Milestone Plan for LLM Application Development

This milestone plan is structured to guide the development of a full-stack LLM application from ideation to full public launch, focusing on core functionality, testing, and iterative feedback.

Summary Table of Milestones

Milestone	Goal	Key Deliverables
1. Discovery and Planning	Define scope and architecture	Requirements doc, architecture diagram
2. Core Infrastructure Setup	Set up essential infrastructure	Storage, databases, task queue
3. Prototype Completion	Develop basic LLM functionality	Basic functional prototype
4. Core Features Developed	Add document processing, caching, search	Feature-complete system
5. Alpha Release	Internal testing and feedback	Stable alpha version
6. Beta Release	Limited user testing and feedback	Beta version, user feedback
7. Performance Optimization	Optimize performance and security	Optimized, secure application
8. Public Launch Prep	Finalize for public release	Launch-ready product, documentation
9. Public Launch	Release to all users	Publicly accessible application
10. Post-Launch Improvements	Minor enhancements and bug fixes	Improved version with fixes
11. Scaling and Maintenance	Ensure scalability and plan future growth	Scalable, maintained application

Milestone 1: Discovery and Planning

• Goal: Define project requirements, key objectives, and architecture.
• Details:
  • Conduct research on user needs, LLM capabilities, and expected system load.
  • Define project scope, including the primary features and user stories.
  • Outline initial system architecture (frontend, backend, cache, databases).
  • Set up project repository, CI/CD pipelines, and preliminary development environment.
• Deliverables: Requirements document, architecture diagram, project timeline, and initial codebase setup.

Milestone 2: Core Infrastructure Setup

• Goal: Establish core infrastructure, including storage, databases, and background processing.
• Details:
  • Set up and configure Document Storage (AWS S3 or MinIO), Vector Database (Qdrant), and Relational Database (SQL Server).
  • Configure the background task queue (Celery on AWS Step Functions or similar) for asynchronous tasks like embedding documents.
  • Establish serverless or managed services for storage and databases to reduce costs and improve scalability.
• Deliverables: Functional infrastructure with integration tests confirming connectivity and data storage.

Milestone 3: Prototype Completion

• Goal: Develop a functional prototype with basic LLM and embedding model integration.
• Details:
  • Integrate the LLM API (e.g., OpenAI API) and embedding model (GPT or PhoBERT) for basic query processing.
  • Build a simple frontend UI (NextJS) for users to submit queries and receive responses.
  • Implement a basic API server (FastAPI on AWS Lambda) with reverse proxy (Nginx).
  • Test end-to-end flow from user input to LLM response and back.
• Deliverables: Basic functional prototype enabling user queries and AI-generated responses.

Milestone 4: Core Features Developed

• Goal: Implement essential features like document processing, caching, and vector search.
• Details:
  • Implement background tasks for document embedding and storage in the Vector Database.
  • Add caching (Redis) for frequently accessed queries to improve response times.
  • Build vector-based search functionality for finding similar documents based on embeddings.
  • Refine UI and backend to support these features with scalability in mind.
• Deliverables: Feature-complete application with document embedding, caching, and search.

Milestone 5: Alpha Release (Internal Testing)

• Goal: Launch an internal version for testing core functionalities and performance.
• Details:
  • Deploy to a test environment with restricted access for internal team members.
  • Conduct usability testing for UI, API reliability, and system stability.
  • Run initial performance tests to check if response times and throughput meet expectations.
  • Collect internal feedback to refine UX and resolve major issues.
• Deliverables: Stable alpha version with feedback from internal testing and an updated backlog.

Milestone 6: Beta Release (Limited User Testing)

• Goal: Release a beta version for a limited audience to gather real user feedback.
• Details:
  • Deploy to a production-like environment with limited access for select users.
  • Implement logging and monitoring to capture usage patterns, errors, and bottlenecks.
  • Integrate a feedback system to gather insights on user experience and response accuracy.
• Deliverables: Beta version with logging and analytics, and documented user feedback.

Milestone 7: Performance and Security Optimization

• Goal: Optimize the system for speed, efficiency, and security.
• Details:
  • Optimize caching for frequently accessed responses.
  • Review and optimize vector database queries for faster results.
  • Conduct a security audit focused on data protection, authentication, and permissions.
  • Run load testing to confirm system scalability.
• Deliverables: Performance-optimized, secure application ready for a wider release, with testing reports.

Milestone 8: Public Launch Preparation

• Goal: Finalize all details for a successful public release.
• Details:
  • Complete final testing, including UAT (User Acceptance Testing), to ensure functional readiness.
  • Finalize documentation for users and developers, including API docs and setup guides.
  • Prepare marketing and user onboarding materials, if needed.
  • Establish support channels for post-launch user queries.
• Deliverables: Launch-ready product, comprehensive documentation, and user onboarding resources.

Milestone 9: Version 1.0 - Public Launch

• Goal: Release the application to all intended users.
• Details:
  • Officially launch the application with monitoring for critical issues.
  • Monitor user activity and metrics for the first 24-48 hours to ensure stability.
  • Provide support for major issues with a rapid response plan.
• Deliverables: Full public release with active user support and monitoring.

Milestone 10: Post-Launch Improvements (Version 1.1)

• Goal: Address post-launch feedback and add minor improvements.
• Details:
  • Collect and analyze public feedback to identify improvement areas.
  • Resolve post-launch issues or bugs based on user reports and monitoring.
  • Implement minor feature enhancements or optimizations.
• Deliverables: Improved version with bug fixes, optimizations, and minor enhancements.

Milestone 11: Scaling and Maintenance (Ongoing)

• Goal: Ensure the application is scalable and well-maintained.
• Details:
  • Review performance under varying loads to identify scaling needs.
  • Set up maintenance plans for databases, storage, and serverless resources to optimize costs.
  • Prioritize future feature requests for competitive advantage.
• Deliverables: Scalable, well-maintained application with a roadmap for future updates.

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This plan provides a structured path from initial development to launch and ongoing maintenance, helping ensure that each stage is well-prepared and aligned with the project’s goals.