Never say refactoring is impossible

Harald Nezbeda

Prompt Engineering Hands-on

This hands-on workshop teaches prompt engineering by working directly with Large Language Models.

• AI Models
• Large Language Models (LLMs)
• Prompt Engineering
• Python

Thomas Fricke

Teaching Kubernetes Security in your Cluster

The workshop shows how to teach hands on Kubernetes trainings lessons in your own cluster environment with Jupyter notebooks Starting with the basics we extend the examples…

• Containers
• DevSecOps
• Security

Stan Bühne

The Decisions Developers Make Without Noticing – And How to Make Them Better

Developers make critical decisions long before they write code — often without consciously noticing them.

• AI Coding Assistants
• Developer Experience (DevEx)
• Productivity
• Soft Skills

Robert Jeutter

Rust on Robots: Hands-on Embedded Rust on STM32

Rust is fast, modern, and great at catching typical embedded mistakes early—exactly what you want on real robots.

• Embedded Systems
• Reliability
• Robotics
• Rust

Jannis Eickenroth +2 more

From COBOL to Java: How Developers Transition 60 Years of Legacy into Modern Java Services

COBOL systems written decades ago still power some of the most critical parts of modern banking.

• AI Coding Assistants
• COBOL
• Microservices

Roland Odorfer +1 more

Agents of Football: Build AI Agents That Compete in Live Football Matches

Meet your hackathon organizers and technical influencer judges, then dive into the Football for Good theme that will drive 3 days of building.

• AI Models
• AWS
• Agents
• Agentic AI

Erhardt Wunderlich

What do we need to deliver high quality products?

Quality assurance is an issue for every development step and for each individual team member.

• Agile
• Automation Testing
• Best Practices
• CI/CD

Dr. Damir Dobric

Deep Dive: Mastering Agents, MCP and other hypes

Building intelligent applications and integrating AI into modern software is an exciting but complex task.

• AI Coding Assistants
• Agents
• Agentic AI
• Azure

Alberts Jekabsons

From messy addresses to production-ready data: Build a location enrichment pipeline on AWS with HERE

Location data often works in development and quietly fails in production.

• APIs
• AWS
• AWS Lambda

Satej Sahu

Beyond the Thor’s Hammer: Pragmatic Agentic AI with Caching, Reuse, and Cost Guardrails

Agentic AI has become the default “big hammer”: throw more agents at the workflow, add more tools, loop until it works.

• AI Models
• Agents
• Agentic AI
• Caching

Sophie-Theresa Kleinke +2 more

Engineering Customer Journey Analytics at Scale: Lessons from Germany's Largest Banking Platform

Customer experience is only as good as your ability to understand what happens across complex digital processes.

• Analytics
• Data
• Data Pipelines
• Lakehouse

Carl Fagerlin +1 more

Trust code you didn't write: From code review to confidence

Agents let us produce code faster than developers can realistically review, understand, and reason about, sometimes leading to unintentional side effects and bugs.

• AppSec
• Agents
• Agentic AI
• Secure Coding

Dagmar de Haan

Getting started with Hexagonal Architecture

You’ve probably heard of hexagonal architecture — an approach that promises to clearly separate business logic from technical concerns, improve testability, and allow for flexib…

• Legacy
• Software Architecture

Salih Guler

Build an agentic full-stack tabletop game master application

I've run AI-powered tabletop game master sessions at conferences where the audience became the adventuring party and an AI ran the game.

• AI Models
• AWS
• Agents
• Agentic AI

Nikos Delis

MCP is all you need to make an AI-agent consume your RESTful API

Turn any existing REST API into an AI-native backend—no frontend required.

• AI Models
• .NET
• VS Code

Tamas Piros

Build a Production-Ready AI Agent in 90 Minutes

AI agent demos are everywhere.

• AI Models
• Agentic AI
• TypeScript

Alfonso Graziano

The Art and Science behind evaluating AI Agents at scale

Evaluating AI Agent is a mix of science and art.

• AI Coding Assistants
• AI Models
• Retrieval-Augmented Generation (RAG)

Linda Stauffenberg +1 more

How to Pitch Innovation to Your CEO

Many innovations never make it to implementation.

• Innovation
• People & Culture
• Product Strategy
• UI/UX

Marco Sussitz

How does a Java agent work? Building a Java agent from scratch.

