How do you turn vague ideas into precise, high-quality AI outputs? This workshop explores best practices in prompt engineering for both text and image generation. We’ll compare different prompting styles, analyze why some prompts fail, and demonstrate optimization techniques such as negative prompting, step-by-step reasoning, and stylistic controls. Attendees will leave with a toolkit of strategies to enhance creativity, accuracy, and efficiency in AI-generated content.

The software development landscape has reached an inflection point. Organizations now face a stark choice: embrace AI integration or risk becoming irrelevant.

AI is no longer optional.

It’s everywhere—from the developer’s toolbelt to the systems and applications we deliver. For technical leaders and decision-makers, the question is no longer whether to adopt AI, but how fast and how smartly you can integrate it to drive real business value and stay competitive. This workshop covers the full range of decisions today’s development leaders face. You’ll explore why organizations that embed AI into their development processes are achieving faster time-to-market, lowering operational costs, differentiating their products—and dramatically improving quality.

As a technical leader, you must understand how tools like GitHub Copilot in Visual Studio/VS Code (and other modern IDEs) are transforming more than just productivity. They are redefining how developers learn, grow, and deliver value. These tools aren’t just about doing more—they’re about doing better. Ignoring them is not just a missed opportunity—it may be the beginning of a slow fade into irrelevance. Even the rise of so-called “vibe coding”—a term no enterprise leader should love—is signaling deep, lasting changes in how software is built. But AI isn’t just in the tools—it’s in the systems we build.

This workshop explores how to integrate AI, especially (but not only) Generative AI and Large Language Models, into your own apps and platforms. Markus will demystify the capabilities of models like OpenAI’s GPT (via OpenAI and Azure AI Foundry), and examine other options—from cloud-based to local models. You’ll also see real-world examples and how-to techniques for building “Better Than ChatGPT” AI into your own software. Not every team wants to build from scratch. Many look to leverage AI through platforms they already use—like Microsoft 365, Power Platform, and Copilot Studio. Markus will walk through how to harness these technologies to amplify what your teams can achieve. Whether you're a CTO shaping AI strategy, a technical director focused on velocity and quality, or a senior developer looking to stay ahead of the curve, this workshop gives you the strategic framework to make the right calls.

Markus will break down high-level concepts and decision-making approaches, while also diving into code to give developers and non-developing leaders alike a clear picture of what AI integration really looks like. You’ll walk away with the insight, urgency, and roadmap needed to reshape your projects for the age of AI.

AI has exploded into the mainstream—and developers are on the front lines. In just two years, we’ve gone from experimenting with chatbots to building production-grade systems powered by OpenAI’s GPT models, Microsoft Copilot, and a wave of other LLM technologies. But while the momentum is undeniable, so are the growing pains. Like with any paradigm shift, the early days are marked by more failures than successes—but those who get it right are seeing massive gains. With the right approach, you can move beyond the hype and deliver transformative solutions with extraordinary ROI.

In this high-impact, insight-packed session, we'll cut through the noise and share real-world lessons from AI development—what actually works, what doesn’t (yet), and where things are going fast. We’ll take you behind the scenes of how we’ve integrated AI into our own applications and tools, with practical takeaways you can apply immediately. You’ll see where ChatGPT excels (yes, even for developers!), how Microsoft Copilot is evolving and what still holds it back, and why some AI promises remain frustratingly just out of reach.

One of the most disruptive shifts has emerged quietly but powerfully: AI-assisted development. In a very short time, we've seen AI tools move beyond autocomplete and code suggestions into something far more powerful. Systems can understand your intent, translate vague prompts into working solutions, and collaborate with you in real time. This is no longer futuristic hype; it's here, and it's already reshaping how software is being built. Developers who learn to think and work in this new mode will be vastly more productive—and far more in demand. Those who don’t risk falling behind faster than they expect.

If you’re a developer wondering “How do I keep up?” or “What do I build next?”—this is your session. Walk away with a clear-eyed view of the AI landscape, a toolkit of proven approaches, and a renewed sense of urgency to level up before your competition does.

AI isn’t coming—it’s already here. Let’s figure out how to thrive in it!

