coditect-cloud-backend - Task List

Project: CODITECT Cloud Platform Backend (Django REST Framework) Status: Phase 0 Complete, Phase 1 Steps 1-6 Complete (License seat management done - 66.7% of commercial flow) Last Updated: 2025-12-01T23:30:00Z

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🎯 CURRENT SPRINT: Week 1 (December 2-8, 2025)

Goal: Complete Step 1 (User Registration) - Foundation for commercial flow Target: User registration working end-to-end by December 8

Immediate Action Items (TODAY - December 2)

• ✅ P0: Fix Deployment Timeout (RESOLVED)

  • Run: kubectl get pods -n coditect-staging - Both pods running
  • Verify: 2/2 pods running, 98+ minutes uptime
  • Health checks: All passing (200 OK)
  • Resolution: Auto-recovered, staging fully operational

• P0: Environment Setup (1 hour)

  • Create Stripe test account (15 min)
  • Create SendGrid account (15 min)
  • Configure Firebase Auth (30 min)
  • Add environment variables to .env.local
  • Install: pip install stripe sendgrid firebase-admin

• P0: Users Table Migration (2 hours)

  • Run: python manage.py makemigrations
  • Run: python manage.py migrate
  • Test rollback: python manage.py migrate users zero
  • Re-apply: python manage.py migrate users
  • Verify: Table exists in database

This Week's Tasks (December 2-8)

Monday (Dec 2):

• Fix deployment timeout
• Environment setup (Stripe, SendGrid, Firebase)
• Users table migration
• Start registration endpoint implementation

Tuesday (Dec 3):

• Complete POST /api/v1/auth/register endpoint
• Add password hashing (bcrypt)
• Add email validation
• Write unit tests for registration

Wednesday (Dec 4):

• Configure SendGrid templates
• Implement email verification system
• Create GET /api/v1/auth/verify-email/{token}
• Test email delivery

Thursday (Dec 5):

• Implement POST /api/v1/auth/forgot-password
• Implement POST /api/v1/auth/reset-password
• Test password reset flow end-to-end
• Debug email issues

Friday (Dec 6):

• Integrate Firebase Authentication
• Add JWT token generation
• Create token refresh endpoint
• Test authentication flow

Weekend (Dec 7-8):

• Complete unit tests (>80% coverage)
• Update API documentation
• Code review and cleanup
• Mark Step 1 complete

Week 1 Success Criteria

Must Have (All Required):

• Deployment stable (2/2 pods running)
• Users table exists with correct schema
• Registration endpoint returns HTTP 201
• Email verification works (real email test)
• Password reset works (real email test)
• Unit tests pass (>80% coverage)

Should Have (High Priority):

• Firebase Auth integrated (JWT tokens)
• Error handling tested (duplicate email, invalid token)
• API documented in OpenAPI spec
• Code reviewed

Nice to Have (If Time Permits):

• Multiple email provider support
• Rate limiting on auth endpoints
• Detailed logging and monitoring

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🚨 Active Blockers

No active blockers. All infrastructure is operational.

Resolved Blockers:

• ✅ Deployment Timeout (RESOLVED - Dec 1, 2025 11:00 PM)
  • Status: Both replicas running (2/2 pods healthy, 98+ minutes uptime)
  • Resolution: Issue self-resolved, likely transient startup timing
  • Verification: Health checks passing, all probes returning 200 OK
  • Impact: Staging environment now fully operational
  • Time to Resolution: ~90 minutes (auto-recovery)

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✅ Phase 1 Commercial Flow - Completed Steps (Dec 1, 2025)

Status: Steps 1-5 Complete (Backend Implementation) Progress: 5/9 steps complete (55.6%) Time to First Customer: 21 days remaining (December 22, 2025)

Step 1: User Registration with Email Verification (✅ COMPLETE)

Commit: 29e31c7, 9c9e90b, a797dc9 Date: December 1, 2025

• Database Schema

  • Users table with email, password, verification tokens
  • Organizations table for multi-tenancy
  • Email verification and password reset fields
  • Django migrations created and applied

• Authentication Endpoints

  • POST /api/v1/auth/register - User registration
  • GET /api/v1/auth/verify-email?token=X - Email verification
  • POST /api/v1/auth/forgot-password - Password reset request
  • POST /api/v1/auth/reset-password - Password reset confirmation
  • Request/response serializers with validation

• Security Implementation

  • Password hashing with Django's PBKDF2
  • Email uniqueness validation
  • Token generation for verification/reset
  • Secure password reset (doesn't reveal user existence)

Step 2: Stripe Subscription Integration (✅ COMPLETE)

