Overview - reza899/AutoSDLC GitHub Wiki

AutoSDLC System Overview

#AutoSDLC #Core #Architecture #Overview

Executive Summary

AutoSDLC revolutionizes software development by creating an autonomous team of AI agents that collaborate to design, implement, test, and deploy software. Built on Claude Code's MCP (Model Context Protocol) capabilities and deep GitHub integration, it transforms how software is created.

Vision

"Transform software development from a manual, error-prone process to an intelligent, self-organizing system where AI agents collaborate seamlessly to deliver high-quality software."

Key Concepts

1. Agent-Based Architecture

Autonomous Agents: Each agent has a specific role and expertise
Collaborative Intelligence: Agents work together, not in isolation
Self-Organizing: Agents coordinate without human intervention

2. Continuous Development

Iterative Process: Small, frequent improvements
Automated Testing: Every change is validated
Continuous Deployment: Automated release pipeline

3. Human-in-the-Loop

Oversight: Humans maintain control over critical decisions
Customization: Agents can be configured and prompted
Monitoring: Real-time visibility into agent activities

System Components

Agent Team

Customer Agent #Agent
- Maintains product vision
- Validates implementations
- Provides requirements clarification
Product Manager Agent #Agent
- Translates requirements
- Manages GitHub issues
- Coordinates development
Coder Agent #Agent
- Implements features
- Writes tests
- Creates pull requests
Code Reviewer Agent #Agent
- Reviews code quality
- Ensures standards
- Suggests improvements
Tester Agent #Agent
- Monitors CI/CD
- Analyzes test results
- Reports issues

Infrastructure Components

MCP Server/Client: Agent communication backbone
GitHub Integration: Version control and workflow
Workflow Engine: Process orchestration
Control Dashboard: Monitoring and configuration

Core Workflows

Feature Development Flow

graph LR
    A[Customer Request] --> B[PM Analysis]
    B --> C[Issue Creation]
    C --> D[Coder Implementation]
    D --> E[Code Review]
    E --> F[Automated Testing]
    F --> G[Deployment]
    G --> H[Customer Validation]

Bug Fix Flow

graph LR
    A[Bug Report] --> B[PM Triage]
    B --> C[Issue Creation]
    C --> D[Coder Fix]
    D --> E[Review & Test]
    E --> F[Deploy Fix]

Benefits

For Development Teams

✅ Increased Velocity: 10x faster feature delivery
✅ Improved Quality: Consistent code standards
✅ Reduced Burnout: Automate repetitive tasks
✅ 24/7 Development: Agents work continuously

For Organizations

✅ Cost Reduction: Lower development costs
✅ Faster Time-to-Market: Rapid iteration
✅ Scalability: Handle multiple projects
✅ Innovation: Focus on creative work

Implementation Philosophy

1. Gradual Adoption

Start with simple workflows and expand gradually. Begin with automated code reviews, then add implementation capabilities.

2. Human Oversight

Maintain checkpoints for critical decisions. Humans approve architectural changes and validate business logic.