Join us for an immersive exploration of Microsoft Semantic Kernel, a powerful framework for building AI-powered applications. This session will guide you through the practical aspects of developing copilots and other intelligent systems that leverage cutting-edge language models. We'll demonstrate real-world code examples that showcase integration with both cloud-hosted models (GPT, Gemini, Llama, Claude) and locally-hosted Small Language Models like GPT 3o-mini.

Throughout our hands-on journey, you'll discover how to implement automatic function calling, create sophisticated agents and agentic systems, and enhance your applications with Retrieval Augmented Generation (RAG). We'll critically examine when frameworks provide the optimal approach versus situations that call for custom solutions, equipping you with decision-making tools for your own AI development.

By the end of this session, you'll have gained valuable insights into Semantic Kernel's strengths and limitations, mastered the essential steps to begin your own projects, and understood the current feature landscape. We'll conclude with a forward-looking discussion of upcoming developments, ensuring you're prepared to adapt as this technology evolves.

Do you wonder how ChatGPT and other large language models (LLM) work? We’ll walk through a comprehensive example to illustrate the intricate process behind how LLMs like ChatGPT generate answers. Through this session, attendees will gain valuable insights into the underlying mechanisms that enable LLMs to understand and respond to human-generated queries. This session will demystify the complex algorithms and advanced techniques used by LLMs, providing a deeper understanding of their capabilities.

Through a carefully curated example (no code demonstrated), you'll witness firsthand how LLMs analyze and interpret the context, meaning, and nuances of questions, enabling them to provide contextually relevant and accurate responses. This interactive exploration will shed light on the state-of-the-art technology driving LLMs, allowing you to appreciate the incredible depth of their knowledge and reasoning abilities. Whether you are an AI enthusiast, a researcher, or simply curious about the capabilities of LLMs, this webinar promises to be an enlightening and interactive experience. Don't miss this chance to uncover the secrets behind how LLMs transform raw input into insightful and meaningful answers.

The rise of large language models (LLMs) has introduced a new paradigm in software development: Vibe Coding, a term coined by Andrej Karpathy in 2025. This AI-assisted approach allows developers to generate functional code by providing high-level descriptions, shifting their role from manual coding to guiding, testing, and refining AI-generated output. While Vibe Coding accelerates development and reduces cognitive load, it also raises concerns about code quality, maintainability, and security. This presentation will explore how software developers can harness LLMs to boost productivity while maintaining rigorous engineering standards. We will discuss best practices for integrating AI-assisted coding into professional workflows, including effective prompting techniques, validation strategies, and AI-aware code review processes. Attendees will gain insights into balancing efficiency with reliability, ensuring that AI remains a tool for enhancement rather than a shortcut to technical debt. By the end of this session, senior developers will have a framework for using coding assistants like Copilot responsibly, maximizing AI’s benefits while preserving the craftsmanship of software engineering.

This session explores how AI transforms the early stages of greenfield software development, enabling teams to launch projects with greater clarity, speed, and strategic alignment. Attendees will learn how to harness AI tools to manage context, craft effective implementation prompts, and initiate intelligent code generation workflows.

Key Topics:

• Managing development context with AI
• Designing effective implementation prompts
• Executing prompts and interpreting AI responses
• Early-stage architecture and scaffolding with generative models
• AI-assisted planning and modular design strategies

Takeaway: Participants will leave with a practical understanding of how to kickstart greenfield projects using AI, reducing ramp-up time and laying a strong foundation for scalable development.

Building on the first session, Starting the Job, this session dives into how AI supports the implementation of greenfield projects. It focuses on how the effective use of context and prompts, and how they guide AI in writing quality maintainable code quickly. Further emphasis is placed on how code reviews provide essential feedback to refine and improve the utilization of AI in software development.

Key Topics:

• Prompting implementation generation
• Verifying and refining the generated code
• Automated test generation and validation with AI
• Directing AI toward the desired outcome
• Continuous learning and feedback loops in AI tooling

Takeaway: Attendees will gain insights into how AI can help finish the job with precision—ensuring robust, well-tested, and production-ready software while maintaining developer control and creativity.

Artificial intelligence is evolving at an unprecedented pace, reshaping industries, redefining creativity, and raising profound ethical questions. But where is AI truly headed? This talk explores both the near-term advancements and the long-term possibilities, including the rise of Artificial General Intelligence (AGI) and the theoretical potential of superintelligence. We'll examine realistic AI trajectories, their impact on society, and the sci-fi-inspired scenarios that range from utopian coexistence to existential risk. Will AI be humanity’s greatest ally or its downfall? Join us for a deep dive into the future of AI—where cutting-edge technology meets speculative fiction.