Java agents let you modify application behavior at runtime without changing source code.

• Java
• JVM
• Observability

Stas Lebedenko

Adopting GitOps for microservices delivery via Argo CD

This workshop is dedicated to GitOps principles adoption with Argo CD for deploying your microservices to Kubernetes.

• ArgoCD
• DevOps
• GitOps

Josh Hobson

Build a data-intensive dashboard (that actually works)

In this hands-on workshop, you'll build a data-intensive dashboard using AI-assisted development, and stress-test it against real requirements: large datasets, cross-filtering,…

• Agentic AI
• Business Intelligence
• JavaScript

Salih Guler

Ideate & Strategize: Defining Your Football for Good Prototype

Now that you've built AI agents hands-on and formed your team, it's time to decide what you'll create.

• AI Models
• AWS
• Agents
• Agentic AI

Rabieh Fashwall

Zero to Binary: Building a Production-Ready AI Agent in Go

Python is excellent for experimentation, but when it’s time to ship AI agents to production, you need the performance, concurrency, and type safety of Go.

• AI Coding Assistants
• AI Models
• Agentic AI

David vonThenen

From Vector Search to Better Understanding: How Hybrid RAG Improves Answers, Not Just Matches

Retrieval-Augmented Generation is everywhere, and most teams start with vector search when building out these agents.

• Embeddings
• Large Language Models (LLMs)
• Retrieval-Augmented Generation (RAG)
• Small Language Models (SLMs)

Abdelfettah Sghiouar +1 more

Build a Multi-Agent Marathon Planner with ADK and A2A

In this codelab, you build a multi-agent system where three specialized AI agents collaborate to plan a city marathon.

• Multi-Agent Systems

Antonio Rueda-Toicen

Teaching AI to Code in Every Language with NVIDIA NeMo

“Teaching AI to Code in Every Language with NVIDIA NeMo” is a hands-on training lab for machine learning practitioners, data scientists, and developers who want to build state-o…

• AI Models

Patrick Feige +1 more

Defending the Modern Supply Chain: Hands-On Vulnerability Remediation

Software supply chains grow more complex every day, bringing new risks from open-source dependencies.

• AppSec
• Cloud Security
• Compliance
• DevOps

Erica Weistrand

Hands-on AMQP with LavinMQ: Decoupling Services with Message Queues

Most services still talk to each other over HTTP, blocking on each call and tightly coupling availability, deployment, and scaling.

• APIs
• Microservices
• Open Source
• Software Architecture

Ramona Schwering

You shall (not) pass!? An Introduction to Testing authenftication

Like a door to a house or a shallow bridge from one cliff to the other: Some parts of your application are crucial and any damage or untrustworthy guide in those areas can have…

• AppSec
• Testing

Przemysław Ładyński

Building Modern Distributed Systems using Less AI Tokens

Modern distributed systems are often hard to understand - not only for developers, but also for AI coding assistants.

• AI Coding Assistants
• AI Standards
• APIs
• C#

Gabriel Kuettel

Give your agent a wallet: Build an AI agent with stablecoin payment capabilities

AI agents can plan and execute tasks, but to be truly autonomous, they need economic agency.

• APIs
• Agents
• Agentic AI
• Web3

Daniel Bodky

Building a Better Tomorrow: Tips and Tricks for Docker Builds

Container are a fundamental building block of DevOps operations, yet building them efficiently and securely can be a burden: Often developers don’t know about the platforms’ sec…

• Containers
• DevSecOps
• Docker

Leandro Gomes da Silva +1 more

HR Workshop - Vibe:athon: Where HR Goes to Build 1/4

If you can describe what you want, you can build it.

Tugdual Grall +1 more

GitHub Copilot: From Zero to Hero

AI isn't just auto-completing lines of code anymore—it’s evolutionizing how we architect, build, and ship software.

• AI Coding Assistants
• Copilot
• DevOps
• GitHub

Marina Coelho +1 more

Building AI apps with the Google ecosystem

The way we build software has changed.

• AGI (Artificial General Intelligence)
• Agentic AI

Anshul Jindal +1 more

Accelerating AI Inference at Scale: A Deep Dive Into NVIDIA Dynamo on Kubernetes

As foundation models move toward deeper test-time computation, inference becomes the dominant scaling constraint.

