Student Database Management with AI Multi-Agents

AI Multi-Agent SDLC System (Free-Tier Implementation) for student table in the database

Objective

Design and implement a small-scale, free-tier proof of concept that demonstrates how a multi-agent AI system can execute the full software development lifecycle (SDLC).

The system will use a simple Student Records use case and prioritize ease of use. From a fresh repository, it should be possible to:

Set up the system with minimal configuration
Seed sample data
Observe agents collaborating end-to-end without manual intervention
System Overview

This solution automates the SDLC using specialized AI agents, each responsible for a distinct phase:

Requirement Agent
Converts a user prompt into structured requirements
JIRA Agent
Creates project structure, including epics and user stories
Developer Agent
Generates application code, infrastructure definitions, and deployable artifacts
Test Agent
Creates and executes automated tests
Progress Agent
Updates JIRA ticket status based on workflow events
DevOps Agent
Handles deployment, monitoring, and alerting
Technology Stack (Free Tier)
Category Tool/Service
LLM OpenAI (free), Claude (free), or local models
Orchestration Python with LangChain (optional)
Source Control GitHub (free)
Project Management Jira (free tier, up to 10 users)
CI/CD GitHub Actions
Database AWS RDS MySQL (free tier)
Hosting AWS Amplify (free tier)
Testing Playwright (free)
Monitoring AWS CloudWatch (free tier)
End-to-End Workflow
User Prompt
↓
Requirement Agent
↓
JIRA Agent
↓
Developer Agent
↓
GitHub Repository + Pull Request
↓
Test Agent (Playwright)
↓
DevOps Agent (Deploy + Monitor)
↓
Progress Agent (Update JIRA)
Pull Request Workflow Automation
Agent creates a feature branch
Code is generated and pushed
Pull request is opened
AWS Amplify automatically deploys a preview
Event-Based Transitions
Event Action
PR Created Move ticket → "In Progress"
Tests Passed Move ticket → "QA"
Deploy Success Move ticket → "Done"
Deliverables
GitHub Repository
Clean, well-commented code
One-command setup script for quick initialization
README Documentation
Explanation of each agent’s role
Instructions to extend or customize agents
Description of SDLC orchestration flow
Demonstration
Short screen recording or GIF
Shows student record import and automated analytical report generation
Scalability Notes
Brief outline of how to evolve beyond free-tier constraints
Suggested improvements for production-grade systems
Acceptance Criteria
The system must remain simple and easy to run
All agents should work together in a cohesive, automated flow
Minimal manual configuration required
Clear demonstration of multi-agent orchestration across the SDLC