Next Steps - Engram Platform Development

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This document outlines the recommended next steps for completing the Engram platform development and deployment.

Immediate Next Steps (Priority 1)

1. Validate Azure AI chat locally

Goal: Confirm text chat works end-to-end with Azure AI (Foundry) key auth.

Steps:

cd backend
export AZURE_AI_KEY="<your-foundry-key>"
export AZURE_AI_ENDPOINT="https://<your-endpoint>.models.ai.azure.com"
export AZURE_AI_PROJECT_NAME="<your-project>"
uvicorn backend.api.main:app --host 0.0.0.0 --port 8082 --reload

Test Cases:

  • /healthz returns 200
  • /api/v1/chat/stream streams tokens
  • Agents swap correctly (Elena/Marcus)
  • No OpenAI or Speech env vars required

2. Harden frontend chat experience

Goal: Ensure chat UI is stable without voice features.

Changes Needed:

  • Verify VITE_API_URL points to backend
  • Keep voice controls hidden/disabled
  • Confirm streaming renders incrementally
  • Add error toasts for missing AZURE_AI_KEY

3. Verify Azure Deployment Configuration

Goal: Ensure all Bicep templates and deployment workflows are correct.

Checklist:

  • Review infra/main.bicep for all required parameters
  • Verify .github/workflows/deploy.yml passes all secrets
  • Check Container App environment variables
  • Verify Key Vault access policies
  • Test Bicep deployment in a dev environment

Commands:

# Validate Bicep templates
az bicep build --file infra/main.bicep

# Test deployment (dry-run)
az deployment group validate \
  --resource-group engram-dev-rg \
  --template-file infra/main.bicep \
  --parameters @infra/parameters/dev.json

Short-term Steps (Priority 2)

4. Complete Agent Brain Implementation

Current Status: Placeholder LangGraph implementations

Tasks:

  • Implement actual LangGraph workflows for Elena
  • Implement actual LangGraph workflows for Marcus
  • Add tool calling and execution
  • Integrate with Zep memory for context retrieval
  • Add error handling and retry logic

Files:

  • backend/agents/elena/agent.py - Complete _reason_node implementation
  • backend/agents/marcus/agent.py - Complete _reason_node implementation
  • backend/agents/base.py - Enhance graph building

5. Integrate Zep Memory Service

Current Status: Placeholder implementations

Tasks:

  • Implement actual Zep client calls
  • Add episodic memory storage
  • Add semantic knowledge graph retrieval
  • Implement memory summarization
  • Add memory search and retrieval

Files:

  • backend/memory/client.py - Complete Zep integration
  • backend/workflows/activities.py - Add memory activities

6. Complete Temporal Workflows

Current Status: Basic workflow structure

Tasks:

  • Implement all workflow activities
  • Add proper error handling and retries
  • Implement human-in-the-loop approval workflow
  • Add workflow monitoring and observability
  • Test long-running conversations

Files:

  • backend/workflows/activities.py - Complete all activities
  • backend/workflows/agent_workflow.py - Enhance workflows
  • backend/workflows/worker.py - Verify worker setup

Medium-term Steps (Priority 3)

7. Frontend Enhancements

Tasks:

  • Add VoiceLive connection status indicator
  • Show agent switching UI
  • Display transcription in real-time
  • Add audio level visualization
  • Improve error handling and user feedback
  • Add voice settings (volume, speed)

8. Observability and Monitoring

Tasks:

  • Verify OpenTelemetry integration
  • Set up Application Insights dashboards
  • Add custom metrics for agent performance
  • Configure alerting for errors
  • Add distributed tracing

Files:

  • backend/observability/telemetry.py - Verify configuration
  • backend/observability/logging.py - Add structured logging

9. Security Hardening

Tasks:

  • Test Microsoft Entra ID authentication
  • Verify RBAC enforcement
  • Add rate limiting
  • Implement PII masking
  • Add audit logging
  • Security testing and penetration testing

Files:

  • backend/api/middleware/auth.py - Test authentication
  • backend/api/middleware/rbac.py - Verify RBAC

10. Performance Optimization

Tasks:

  • Optimize LangGraph execution
  • Cache frequently accessed memory
  • Optimize database queries
  • Add connection pooling
  • Load testing

Long-term Steps (Priority 4)

11. Documentation

Tasks:

  • Complete API documentation
  • Add architecture diagrams
  • Create user guides
  • Document deployment procedures
  • Add troubleshooting guides

12. Testing

Tasks:

  • Unit tests for all agents
  • Integration tests for workflows
  • End-to-end tests
  • Performance tests
  • Security tests

13. Production Readiness

Tasks:

  • Disaster recovery plan
  • Backup and restore procedures
  • Monitoring runbooks
  • Incident response procedures
  • Capacity planning
  1. Week 1: Test VoiceLive locally + Update frontend
  2. Week 2: Complete agent brain + Zep integration
  3. Week 3: Complete Temporal workflows + Testing
  4. Week 4: Frontend enhancements + Observability
  5. Week 5: Security hardening + Performance optimization
  6. Week 6: Documentation + Production readiness

Quick Start Commands

Local Development 

# Start all services
docker-compose up -d

# Start backend
cd backend
pip install -r requirements.txt
uvicorn backend.api.main:app --reload

# Start frontend
cd frontend
npm install
npm run dev

Deploy to Azure 

# Push to main branch to trigger deployment
git push origin main

# Or deploy manually
az deployment group create \
  --resource-group engram-rg \
  --template-file infra/main.bicep \
  --parameters postgresPassword='...' \
               adminObjectId='...' \
               azureAiKey='...'

✅ Memory persists across conversations
✅ Workflows handle errors gracefully
✅ Deployment succeeds in Azure
✅ Monitoring shows healthy metrics