• AI Models
• Agentic AI
• Distributed Systems
• Docker

Rafael Levi

The Bright Data Build-Off

AI writes the UI.

• AI Models
• Agents
• Agentic AI
• Automation

Panley Cooze

Building & scaling custom serverless AI

When building custom AI solutions, you often have to rent a GPU 24/7.

• AI Models
• Best Practices
• Containers
• Generative AI (GenAI)

Jovana Dunisijevic

The best SDLC is the one you build yourself: Why orchestration changes everything

Industry research shows AI productivity gains have plateaued at 10–15% — because today's tools only optimize the 20% of a developer's day spent writing code.

• AI Coding Assistants
• AI Models
• Agents
• Agentic AI

Leandro Gomes da Silva +1 more

HR Workshop - Vibe:athon: Where HR Goes to Build 2/4

If you can describe what you want, you can build it.

Mara Kiefer

Level Up Your Automation with GitHub Agentic Workflows

In this hands-on workshop, you'll build a repository assistant that can understand your project, identify high-impact work, investigate issues, propose fixes, and help keep main…

• Automation
• DevOps
• GitHub Actions
• Open Source

Tom Wheeler

Developing Crash-Proof Java Applications

Crashes and failures are inevitable, but they don’t have to be disruptive.

• Distributed Systems
• Java
• Open Source
• Reliability

Amit Kushwaha

Faster Together: Train and Deploy a Speculative Decoding Model for Low-Latency LLM Inference

Dive deep into theory and practice of low-latency inference by deploying NVIDIA TensorRT-LLM with advanced speculative decoding techniques.

• AI Models
• Tokenomics

Matthias Kordt +1 more

Managing Sovereign AI Infrastructure: MLOps and LLMOps in Highly Regulated Banking IT

AI only becomes strategically relevant when it can be operated reliably, securely, and sustainably.

• AI Models
• AI Standards
• Automation
• Infrastructure

Predrag Radenkovic +1 more

Spec-Driven Development with Agentic Skills

We'll dive into spec-driven development on the example of integrations development.

• Agentic AI
• Claude
• Integration
• Integration Testing

Jenny Speelman

Ducks, Sensors & Agents: Hands-On Edge AI with Arduino UNO Q

By the end of this workshop, attendees will be able to: Part 1 – Computer Vision: 1.

• AI Coding Assistants
• Agentic AI
• Arduino
• Edge AI

Joseph Katsioloudes

Shall we play a Game? LLM Security in Practice

Artificial Intelligence (AI) is no longer a futuristic concept.

• Secure Coding
• Security

Stefan Ganß

HR Workshop - The Human Advantage: Storytelling in the Age of AI

AI can generate code, emails, product descriptions, and pitch decks in seconds.

Evgenij Renke

AI That Acts: Orchestrating Agents in Modern Developer Workflows (securely)

AI agents are no longer a concept — they're writing code, opening PRs, and running pipelines.

• AI Models
• Autonomous Systems
• DevSecOps
• GitHub

Javier Cañadillas +1 more

Agents at Scale: Multi-Agent Architecture with A2A Protocol on Agent Runtime and ADK Integration

As AI agents take on more responsibilities, a single agent doing everything becomes hard to maintain, scale, and evolve.

Anshul Jindal

Always-On Autonomous AI Agents: Exploring the OpenClaw Abstraction

As agents evolve from basic conversational interfaces to personal complex task navigators, the primary challenge shifts from writing context strategies to designing robust systems.

• Agents
• Multi-Agent Systems
• Open Source

Xuan Huang · 黄玄

Vibe³ Cross-Platform Apps with Lynx: A TikTok Hackathon

AI is changing how apps are built, but most apps are still built one platform at a time.

• AI Coding Assistants
• Cross-Platform
• CSS
• Generative AI (GenAI)

Krasimir Tsonev

Exploring Server Side Rendering

Server-side rendering (SSR) is back in the spotlight—and React is evolving fast.

• Node.js
• React

Lucía Conde-Moreno +1 more

From Hallucination to Justification: Hands-On Explainability for LLMs

Human beings are biased and often wrong.

