Event 2

Event 2 :: Internship Report

Event Report “AI-Driven Development Life Cycle: Reimagining Software Engineering”

Purpose of the Event

Exploring AI-Driven Development using Amazon Q Developer and Kiro to revolutionize software engineering practices and development workflows.

Speakers List

Instructors

  • Toan Huynh - AI-Driven Development Life Cycle & Amazon Q Developer Expert
  • My Nguyen - Kiro Platform Specialist

Coordinators

  • Diem My - Event Coordinator
  • Dai Truong - Technical Coordinator
  • Dinh Nguyen - Workshop Coordinator

Key Highlights

Session Schedule

  • 2:00 PM - 2:15 PM: Welcome & Introduction
  • 2:15 PM - 3:30 PM: AI-Driven Development Life Cycle overview and Amazon Q Developer demonstration
  • 3:30 PM - 3:45 PM: Networking Break
  • 3:45 PM - 4:30 PM: Kiro platform demonstration and hands-on session

AI-Driven Development Lifecycle

Comprehensive overview of how AI transforms traditional software development processes, from requirements gathering to deployment and maintenance.

Amazon Q Developer Integration

Hands-on demonstration of Amazon Q Developer’s capabilities in code generation, debugging, testing, and documentation automation.

Kiro Platform Architecture

Exploration of Kiro’s AI-powered development environment and its integration with existing development workflows.

Development Velocity Optimization

Techniques for accelerating development cycles using AI-assisted coding, automated testing, and intelligent code review processes.

Automated Code Generation

Practical examples of AI-generated code snippets, unit tests, and documentation using both Amazon Q Developer and Kiro platforms.

Lessons Learned

AI Integration Strategy

  • Start with pilot projects to validate AI tool effectiveness
  • Establish coding standards for AI-generated code
  • Implement proper review processes for AI-assisted development

Technical Implementation

  • Amazon Q Developer reduces coding time by 35-50%
  • Kiro platform enhances code quality through intelligent suggestions
  • AI tools require proper training data and context for optimal performance

Development Workflow Enhancement

  • Seamless integration with existing IDEs and CI/CD pipelines
  • Real-time code analysis and optimization recommendations
  • Automated documentation generation improves project maintainability

Practical Applications

  • Implementing Amazon Q Developer in VS Code and IntelliJ environments
  • Setting up Kiro platform for team collaboration and code review
  • Creating AI-assisted testing frameworks for automated quality assurance
  • Developing intelligent code completion and refactoring workflows

Personal Experience & Reflections

The workshop provided hands-on experience with cutting-edge AI development tools. The live demonstrations of Amazon Q Developer’s code generation capabilities were particularly impressive, showing real-time solutions to complex programming challenges. Kiro’s collaborative features demonstrated how AI can enhance team productivity while maintaining code quality standards.

Event Photos

AI-Driven Development Workshop - Welcome Session Welcome session and introduction to AI-Driven Development

Amazon Q Developer Demonstration Toan Huynh demonstrating Amazon Q Developer capabilities

Kiro Platform Workshop My Nguyen presenting Kiro platform features

Hands-on Coding Session Participants engaging in hands-on AI-assisted coding exercises