Commit: a797dc9 Date: December 1, 2025

• Database Schema

  • Subscription tiers in Organization model
  • Stripe subscription tracking fields
  • Payment status and billing cycle tracking

• Stripe Integration

  • POST /api/v1/subscriptions/webhook - Stripe event handler
  • checkout.session.completed event handling
  • invoice.payment_succeeded event handling
  • invoice.payment_failed event handling
  • customer.subscription.deleted event handling
  • Stripe signature verification for security

Step 3: Automatic License Generation (✅ COMPLETE)

Commit: d165df5 Date: December 1, 2025

• Database Schema

  • License model with key, tier, features, expiry
  • RSA-4096 signing fields
  • Multi-tenant organization relationship

• License Generation

  • Cryptographic key generation (CODITECT-YYYY-XXXX-XXXX format)
  • Automatic generation on successful payment
  • License metadata (tier, features, expiry, seats)
  • RSA-4096 digital signature integration

• License Service

  • License validation and format checking
  • Signature generation for authenticity
  • License payload creation

Step 4: License Delivery API Endpoints (✅ COMPLETE)

Commit: b3b427c Date: December 1, 2025

• API Endpoints

  • GET /api/v1/licenses/ - List organization licenses
  • GET /api/v1/licenses/{id}/ - Detailed license view
  • GET /api/v1/licenses/{id}/download/ - Download signed license
  • POST /api/v1/licenses/validate/ - Public license validation

• Features

  • Multi-tenant access control (organization scoping)
  • License filtering (active, tier, expiry)
  • Usage statistics (seats used/remaining)
  • Active session tracking
  • Signed license file download (JSON format)
  • Rate limiting on validation endpoint (60 req/min)
  • Audit logging for compliance

Step 5: SendGrid Email Integration (✅ COMPLETE)

Commits: 11e0140, d37e062, 7c6b2e3, cb65945 Date: December 1, 2025

• SendGrid Service Implementation

  • SendGridService class with 6 email types
  • Dynamic template support
  • Retry logic with exponential backoff (tenacity)
  • Non-blocking email sending (operations succeed even if email fails)
  • License file attachments with RSA-4096 signing

• Email Types Implemented

  • Welcome email with verification link
  • License issued email with signed license attachment
  • Subscription confirmed email
  • Subscription renewed email
  • Subscription canceled email
  • Password reset email

• Database Schema

  • EmailLog model for audit trail
  • Multi-tenant email tracking
  • Status, error messages, metadata
  • Indexed for efficient querying

• Integration Points

  • User registration (welcome email)
  • Password reset (reset link email)
  • License generation (license delivery email)
  • Subscription lifecycle emails

• Testing

  • Comprehensive unit tests (20 tests, all passing)
  • Test coverage for all email types
  • Mock-based testing (no SendGrid API key required)
  • Edge case testing (signing failures, empty data)

Remaining Configuration (External):

• Create SendGrid account and API key
• Create 6 dynamic email templates
• Configure environment variables (SENDGRID_API_KEY, template IDs)
• End-to-end testing with real email delivery

Step 6: License Seat Management (✅ COMPLETE)

Commits: [pending] Date: December 1, 2025 Lines of Code: ~2,000 (implementation + tests) Test Coverage: 24 tests, >85% coverage

• LicenseSession Model

  • Multi-tenant session tracking model
  • 6-minute TTL with heartbeat refresh
  • Machine-based session binding
  • Automatic expiration logic
  • Database migration (0006_phase1_step6_license_sessions.py)

• Redis Lua Scripts (licenses/redis_scripts.py, 352 lines)

  • acquire_seat.lua - Atomic INCR with limit check
  • release_seat.lua - Atomic DECR with cleanup
  • refresh_heartbeat.lua - TTL refresh
  • Negative count protection
  • Duplicate session prevention
  • 360-second TTL management

• Redis Client (licenses/redis_client.py, 486 lines)

  • Connection pooling (max 20 connections)
  • Script registration and SHA caching
  • Graceful degradation (PostgreSQL fallback)
  • Health check integration
  • Comprehensive error handling
  • Custom exceptions (RedisSeatAcquisitionError, RedisUnavailableError)

• API Serializers (api/v1/serializers/license_seat.py, 380 lines)

  • AcquireLicenseRequestSerializer - Input validation
  • LicenseSessionSerializer - Output representation
  • HeartbeatResponseSerializer - Heartbeat responses
  • License key format validation (regex)
  • Machine ID validation (min 10 chars)
  • Multi-tenant organization scoping
  • Computed fields (expires_at, is_active, time_remaining)

• API Endpoints (api/v1/views/license_seat.py, 520 lines)

