsx
  • Create /components/loading/skeleton.tsx
  • Add loading states to all async operations

13.4 Validation

  • Add Zod schemas for all inputs
  • Validate file uploads
  • Validate API requests
  • Validate forms

Phase 14: Performance Optimization

14.1 Code Splitting

  • Implement dynamic imports for heavy components
  • Lazy load chat interface
  • Lazy load analytics charts

14.2 Caching Strategy

  • Implement React Server Component caching
  • Add caching headers to API routes
  • Cache embeddings (optional)
  • Use Vercel KV for session caching (optional)

14.3 Database Optimization

  • Review and optimize database queries
  • Add missing indexes
  • Optimize vector search queries
  • Implement query result pagination

14.4 Bundle Size Optimization

  • Analyze bundle size
  • Remove unused dependencies
  • Optimize imports
  • Use tree-shaking

Phase 15: Testing

15.1 Unit Tests

  • Set up Jest and React Testing Library
  • Test utility functions
  • Test components
  • Test hooks

15.2 Integration Tests

  • Test API routes
  • Test Server Actions
  • Test database operations

15.3 E2E Tests (Optional)

  • Set up Playwright or Cypress
  • Test user flows:
    • Sign up → Upload document → Chat
    • Search → View results
    • Settings → Update preferences

Phase 16: Deployment

16.1 Vercel Deployment

  • Connect GitHub repository to Vercel
  • Configure environment variables
  • Set up build settings
  • Deploy to production
  • Configure custom domain (optional)

16.2 Supabase Production Setup

  • Verify production database
  • Run migrations
  • Configure production storage buckets
  • Set up production auth settings
  • Configure CORS and security settings

16.3 Monitoring & Observability

  • Set up error tracking (Sentry or similar)
  • Set up analytics (PostHog or Vercel Analytics)
  • Monitor API performance
  • Set up alerts for errors

16.4 Documentation

  • Write README.md with setup instructions
  • Document environment variables
  • Document API endpoints
  • Create user guide (optional)

Phase 17: Polish & Refinement

17.1 UI/UX Polish

  • Review all pages for consistency
  • Ensure responsive design works on all devices
  • Add animations and transitions
  • Improve loading states
  • Add tooltips and help text

17.2 Accessibility

  • Add ARIA labels
  • Ensure keyboard navigation
  • Test with screen readers
  • Ensure color contrast

17.3 Security Review

  • Review RLS policies
  • Review API authentication
  • Review file upload security
  • Review XSS prevention
  • Review CSRF protection

17.4 Performance Testing

  • Load testing for API routes
  • Test with large documents
  • Test with many conversations
  • Optimize slow queries

Implementation Order Summary

Week 1: Foundation

  • Phase 1: Project Setup
  • Phase 2: Supabase & Database
  • Phase 3: Authentication

Week 2: Core Features

  • Phase 4: Document Upload
  • Phase 5: Ingestion Pipeline
  • Phase 6: Vector Search

Week 3: Chat & Search

  • Phase 7: Chat Frontend
  • Phase 8: RAG Backend
  • Phase 9: Semantic Search UI

Week 4: Polish & Deploy

  • Phase 10: Analytics
  • Phase 11: Settings
  • Phase 12: Dashboard
  • Phase 13-17: Error Handling, Optimization, Testing, Deployment

Key Dependencies Between Phases

  1. Phase 2 → Phase 3: Database must exist before auth
  2. Phase 2 → Phase 4: Documents table needed for upload
  3. Phase 4 → Phase 5: Upload must work before ingestion
  4. Phase 5 → Phase 6: Chunks must exist before search
  5. Phase 6 → Phase 8: Vector search needed for RAG
  6. Phase 7 → Phase 8: Frontend needs backend API
  7. Phase 8 → Phase 10: Chat must work before analytics

Notes

  • Each phase should be completed and tested before moving to the next
  • Use feature flags for incomplete features
  • Commit frequently with descriptive messages
  • Test on multiple browsers and devices
  • Keep security and performance in mind throughout

Estimated Timeline

  • Minimum Viable Product (MVP): 3-4 weeks
  • Full Production Version: 6-8 weeks
  • With Testing & Polish: 8-10 weeks

This roadmap is designed to be followed sequentially, but some phases can be worked on in parallel with proper coordination.