Programa del Curso

⚔️ Level 1: The Discovery Dungeon – Secrets of Requirements

Mission: Use LLMs (ChatGPT) to extract structured requirements from vague input.
Key Activities:

  • Interpret ambiguous product ideas or feature requests
  • Use AI to:
    • Generate user stories and acceptance criteria
    • Suggest personas and scenarios
    • Generate visual artifacts (e.g., simple diagrams with Mermaid or draw.io)
      Outcome: Structured backlog of user stories + initial domain model/visuals

 


🔥 Level 2: The Design Forge – Architect’s Scroll

Mission: Use AI to create and validate architecture plans.
Key Activities:

  • Use AI to:
    • Propose architectural style (monolith, microservices, serverless)
    • Generate high-level component and interaction diagrams
    • Scaffold class/module structures
  • Challenge each other's choices through peer design reviews
    Outcome: Validated architecture + code skeleton

 


🧙‍♂️ Level 3: The Code Arena – Codex Gauntlet

Mission: Use AI copilots to implement features and improve code.
Key Activities:

  • Use GitHub Copilot or ChatGPT to implement functionality
  • Refactor AI-generated code for:
    • Performance
    • Security
    • Maintainability
  • Inject “code smells” and run peer clean-up challenges
    Outcome: Functional, refactored, AI-generated codebase

 


🐛 Level 4: The Bug Swamp – Test the Darkness

Mission: Generate and improve tests with AI, then find bugs in others’ code.
Key Activities:

  • Use AI to generate:
    • Unit tests
    • Integration tests
    • Edge case simulations
  • Exchange buggy code with another team for AI-assisted debugging
    Outcome: Test suite + bug report + bug fixes

 

⚙️ Level 5: The Pipeline Portals – Automaton Gate

Mission: Set up smart CI/CD pipelines with AI assistance.
Key Activities:

  • Use AI to:
    • Define workflows (e.g., GitHub Actions)
    • Automate build, test, and deploy steps
    • Suggest anomaly detection/rollback policies
      Outcome: AI-assisted, working CI/CD pipeline script or flow

 


🏰 Level 6: The Monitoring Citadel – Watchtower of Logs

Mission: Analyze logs and use ML to detect anomalies and simulate recovery.
Key Activities:

  • Analyze pre-populated or generated logs
  • Use AI to:
    • Identify anomalies or error trends
    • Suggest automated responses (e.g., self-healing scripts, alerts)
    • 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 everything learned to build a working SDLC loop for a mini-project.
Key Activities:

  • Select a team mini-project (e.g., bug tracker, chatbot, microservice)
  • Apply AI at each SDLC phase:
    • Requirements, Design, Code, Test, Deploy, Monitor
  • Present outcomes in a short team demo

Peer voting or judging for most effective AI-powered pipeline
Outcome: End-to-end AI-enhanced SDLC implementation + team showcase

 

By the end of this workshop, participants will be able to:

  • Apply generative AI tools to extract and structure software requirements
  • Generate architectural diagrams and validate design choices using AI
  • Use AI copilots to implement and refactor production-grade code
  • Automate test generation and perform AI-assisted debugging
  • Design intelligent CI/CD pipelines that detect and react to anomalies
  • Analyze logs with AI/ML tools to identify risks and simulate self-healing
  • Demonstrate a fully AI-enhanced SDLC through a mini team project

 

Requerimientos

Audience: Desarrolladores de software, probadores, arquitectos, ingenieros DevOps, propietarios de productos

Los participantes deben tener:

  • Un entendimiento práctico del Ciclo de Vida del Desarrollo de Software (SDLC)
  • Experiencia práctica en al menos un lenguaje de programación (por ejemplo, Python, Java, JavaScript, C#, etc.)
  • Familiaridad con:
    • Escribir y leer historias de usuario o requisitos
    • Principios básicos de diseño de software
    • Control de versiones (por ejemplo, Git)
    • Escribir y ejecutar pruebas unitarias
    • Ejecutar o interpretar pipelines CI/CD

💡 Este es un taller intermedio a avanzado. Es ideal para profesionales que ya son parte de equipos de entrega de software (desarrolladores, probadores, ingenieros DevOps, arquitectos, propietarios de productos).

 7 Horas

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