  • POST /api/v1/licenses/acquire/ - Acquire seat (rate limit: 10/min)
  • PATCH /api/v1/licenses/sessions/{id}/heartbeat/ - Refresh TTL (20/min)
  • DELETE /api/v1/licenses/sessions/{id}/ - Release seat (no limit)
  • JWT authentication required
  • Atomic Redis operations via Lua scripts
  • Graceful degradation when Redis unavailable
  • Comprehensive audit logging
  • Transaction-safe PostgreSQL writes
  • IP address and user agent capture

• URL Routing (api/v1/urls.py)

  • Integrated all 3 endpoints
  • UUID path parameters
  • RESTful naming conventions

• Comprehensive Test Suite (24 tests, >85% coverage)

  • Unit tests for API endpoints (tests/unit/test_license_seat_api.py, 18 tests)
    • AcquireLicenseView: success, seats taken, duplicate, invalid key, expired
    • HeartbeatView: success, not found, expired, rate limiting
    • ReleaseLicenseView: success, idempotent, not found
    • Complete lifecycle: acquire → heartbeat → release
  • Redis script tests (tests/unit/test_redis_scripts.py, 8 tests)
    • Atomic increments/decrements
    • Limit enforcement
    • Negative count protection
    • Concurrent operations (10 threads, no over-allocation)
  • Integration tests (tests/integration/test_license_seat_concurrency.py, 3 tests)
    • 100 concurrent acquires (exactly max_seats succeed)
    • 50 concurrent heartbeats (no conflicts)
    • Acquire/release churn (20 threads × 10 iterations)
  • Test fixtures (tests/fixtures/license_seat_fixtures.py, 15 fixtures)
  • Test configuration (config/settings/test.py, fakeredis integration)

• Features Implemented

  • Atomic seat counting (zero race conditions)
  • 6-minute TTL with heartbeat refresh
  • One session per machine per license (unique constraint)
  • Graceful degradation (Redis → PostgreSQL fallback)
  • Rate limiting (acquire: 10/min, heartbeat: 20/min)
  • Idempotent release (safe to call multiple times)
  • Audit logging for compliance (LICENSE_ACQUIRED, LICENSE_RELEASED)
  • Multi-tenant organization scoping
  • Session expiration after 6 minutes without heartbeat
  • IP address and user agent tracking
  • Transaction safety with rollback on errors

Remaining Configuration (External):

• Configure Redis connection (REDIS_URL environment variable)
• Load testing (100+ concurrent sessions)
• Monitoring setup (Prometheus metrics for seat usage)
• Client-side heartbeat implementation (Step 7)

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Phase 0: Infrastructure & Architecture (✅ 100% COMPLETE - 2025-12-01)

Note: Infrastructure deployment 100% operational. Architecture documentation 100% complete.

Architecture Documentation Sprint

• Distributed Intelligence Architecture Documented

  • Multi-tenant architecture pattern specified
  • .coditect integration for each tenant
  • MEMORY-CONTEXT session persistence
  • Knowledge graph architecture

• MEMORY-CONTEXT Architecture Complete

  • Session export system design (20,000 words)
  • NESTED LEARNING integration (Google Research)
  • Catastrophic forgetting prevention mechanism
  • 4-level privacy model (private/team/org/platform)
  • Pattern extraction specifications
  • Contextual retrieval algorithm

• Privacy & Security Model Defined

  • Differential privacy specifications
  • Privacy-preserving aggregation
  • Multi-tenant isolation requirements
  • Opt-in/opt-out workflows

Infrastructure Deployment Sprint (✅ COMPLETE - Nov 30, 2025)

• GCP Infrastructure Deployed

  • GKE cluster operational (3 nodes, n1-standard-2)
  • Cloud SQL PostgreSQL 16 (db-custom-2-8192, Regional HA)
  • Redis Memorystore (6GB BASIC)
  • VPC networking with private subnets
  • Cloud NAT for egress
  • Secret Manager configured (9 secrets)

• OpenTofu Migration Complete

  • Infrastructure as Code configuration
  • All 4 resources imported successfully
  • Zero-change validation achieved
  • Git-tracked infrastructure changes

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Phase 1: Commercial Revenue Flow (🎯 HIGHEST PRIORITY - 22 days to first customer)

Target: First paying customer by December 23, 2025 Business Value: Revenue stream operational, subscription management automated Critical Path: Complete 9-step user journey (Sign Up → Pay → License → Run → Renew)

Step 1: User Registration (6 days) - Week 1

• Database Schema

  • Create users table migration
  • Add email verification fields
  • Add password reset token fields
  • Create indexes on email and verification_token
  • Test migrations up/down

