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Workshop Übersicht

Module 1: The Revolution in Code – Fundamentals & Motivation (approx. 10%)

  • 1.1. Motivation: Why GenAI is Fundamentally Changing Software Development
  • 1.2. What is Generative AI? An Intuitive Explanation for Developers (LLMs, Transformers)
  • 1.3. The New Core Skill: An Introduction to Prompt Engineering

Module 2: AI as a Co-Pilot – Tools for the Daily Developer Workflow (approx. 30%)

  • 2.1. General-Purpose Tools in Action:
    • GitHub Copilot: Code Completion, Test Generation, Code Explanation
    • ChatGPT/Gemini & Co.: Debugging, Refactoring, Boilerplate Code
    • Cursor & Co.: AI-Native IDEs and Their Advantages
  • 2.2. Specialized Tools in the SDLC:
    • Tools for Code Analysis, Security, and Automated Testing
  • 2.3. The AI-Optimized Repository: Best Practices for Humans & Machines
    • Code Quality: Descriptive Names, SRP, Type Hinting
    • Structure & Documentation: The Role of README, /docs, CONTRIBUTING.md
    • Interactive Element: Live Refactoring of an "AI-unfriendly" Code Example

Module 3: From User to Architect – GenAI in Custom Applications (approx. 45%)

  • 3.1. Level 1: The Fundamentals of LLM APIs
    • Overview: OpenAI API, Google AI Platform, etc.
    • Live Coding: A Simple Application with an LLM API Call (e.g., in Python)
  • 3.2. Level 2: Building Robust and Fact-Based Systems
    • The Problem: Hallucinations and Lack of Domain Knowledge
    • The Solution: The "Retrieval-Augmented Generation" (RAG) Architectural Pattern
    • The "Ground Truth": Knowledge Graphs & Ontologies as an External Brain
    • The Process: How an LLM Learns to Query Graph Databases (Graph RAG)
    • Live Demo: Comparing a query to a standard LLM vs. a system with a Knowledge Graph

Module 4: Responsibility & Outlook (approx. 15%)

  • 4.1. Responsible AI: Ethics, Security, and Limitations
    • Handling Hallucinations and Bias
    • Data Privacy and Copyright for AI-Generated Code
  • 4.2. The Future of Software Development with AI
    • Outlook: AI Agents and the Evolution of the Developer Profession
  • 4.3. Open Q&A & Next Steps

Workshop Journey Map 🗺️

journey
    title Your AI-Powered Developer Journey
    section Module 1 - Fundamentals
      Understanding GenAI: 5: You
      Learning Prompt Engineering: 4: You
      Mind Blown: 5: You
    section Module 2 - Daily Tools
      Using Copilot: 5: You, AI
      Exploring AI IDEs: 4: You, AI
      Refactoring Code: 5: You, AI
    section Module 3 - Custom Apps
      First API Call: 3: You, AI
      Building RAG System: 4: You, AI
      Graph RAG Magic: 5: You, AI
    section Module 4 - Going Pro
      Understanding Ethics: 4: You
      Ready for Future: 5: You

Workshop Architecture Overview

flowchart TB
    Start([👋 Welcome!]) --> M1

    subgraph M1["📚 Module 1: The Revolution (10%)"]
        M1A[Why GenAI Matters]
        M1B[How LLMs Work]
        M1C[Prompt Engineering]
    end

    subgraph M2["🛠️ Module 2: Daily Tools (30%)"]
        M2A[Copilot & ChatGPT]
        M2B[Specialized SDLC Tools]
        M2C[AI-Optimized Repos]
    end

    subgraph M3["🏗️ Module 3: Custom Apps (45%)"]
        M3A[LLM APIs 101]
        M3B[RAG Systems]
        M3C[Knowledge Graphs]
    end

    subgraph M4["🎯 Module 4: Future (15%)"]
        M4A[Responsible AI]
        M4B[What's Next?]
        M4C[Q&A]
    end

    M1 --> M2
    M2 --> M3
    M3 --> M4
    M4 --> End([🚀 You're an AI-Powered
Developer Now!])

    style M1 fill:#e1f5ff
    style M2 fill:#fff4e1
    style M3 fill:#ffe1f5
    style M4 fill:#e1ffe1
    style Start fill:#ffd700
    style End fill:#90ee90