AI-powered dev | Front-end enthusiast | DevOps | Azure
Thijs is a passionate DevOps engineer and front-end development enthusiast, with a unique edge as an AI-powered developer. He has been consulting at various clients, building and supporting large distributed systems in DevOps teams. Maximizing impact and business value is something that Thijs pursues, and people call him a Jack of All Trades or Mr. Frontend. His methodology of work is much like the book: “The Lean Startup”.
Thijs is a strong advocate for applying DevOps practices at customers' projects, focusing on team autonomy as one of the most important aspects. He enables teams to deploy their own cloud resources through Infrastructure as Code and their services through CI/CD. Thijs has also implemented an observability strategy to provide effective 24/7 support.
As an AI-powered developer, Thijs integrates cutting-edge AI tools into his development process. This allows him to improve code quality, boost productivity, and be any profession, ensuring that his projects stay ahead of the curve.
"You build it, you run it, you own it."
Area of Expertise
Is ChatGPT a Better Software Engineer Than Me?
In this session, we will explore the capabilities of ChatGPT as a software engineer, including its ability to write code, debug, and troubleshoot issues. We will also discuss the limitations and challenges of using AI in software engineering and consider the implications for the future of the field.
We explore how to become a better developer using AI, touching on the mindset shift from traditional search engines to leveraging ChatGPT. We also discuss the importance of prompt building for effective communication with ChatGPT.
We present various IDE integrated AI tools to assist with coding, writing commits and more. Additionally, we introduce image generation tools like Midjourney and Dall-E for inspiring UI, icon, and artwork design, as well as AI applications for blogging, documentation, and tutorials.
Whether you are a software engineer yourself or simply interested in the role of AI in technology, this session will provide insights and thought-provoking discussions on the intersection of AI and software engineering.
Unlock the Power of AI with Microsoft Semantic Kernel
Explore Semantic Kernel (SK), a lightweight SDK designed to seamlessly integrate AI Large Language Models (LLMs) with conventional programming languages like ChatGPT. This session will guide you through the innovative features and applications of Microsoft's Semantic Kernel, empowering you to unlock the potential of AI in your projects and applications.
During this session, we will cover:
Introduction to Semantic Kernel:
A brief overview of SK and its role in bridging the gap between LLMs and traditional programming languages.
The SK Extensible Programming Model:
A deep dive into the architecture and components of SK, including prompt chaining, recursive reasoning, summarization, zero/few-shot learning, contextual memory, long-term memory, embeddings, semantic indexing, planning, and accessing external knowledge stores as well as your own data.
Integrating LLMs with Conventional Programming Languages:
Hands-on demonstrations and examples displaying how to leverage SK to bring AI capabilities into popular programming languages such as C# and Techniques for optimizing AI integration in your projects for maximum performance and efficiency.
Real-world Applications and Use Cases:
An examination of the diverse sectors and industries that can benefit from the capabilities unlocked by the SK programming model.
Future Directions and Opportunities:
A discussion on the future of SK and its potential impact on AI development and programming paradigms.
By the end of this session, you'll have an understanding of Semantic Kernel and its potential in integrating AI Large Language Models with conventional programming languages. Stay ahead of the curve and harness the power of AI in your projects!
- Software developers and engineers
- AI and machine learning enthusiasts
- Technical team leads and managers
Preferred Session Duration: 45 - 60 minutes
Prior experience with AI Large Language Models, such as GPT is recommended but not required.
Slides and example code will be provided to participants after the session.