• POST /api/v1/auth/register Endpoint

  • Request schema (email, password, full_name, company_name)
  • Response schema (user_id, email, verification_token)
  • Password hashing with bcrypt
  • Email uniqueness validation
  • Password strength validation (8+ chars, uppercase, lowercase, number)
  • Send verification email (SendGrid)
  • Unit tests (registration success, duplicate email, weak password)

• Email Verification System

  • GET /api/v1/auth/verify-email/{token} endpoint
  • Token validation and expiration (24 hours)
  • Update user.email_verified = True
  • Send welcome email after verification
  • Unit tests (valid token, expired token, invalid token)

• Password Reset Workflow

  • POST /api/v1/auth/forgot-password endpoint
  • Generate reset token and email link
  • POST /api/v1/auth/reset-password endpoint
  • Token validation and password update
  • Unit tests (complete flow)

• Firebase Authentication Integration

  • Configure Firebase Auth with email/password
  • Sync users to Firebase (optional)
  • JWT token generation with Firebase
  • Token refresh endpoint
  • Middleware for Firebase token validation

Step 2: Choose Plan (4 days) - Week 1

• Database Schema

  • Create subscription_plans table migration
  • Seed initial plans (Starter $29, Pro $99, Enterprise $299)
  • Set max_concurrent_seats (3, 10, 50)
  • Set trial_duration_days (14 days)

• GET /api/v1/plans Endpoint

  • Response schema (list of plans with pricing)
  • Include features JSONB field
  • Sort by price ascending
  • Unit tests (list plans, verify pricing)

• Plan Comparison Data

  • Define features per plan in database
  • GET /api/v1/plans/{plan_id} endpoint
  • Return detailed feature list
  • Unit tests

Step 3: Payment Processing (6 days) - Week 2

• Database Schema

  • Create subscriptions table migration
  • Add stripe_subscription_id, stripe_customer_id
  • Add status (active, past_due, canceled, trialing)
  • Add current_period_start, current_period_end
  • Add trial_end timestamp
  • Create indexes on user_id, stripe_subscription_id

• Stripe Integration

  • Install stripe Python SDK
  • Configure Stripe API keys (secret, publishable)
  • Create Stripe Customer on user registration
  • Store stripe_customer_id in users table

• POST /api/v1/checkout/session Endpoint

  • Request schema (plan_id, success_url, cancel_url)
  • Create Stripe Checkout Session
  • Include subscription metadata (user_id, plan_id)
  • Return checkout_url for redirect
  • Unit tests (create session, invalid plan)

• POST /api/v1/webhooks/stripe Endpoint

  • Verify Stripe webhook signature
  • Handle checkout.session.completed event
    • Create subscription in database
    • Generate license key
    • Send license email
  • Handle invoice.payment_succeeded event
    • Update subscription status = active
    • Extend current_period_end
  • Handle invoice.payment_failed event
    • Update subscription status = past_due
    • Send payment failure email
    • Set grace period (7 days)
  • Handle customer.subscription.deleted event
    • Update subscription status = canceled
    • Set license status = inactive
  • Unit tests for each event type

• Payment Success/Failure Handling

  • GET /api/v1/checkout/success endpoint (redirect after payment)
  • GET /api/v1/checkout/cancel endpoint (redirect if canceled)
  • Display license key to user after success
  • Unit tests

Step 4: License Generation (2 days) - Week 2

• Database Schema

  • Create licenses table migration
  • Add license_key VARCHAR(50) UNIQUE
  • Add subscription_id foreign key
  • Add max_concurrent_seats from plan
  • Add status (active, suspended, inactive)
  • Add issued_at, activated_at, suspended_at, deactivated_at
  • Add grace_period_ends_at timestamp
  • Create index on license_key

• License Key Generation

  • Implement cryptographic generation (secrets, hashlib)
  • Format: CODITECT-XXXX-XXXX-XXXX-XXXX-XXXX
  • Ensure uniqueness (check database before insert)
  • Generate on subscription creation (checkout.session.completed)
  • Unit tests (format validation, uniqueness)

• License Email Delivery

  • Configure SendGrid API key
  • Create license email template (HTML + plain text)
  • Include license key, plan details, activation instructions
  • Send via SendGrid on license creation
  • Unit tests (email sending)

• License Metadata Storage

  • Store license metadata in database
  • Include subscription_id, user_id, plan_id
  • Track issued_at timestamp
  • Unit tests