• AI Coding Assistants
• AI Models
• Anthropic
• Agents

Mehdi Mohseni

Bridging LLMs and Systems: Practical Automation with MCP Tools and Function Calls

In this session, we’ll look at how a .NET-based solution enables Large Language Models (LLMs) to act as automation engines inside a VR application.

• AI Models
• APIs
• AR/VR/XR
• ASP.NET

Leandro Gomes da Silva +1 more

HR Workshop - Vibe:athon: Where HR Goes to Build 3/4

If you can describe what you want, you can build it.

Julia Kordick

Teaching GitHub Copilot COBOL: A Practical Guide to Agentic AI Legacy Modernization

Everyone talks about modernizing legacy systems.

• AI Models
• Agents
• Agentic AI
• GitHub

Miguel Toscano +1 more

Vibe Coding with Postgres: From Zero to Prod in Your IDE

Vibe coding has revolutionized the speed and way we develop frontends, but it often hits a wall when it reaches the database.

Sergio Perez

Compress, Cut, and Distill: The Latest Gen AI Model Compression Techniques in Practice

This training lab explores the art and engineering of compressing large language models to make them cheaper, faster, and easier to deploy while preserving practical capability.

• AI Models
• Large Language Models (LLMs)

Wekoslav Stefanovski

How to mess up JWT's - a practitioner's guide

JSON Web Tokens are everywhere - you are using a bunch of them right now.

• Infosec
• JavaScript
• Node.js
• Secure Coding

Arnaud Jean

Create Your Own Role-Playing Game with Agentic AI using Strands Agents

Come discover how to code a Game Master that will orchestrate multiple AI agents, each specialized in a particular task.

• AI Coding Assistants
• Agentic AI
• Open Source

Ed Marquez +2 more

Build Agents That Can Pay with x402: From Your Laptop to a Live Network

AI agents are starting to act on their own, but an agent that can't pay for anything is stuck asking a human for a credit card.

• AI Models
• APIs
• Infrastructure
• Open Source

Jorrin Bruns

Let agents buy your API: Build a payment-gated service with x402

The digital economy is shifting from human consumers to autonomous AI agents.

• APIs
• Agents
• Agentic AI
• Web3

Moataz Nabil

GenAI in Testing: Using GitHub Copilot to Accelerate Quality Without Losing Trust

Generative AI is rapidly changing how developers write code—but its impact on testing and quality engineering is often misunderstood.

• Automation Testing
• CI/CD
• Copilot
• Developer Experience (DevEx)

Stefan Ganß

HR Workshop - The Human Advantage: Storytelling in the Age of AI

AI can generate code, emails, product descriptions, and pitch decks in seconds.

Isha Salania +2 more

Building Multi-Agent AI Systems with MAF: From Copilot to Orchestrated Agents

This hands-on workshop focuses on building multi-agent AI systems using Microsoft's Multi-Agent Framework (MAF).

• AI Coding Assistants
• Agents
• Agentic AI
• Azure

Duan Lightfoot

Agents That Own Their Inference: Building Production AI Agents on Dedicated GPUs

Every production agent today is renting its intelligence.

• AI Models
• Agents
• Generative AI (GenAI)
• Infrastructure

Alexander Schwarz +1 more

Generate Synthetic Data for Physical AI with NVIDIA Cosmos World Foundation Models

This hands-on lab introduces roboticists, AI developers, and pipeline engineers to NVIDIA Cosmos world foundation models (WFMs) for synthetic data generation in robot learning p…

• Data Pipelines
• Robotics

Andrew Demczuk

Hack Me, Bro: An Antifragile AI Battle Arena

I run an AI Battle Arena at arena.angel-serv.com.

• AI Coding Assistants
• AI Models
• Anthropic
• APIs

Anni Chen

Build a Multi-Channel AI Agent

Building production AI agents means solving infrastructure problems before writing agent logic.

• Agentic AI
• Large Language Models (LLMs)

Leandro Gomes da Silva +1 more

HR Workshop - Vibe:athon: Where HR Goes to Build 4/4

If you can describe what you want, you can build it.

Marc Teipel

Context > Models: How to make your agents truly intelligent

Strong agents are not only defined by the model they use, but by the context they can access and the systems they can act on.

• AI Coding Assistants
• AI Models
• Agents
• Collaboration