Blog.CodeWithDan.com is the personal blog of Dan Wahlin, Cloud Developer Advocate at Microsoft and a well known educator in the JavaScript and cloud ecosystem. Dan writes about JavaScript, TypeScript, Angular, Azure, Docker, Kubernetes, AI assisted development, and modern cloud architecture, always focusing on practical examples and real world scenarios. His articles explain how to build scalable applications, use Azure services effectively, and integrate AI, Realtime APIs, and tools like MCP or TypeChat into production projects. Much of the content comes from his work on courses, workshops, and developer training, which makes the writing clear, actionable, and grounded in real engineering experience.
10 articles from this blog
A guide to the Model Context Protocol (MCP) for AI agents, explaining its core capabilities using a story-driven example.
A hands-on guide for JavaScript developers to learn Generative AI and LLMs through interactive lessons, projects, and a companion app.
A beginner's guide to the Model Context Protocol (MCP) for building scalable AI applications with tutorials in C#, Python, Java, and TypeScript.
A guide to the GitHub Copilot Adventures repository, featuring hands-on coding challenges to learn AI-paired programming across multiple languages.
A guide to building a Model Context Protocol (MCP) server that connects to the Marvel API, demonstrating how to integrate external APIs with AI systems.
An introduction to RealTime AI, exploring the fundamentals of low-latency AI using the OpenAI Realtime API for fluid, conversational applications.
A free, interactive course on GitHub teaching Generative AI concepts using JavaScript through a creative time-travel adventure narrative.
A curated list of resources for learning Generative AI and Prompt Engineering, including guides, tutorials, and documentation from OpenAI, DeepLearning.AI, and Microsoft.
Learn how to enhance Line of Business apps using OpenAI GPT models, Azure Communication Services, and Microsoft Graph for better productivity.
Explains AI transformers, tokens, and embeddings using a simple LEGO analogy to demystify how language models process and understand text.