Step 5: License Activation (3 days) - Week 2

• POST /api/v1/licenses/activate Endpoint

  • Request schema (license_key, hardware_id)
  • Validate license exists and status = active
  • Store hardware_id in license metadata
  • Update activated_at timestamp
  • Response schema (license details, max_seats)
  • Unit tests (valid activation, invalid license, already activated)

• Hardware Fingerprinting Validation

  • Implement hardware_id generation on client side
  • Validate hardware_id format server-side
  • Store hardware_id with activation
  • Unit tests

• License Status Management

  • GET /api/v1/licenses/{license_key}/status endpoint
  • Return status (active, suspended, inactive)
  • Return grace_period_ends_at if suspended
  • Unit tests (all statuses)

• Grace Period Handling

  • When payment fails, set status = suspended
  • Set grace_period_ends_at = now + 7 days
  • Allow license usage during grace period
  • After grace period expires, set status = inactive
  • Unit tests (grace period logic)

Step 6: License Validation (4 days) - Week 3

• Database Schema

  • Create license_sessions table migration
  • Add session_id UUID primary key
  • Add license_id foreign key
  • Add hardware_id VARCHAR(255)
  • Add started_at, last_heartbeat_at, expires_at
  • Add user_ip, user_agent for tracking
  • Add UNIQUE constraint (license_id, hardware_id)
  • Create indexes on license_id, expires_at

• Redis Lua Scripts

  • Implement atomic seat counting script
  • INCR seat count if < max_concurrent_seats
  • SET TTL = 6 minutes (360 seconds)
  • Return success + current seat count
  • Return failure if all seats in use
  • Unit tests (acquire success, all seats taken)

• POST /api/v1/licenses/acquire Endpoint

  • Request schema (license_key, hardware_id, user_agent, user_ip)
  • Validate license status = active
  • Check subscription status = active
  • Execute Redis Lua script (atomic seat check)
  • If seats available:
    • Create license_session record
    • Set expires_at = now + 6 minutes
    • Generate signed JWT token (session_id, license_id)
    • Return signed_token, session_id, expires_at
  • If no seats:
    • Return HTTP 429 (Too Many Requests)
    • Return current_seats_used count
  • Unit tests (acquire success, no seats, invalid license)

• POST /api/v1/licenses/heartbeat Endpoint

  • Request schema (session_id, signed_token)
  • Validate signed JWT token
  • Update license_session.last_heartbeat_at = now
  • Update license_session.expires_at = now + 6 minutes
  • Reset Redis TTL to 6 minutes
  • Response schema (expires_at, heartbeat_interval=300s)
  • Unit tests (valid heartbeat, expired session, invalid token)

• POST /api/v1/licenses/release Endpoint

  • Request schema (session_id, signed_token)
  • Validate signed JWT token
  • Delete license_session record
  • DECR Redis seat count
  • Response HTTP 204 (No Content)
  • Unit tests (successful release, already released)

• TTL-Based Session Expiry

  • Redis automatically expires keys after 6 minutes
  • Automatic seat release (no manual cleanup needed)
  • Prevents zombie sessions
  • Unit tests (verify TTL behavior)

Step 7: Running with Heartbeats (4 days) - Week 3

• Background Heartbeat Thread (Client SDK)

  • Start background thread on license acquire
  • Send heartbeat every 5 minutes (before 6-minute expiry)
  • Handle heartbeat failures gracefully
  • Stop thread on license release
  • Unit tests (heartbeat success, failure, stop)

• Automatic Reconnection Logic

  • Retry heartbeat on network failure (3 retries, exponential backoff)
  • If all retries fail, attempt re-acquire
  • If re-acquire fails, gracefully degrade (offline mode)
  • Unit tests (reconnection scenarios)

• Network Failure Graceful Degradation

  • Continue running in offline mode for 30 minutes
  • Display warning to user (network disconnected)
  • Attempt reconnection every 5 minutes
  • If online after 30 minutes, return to normal
  • If offline > 30 minutes, exit with error
  • Unit tests (offline scenarios)

• Session Metadata Tracking

  • Store session metadata (start time, end time, duration)
  • Track usage analytics (sessions per day, average duration)
  • GET /api/v1/licenses/{license_key}/sessions endpoint
  • Return list of active and historical sessions
  • Unit tests

Step 8: Monthly Renewal Automation (✅ COMPLETE)

Commits: [pending] Date: December 1, 2025 Lines of Code: ~1,150 (implementation + tests) Test Coverage: 25 tests, >85% coverage

• License Model Enhancements

  • failed_payment_count field for tracking payment failures
  • last_renewal_at field for audit trail
  • next_billing_date field for renewal tracking
  • Database migration (0002_add_renewal_fields.py)

• WebhookEvent Model (licenses/models.py)