Discover how to rapidly design, customize, and deploy image generation pipelines—without writing a single line of code. This session strips away complexity, focusing on intuitive no-code platforms and visual workflow builders that let you drag-and-drop components to create tailored solutions. Learn to configure environments, assemble pipelines using prebuilt diffusion models, and adjust parameters through user-friendly interfaces to generate images for your unique use case—whether marketing visuals, prototyping, or creative experiments.

We’ll demo a streamlined approach to saving pipelines as reusable templates and deploying them as lightweight APIs for instant testing or app integration. Skip the boilerplate: This session is for technical teams who want to bypass coding bottlenecks and focus on speed, iteration, and real-world results. Leave with actionable strategies to automate image generation workflows today—no DevOps or Python required. If you’re ready to turn ideas into outputs faster, this is your blueprint.

This session explores how artificial intelligence can modernize outdated codebases, improve maintainability, and accelerate migration to newer technologies. Attendees will learn how AI-driven tools analyze legacy systems, identify inefficiencies, and suggest optimized refactorings while preserving functionality. The session covers key topics such as automated code analysis, AI-assisted dependency mapping, machine-learning-based code transformation, predictive debugging, and best practices for AI-enhanced modernization strategies. Discussions would also delve into ethical considerations, data security in refactoring, and real-world case studies showcasing successful AI-driven legacy modernization. By the end of the session, participants will gain practical insights into leveraging AI to streamline refactoring processes, reduce technical debt, and future-proof software systems.

Artificial intelligence has rapidly transformed the way we build and deploy applications, and Microsoft.Extensions.AI provides a powerful yet streamlined framework for integrating AI capabilities into .NET-based solutions. In this session, we’ll explore how developers can leverage Microsoft.Extensions.AI to incorporate AI-powered services—such as intelligent decision-making, natural language processing, and data-driven insights—into their applications with minimal complexity.

We’ll start by discussing the architecture of Microsoft.Extensions.AI, covering key components, extensibility patterns, and best practices for integration. Then, we’ll dive into practical examples, demonstrating how to utilize Microsoft.Extensions.AI to enhance applications with machine learning models, OpenAI services, and custom AI functionalities. Along the way, we’ll examine performance optimization strategies and explore deployment considerations to ensure scalable and efficient AI implementations.

By the end of this session, attendees will gain a strong foundation in building AI solutions within the .NET ecosystem, empowering them to create intelligent and adaptive applications that deliver meaningful user experiences. Whether you're new to AI development or looking to refine your expertise, this presentation will equip you with the tools and insights to accelerate your AI journey with Microsoft.Extensions.AI.

This panel explores the evolving impact of AI in coding and the critical ethical concerns. At a high level, we hope to cover these topics, but in a panel session, the conversation goes where it goes.

1. Emerging Trends in AI-Assisted Development

• Self-Learning AI Models: Systems that continuously improve by analyzing developer habits.
• AI-Augmented Low-Code Platforms: Allowing non-developers to build applications more efficiently.
• Autonomous Debugging & Optimization: AI tools that predict and fix code issues before deployment.
• AI-Driven Personalization in Software Design: Customizing applications based on real-time user behavior.
• Integration with Quantum Computing: Exploring how AI-assisted development will evolve alongside quantum tech.

2. Ethical Challenges & Responsible AI Development

• Bias in AI-Generated Code: How training data impacts inclusivity and fairness in software.
• Transparency & Accountability: Ensuring AI-assisted decisions can be audited and explained.
• Job Displacement Concerns: The impact of automation on traditional developer roles.
• Security & Data Privacy: Safeguarding proprietary code and preventing AI-generated vulnerabilities.
• AI Governance & Regulation: How governments and tech leaders are shaping ethical AI policies.

3. Best Practices for Ethical AI in Software Engineering

• Establishing human oversight in AI-generated code.
• Implementing ethical guidelines for AI-assisted development.
• Encouraging community-driven AI research to ensure inclusivity.
• Creating transparency reports for AI-generated recommendations.

4. Interactive Discussion & Case Studies

• Real-world examples of AI misuse in software engineering.
• How companies successfully implement ethical AI policies.