/AI-assisted SDLC (SMW Project)

Overview

The SMW Project is a strategic initiative to transform the traditional Software Development Lifecycle (SDLC) by integrating AI-assisted tools. As the Technical Lead, I defined the AI adoption framework, aiming to improve delivery speed, estimation accuracy, and code quality across the organization.

1. Key Innovation: Full-Cycle Agentic AI

We moved beyond simple code completion to a comprehensive Full-Cycle Agentic AI workflow that handles:

1. Requirement Gathering: Generating SRS documents from raw inputs.
2. Data Modeling: Automating backend schema generation.
3. Frontend Generation: Producing production-ready Next.js code.
4. Quality Assurance: Autonomously generating and executing test cases.
   
   

2. Tooling Ecosystem

• Windsurf: For IDE-integrated coding assistance.
• Antigravity: For autonomous agentic tasks and complex refactoring.
• GitHub Copilot: For rapid code suggestion and boilerplate generation.
  
  

3. Workflow Integration

• Defined operating models for AI-aided estimation and SRS documentation.
• Established governance and quality control for AI-generated outputs.
• Built custom Agent Skills to adapt business logic specific to our domain.
  
  

4. Impact

"We didn't just write code faster; we thought about problems differently."

• +30% Productivity: Verified improvement across pilot teams.
• Reduced Effort: Significant reduction in technical documentation and estimation time.
• Consistency: Improved onboarding speed for new engineers via standardized AI prompts/contexts.
  
  

5. Technology Stack

• AI Tools: Windsurf, Antigravity, GitHub Copilot
• Infrastructure: AKS, Azure DevOps, Airbase