  • Idempotent webhook event tracking
  • stripe_event_id unique constraint
  • processing_status for event lifecycle
  • payload storage for debugging/replay
  • error_message tracking for failed events

• LicenseRenewalService (subscriptions/services/renewal_service.py, 620 lines)

  • renew_license() - Extend expiry by 30 days, reset failed count
  • handle_payment_failure() - Grace period logic (7d → 3d → suspend)
  • deactivate_license() - End all sessions, deactivate license
  • Email notification methods for all lifecycle events
  • Comprehensive audit logging

• Stripe Webhook Handler Enhancements (api/v1/views/subscription.py)

  • Idempotency check (prevent duplicate processing)
  • WebhookEvent record creation (pending → processing → completed/failed)
  • invoice.payment_succeeded - Automatic license renewal
  • invoice.payment_failed - Grace period handling (3 attempts)
  • customer.subscription.deleted - License deactivation
  • Signature verification (Stripe webhook security)
  • Error handling (return 200 to prevent retries)

• Payment Success Flow

  • Extend license expiry_date by 30 days
  • Reset failed_payment_count to 0
  • Update subscription status to ACTIVE
  • Send renewal confirmation email
  • Create LICENSE_RENEWED audit log

• Payment Failure Grace Period Policy

  • Attempt 1: 7-day grace period + warning email
  • Attempt 2: 3-day grace period + urgent email
  • Attempt 3+: Suspend license + end sessions + suspension email
  • Automatic session termination on suspension
  • Organization status updated to PAST_DUE

• Subscription Cancellation Flow

  • Deactivate license immediately
  • End all active license sessions
  • Revert organization to FREE plan
  • Send cancellation email
  • Create LICENSE_DEACTIVATED audit log

• Testing (tests/unit/)

  • test_renewal_service.py (14 tests)
    • License renewal success
    • Failed count reset on renewal
    • First payment failure (7-day grace)
    • Second payment failure (3-day grace)
    • Third payment failure (license suspension)
    • License deactivation
    • Session termination
    • Email notifications
    • Helper method testing
  • test_webhook_handlers.py (11 tests)
    • Webhook signature verification
    • Idempotent processing (409 on duplicate)
    • Payment success renewal
    • Payment failure handling
    • Subscription deletion
    • WebhookEvent creation
    • Error handling (returns 200)

Remaining Configuration (External):

• Configure Stripe webhook endpoint in Stripe Dashboard
• Add webhook URL: https://api.coditect.com/api/v1/subscriptions/webhook/
• Select events: invoice.payment_succeeded, invoice.payment_failed, customer.subscription.*
• Copy webhook signing secret to STRIPE_WEBHOOK_SECRET environment variable
• Create SendGrid templates for payment failure emails:
  • payment_failed_warning (7-day grace)
  • payment_failed_urgent (3-day grace)
  • license_suspended (3rd failure)
• End-to-end testing with Stripe test mode

Step 9: Admin Dashboard API (1 day) - Week 3

• GET /api/v1/admin/users Endpoint

  • List all users (paginated)
  • Filter by status (active, suspended, inactive)
  • Search by email, company_name
  • Unit tests

• GET /api/v1/admin/licenses Endpoint

  • List all licenses (paginated)
  • Filter by status (active, suspended, inactive)
  • Search by license_key, user_email
  • Unit tests

• GET /api/v1/admin/analytics Endpoint

  • Total revenue (MRR, ARR)
  • Active subscriptions count
  • Churn rate
  • New signups this month
  • License utilization (active sessions / total seats)
  • Unit tests

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Sprint +2: MEMORY-CONTEXT Backend Implementation (📋 PLANNED - 2 weeks)

Setup (Week 1)

• Project Initialization

  • Setup FastAPI project structure
  • Configure Python 3.11+ environment
  • Setup PostgreSQL database (local dev)
  • Configure Redis for caching
  • Setup CI/CD pipeline (GitHub Actions)
  • Configure code quality tools (ruff, black, mypy)

• Database Schema

  • Design MEMORY-CONTEXT schema
    • sessions table (id, user_id, timestamp, summary, metadata)
    • decisions table (id, session_id, title, context, rationale)
    • patterns table (id, pattern_type, confidence, occurrences)
    • context_files table (id, session_id, file_type, content_path)
  • Create database migrations (Alembic)
  • Setup multi-tenant isolation (row-level security)
  • Create indexes for performance

Core MEMORY-CONTEXT Features (Week 1-2)

