Course Outline
Level 1: The Discovery Dungeon – Secrets of Requirements
Mission: Utilize Language Learning Models (LLMs) such as ChatGPT to extract structured requirements from ambiguous input.
Key Activities:
- Interpret vague product ideas or feature requests
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Use AI to:
- Generate user stories and acceptance criteria
- Suggest personas and scenarios
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Create visual artifacts (e.g., simple diagrams with Mermaid or draw.io)
Outcome: Structured backlog of user stories and initial domain model/visuals
Level 2: The Design Forge – Architect’s Scroll
Mission: Leverage AI to create and validate architecture plans.
Key Activities:
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Use AI to:
- Propose architectural styles (monolithic, microservices, serverless)
- Generate high-level component and interaction diagrams
- Scaffold class/module structures
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Conduct peer design reviews to challenge each other's choices
Outcome: Validated architecture and code skeleton
Level 3: The Code Arena – Codex Gauntlet
Mission: Utilize AI copilots to implement features and enhance code quality.
Key Activities:
- Use GitHub Copilot or ChatGPT to implement functionality
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Refactor AI-generated code for:
- Performance
- Security
- Maintainability
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Introduce "code smells" and conduct peer clean-up challenges
Outcome: Functional, refactored, AI-generated codebase
Level 4: The Bug Swamp – Test the Darkness
Mission: Generate and enhance tests with AI, then identify bugs in others’ code.
Key Activities:
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Use AI to generate:
- Unit tests
- Integration tests
- Edge case simulations
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Exchange buggy code with another team for AI-assisted debugging
Outcome: Test suite, bug report, and bug fixes
Level 5: The Pipeline Portals – Automaton Gate
Mission: Set up intelligent CI/CD pipelines with AI assistance.
Key Activities:
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Use AI to:
- Define workflows (e.g., GitHub Actions)
- Automate build, test, and deployment steps
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Suggest anomaly detection and rollback policies
Outcome: AI-assisted, functional CI/CD pipeline script or flow
Level 6: The Monitoring Citadel – Watchtower of Logs
Mission: Analyze logs and use machine learning to detect anomalies and simulate recovery.
Key Activities:
- Analyze pre-populated or generated logs
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Use AI to:
- Identify anomalies or error trends
- Suggest automated responses (e.g., self-healing scripts, alerts)
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Create dashboards or visual summaries
Outcome: Monitoring plan or simulated intelligent alerting mechanism
Final Level: The Hero’s Arena – Build the Ultimate AI-Supported SDLC
Mission: Teams apply all learned skills to build a functional SDLC loop for a mini-project.
Key Activities:
- Select a team mini-project (e.g., bug tracker, chatbot, microservice)
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Apply AI at each SDLC phase:
- Requirements, Design, Code, Test, Deploy, Monitor
- Present outcomes in a short team demonstration
Peer voting or judging for the most effective AI-powered pipeline
Outcome: End-to-end AI-enhanced SDLC implementation and team showcase
By the end of this workshop, participants will be able to:
- Apply generative AI tools to extract and structure software requirements for government projects
- Generate architectural diagrams and validate design choices using AI for government applications
- Use AI copilots to implement and refactor production-grade code for government systems
- Automate test generation and perform AI-assisted debugging for government software development
- Design intelligent CI/CD pipelines that detect and react to anomalies in government projects
- Analyze logs with AI/ML tools to identify risks and simulate self-healing mechanisms for government systems
- Demonstrate a fully AI-enhanced SDLC through a mini team project for government use cases
Requirements
Audience: Software developers, testers, architects, DevOps engineers, and product owners for government projects
Participants should have:
- A practical understanding of the Software Development Lifecycle (SDLC)
- Hands-on experience with at least one programming language (such as Python, Java, JavaScript, C#, etc.)
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Knowledge in:
- Crafting and interpreting user stories or requirements
- Fundamental software design principles
- Version control systems (e.g., Git)
- Developing and running unit tests
- Managing or analyzing CI/CD pipelines
This workshop is designed for intermediate to advanced professionals who are currently part of software delivery teams, including developers, testers, DevOps engineers, architects, and product owners for government initiatives.
Testimonials (1)
Lecturer's knowledge in advanced usage of copilot & Sufficient and efficient practical session