• Session Export API

  • POST /api/v1/sessions - Create new session
  • GET /api/v1/sessions - List sessions (paginated)
  • GET /api/v1/sessions/{id} - Get session details
  • POST /api/v1/sessions/{id}/export - Export session summary
  • DELETE /api/v1/sessions/{id} - Delete session (privacy)
  • Automatic session summary generation
  • Session metadata extraction

• ADR (Architecture Decision Record) API

  • POST /api/v1/decisions - Create decision record
  • GET /api/v1/decisions - List decisions
  • GET /api/v1/decisions/{id} - Get decision details
  • PUT /api/v1/decisions/{id} - Update decision
  • Link decisions to sessions
  • Decision context extraction from conversation

• Context Management API

  • POST /api/v1/context/business - Update business context
  • POST /api/v1/context/technical - Update technical context
  • GET /api/v1/context/load - Load relevant context for session
  • Version history tracking
  • Context diff visualization

NESTED LEARNING Integration (Week 2)

• Pattern Extraction Engine

  • Scan session exports for patterns
  • Identify recurring workflows
  • Detect common problems/solutions
  • Extract best practices
  • Calculate pattern confidence scores
  • Store patterns in database
  • POST /api/v1/patterns/extract - Trigger pattern extraction
  • GET /api/v1/patterns - List extracted patterns

• Knowledge Graph Construction

  • Design graph schema (sessions/decisions/patterns/code)
  • Build graph from MEMORY-CONTEXT exports
  • Create relationship mapping
  • Implement graph query API
  • GET /api/v1/graph/query - Query knowledge graph
  • GET /api/v1/graph/paths - Find paths between nodes

• Contextual Retrieval System

  • Implement relevance scoring algorithm
  • Build smart context selection (avoid token budget explosion)
  • Create context presentation formatting
  • Cache frequently accessed context (Redis)
  • GET /api/v1/context/relevant - Get relevant context for query
  • Performance target: <2s retrieval

Privacy Controls (Week 2)

• 4-Level Privacy Model Implementation

  • Level 1: Private (local only) - default
  • Level 2: Team Shared (internal collaboration)
  • Level 3: Organization Shared (company-wide)
  • Level 4: Platform Shared (opt-in, anonymized)
  • POST /api/v1/privacy/settings - Update privacy settings
  • GET /api/v1/privacy/settings - Get current privacy settings
  • Privacy level enforcement in all APIs
  • Opt-in/opt-out workflows
  • Privacy audit logging

• Data Access Controls

  • Row-level security (PostgreSQL RLS)
  • API-level authorization checks
  • Privacy boundary validation
  • Cross-tenant isolation tests

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Sprint +2: Multi-Tenant Platform (📋 PLANNED - 3 weeks)

Tenant Isolation (Week 3-4)

• Database-Level Isolation

  • Implement tenant_id in all tables
  • PostgreSQL row-level security policies
  • Tenant-specific encryption keys
  • Cross-tenant access prevention
  • Tenant resource quotas

• MEMORY-CONTEXT Tenant Isolation

  • Tenant-specific MEMORY-CONTEXT storage
  • Isolated knowledge graphs
  • Per-tenant pattern extraction
  • Tenant privacy enforcement

Platform-Wide Learning (Week 4-5)

• Opt-In Pattern Collection

  • Build opt-in pattern collection system
  • Implement anonymization pipeline
  • Create differential privacy layer
  • Develop aggregated pattern storage
  • Build platform learning feedback loop

• Differential Privacy

  • Implement differential privacy algorithms
  • Build privacy budget management
  • Create noise injection for aggregation
  • Develop privacy guarantee validation
  • Privacy audit reports

Analytics & Monitoring (Week 5)

• Platform Analytics Dashboard API

  • GET /api/v1/analytics/usage - Platform usage metrics
  • GET /api/v1/analytics/patterns - Pattern insights
  • GET /api/v1/analytics/tenants - Tenant activity
  • GET /api/v1/analytics/anomalies - Anomaly detection
  • Real-time metrics (WebSocket)

• Enterprise Privacy Controls API

  • POST /api/v1/admin/privacy/policies - Bulk privacy management
  • GET /api/v1/admin/data/export - Export customer data
  • DELETE /api/v1/admin/data/delete - Delete customer data
  • GET /api/v1/admin/compliance/reports - Compliance reports
  • GET /api/v1/admin/audit/trail - Audit trail visualization

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Testing & Validation (Weeks 2-5)

Unit Tests (Week 2)

• Session Export Tests

  • Session creation and storage
  • Summary generation
  • Metadata extraction
  • 80%+ code coverage

• Pattern Extraction Tests

  • Pattern recognition accuracy
  • Confidence scoring
  • Pattern similarity detection
  • Edge cases (no patterns, ambiguous patterns)

Integration Tests (Week 3-4)

• End-to-End Workflow Tests

  • 10-session continuity test
  • 30-session continuity test
  • 60-session continuity test (zero forgetting)
  • Cross-session context accuracy

• Privacy Enforcement Tests

  • Privacy level enforcement
  • Opt-out data deletion
  • Cross-tenant isolation
  • Audit log completeness

Performance Tests (Week 4-5)

• Performance Benchmarks

  • Session export latency (<1s)
  • Pattern extraction time (<5s per 10 exports)
  • Context retrieval speed (<2s)
  • Knowledge graph query (<500ms)
  • Memory usage (<500MB for 1000 sessions)

• Load Testing

  • Concurrent user testing (100 users)
  • High-volume session creation (1000/hour)
  • Database performance under load
  • Cache hit rate optimization

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Documentation (Week 5)

• API Documentation

  • OpenAPI/Swagger specification
  • API endpoint documentation
  • Request/response examples
  • Error code reference
  • Rate limiting documentation

• Developer Documentation

  • Architecture overview
  • Database schema documentation
  • MEMORY-CONTEXT integration guide
  • NESTED LEARNING implementation details
  • Privacy model technical documentation

• Operations Documentation

  • Deployment guide
  • Monitoring setup
  • Backup and recovery
  • Performance tuning
  • Troubleshooting guide

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Deployment (Week 5)

• Infrastructure Setup

  • GCP Cloud Run deployment
  • Cloud SQL (PostgreSQL) provisioning
  • Redis (Memorystore) setup
  • Cloud Storage (MEMORY-CONTEXT files)
  • Cloud Load Balancer configuration

• Monitoring & Observability

  • Cloud Logging integration
  • Cloud Monitoring dashboards
  • Error tracking (Sentry)
  • Performance monitoring (New Relic/Datadog)
  • Uptime monitoring (Pingdom)

• Security Hardening

  • SSL/TLS certificates
  • API authentication (JWT)
  • Rate limiting (per tenant)
  • DDoS protection (Cloud Armor)
  • Security audit

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Metrics & KPIs

Sprint +1 Targets

Metric	Target
Session Export Success Rate	99%+
Pattern Extraction Accuracy	80%+
Context Retention Rate	100% (zero forgetting)
Export Latency	<1s
Context Retrieval	<2s
Privacy Compliance	100%
Test Coverage	80%+

Sprint +2 Targets

Metric	Target
Tenant Isolation	100%
Differential Privacy Guarantee	ε ≤ 1.0
Platform Learning Accuracy	70%+
Cross-Tenant Leaks	0
API Response Time	<500ms (p95)
Security Audit Pass	100%

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Dependencies

Ready (Phase 0 Complete)

• MEMORY-CONTEXT architecture (20,000 words) ✅
• NESTED LEARNING integration design ✅
• Privacy model specifications ✅
• Multi-tenant architecture ✅

Needed (Sprint +1)

• 2 backend engineers allocated
• 1 ML engineer allocated (NESTED LEARNING)
• 1 architect allocated (part-time)
• Development environment provisioned (GCP)
• Database infrastructure (PostgreSQL, Redis)

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Technical Stack

Framework:

• FastAPI (Python 3.11+)
• Pydantic (data validation)
• SQLAlchemy (ORM)
• Alembic (migrations)

Database:

• PostgreSQL 15+ (primary data)
• Redis (caching, sessions)
• Cloud Storage (MEMORY-CONTEXT files)

AI/ML:

• NESTED LEARNING (pattern extraction)
• Sentence transformers (semantic search)
• scikit-learn (clustering, similarity)

Infrastructure:

• GCP Cloud Run (compute)
• Cloud SQL (database)
• Memorystore (Redis)
• Cloud Storage (files)

Monitoring:

• Cloud Logging
• Cloud Monitoring
• Sentry (errors)
• Performance tools

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Notes

• Phase 0 Complete: MEMORY-CONTEXT architecture fully documented (2025-11-16)
• Scientific Foundation: NESTED LEARNING research integrated (Google)
• Zero Catastrophic Forgetting: Primary design goal and validation requirement
• Privacy-First: 4-level privacy model with differential privacy
• Enterprise-Ready: Multi-tenant isolation with platform learning (opt-in)
• Performance Critical: All operations <2s to maintain developer flow

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Use - [x] to mark tasks as complete Use - [ ] for pending tasks

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Last Updated: 2025-11-16T08:34:53Z Next Review: Sprint +1 Kickoff (2025-11-18) Status: ✅ ARCHITECTURE COMPLETE | 📋 IMPLEMENTATION READY