Issue: 2025 - Jan/Feb

  • Rod explores the rapidly evolving landscape of artificial intelligence (AI) and machine learning (ML), emphasizing their increasing accessibility to smaller developers and companies. He notes that AI tools like Whisper and LangChain can enhance application functionalities while acknowledging the accompanying challenges, such as the potential for misinformation and the need for human oversight to ensure accuracy. Through CODE Magazine, Rod hopes to guide readers in integr...See More
  • Sahil Malik explores the feasibility of creating a sophisticated AI digital assistant akin to HAL 9000 from "2001: A Space Odyssey," all while ensuring the system operates offline on a commercially available MacBook Pro. Sahil details the process of constructing this AI system, leveraging tools like Hugging Face for model sourcing, OpenAI's Whisper for speech recognition, and the Gemma language model for processing and generating coherent, context-aware responses. He sha...See More
  • In this fourth entry in his series on MAUI, Paul teaches you about the Model-View-View-Model (MVVM) and Dependency Injection (DI) design patterns to make reusable, maintainable, and testable applications. You’ll also learn how to make your code-behind more efficient using Commanding.
  • Joydip Kanjilal explores the Command Query Responsibility Segregation (CQRS) design pattern and its application in microservices architectures built with ASP.NET Core. You'll learn the benefits of using CQRS, including scalability, performance optimization, and maintainability, by isolating read and write operations. Kanjilal provides a comprehensive guide on implementing CQRS with code examples, focusing on creating, updating, and deleting operations using ASP.NET Core ...See More
  • Wei-Meng Lee provides an in-depth guide to using the LangChain framework for building applications incorporating large language models (LLMs). He emphasizes LangChain's modular design, enabling developers to create complex workflows with customizable components and integrate external data sources, facilitating Retrieval-Augmented Generation. Key topics covered include constructing chains, maintaining conversational context with memory management, and leveraging Microsoft...See More
  • In "Semantic Kernel Part 4: Agents," Mike Yeager explores the use of agents within Semantic Kernel (SK) to tackle complex tasks by customizing Large Language Models (LLMs). Mike explains that agents function as specialized LLMs with specific capabilities, such as performing calculations or accessing tools like MATLAB, to produce more accurate and specialized outcomes. You'll learn about creating assistant agents for specific use cases, like tax calculation, and chat agen...See More
  • Jason Murphy explores the evolution of his fascination with tabletop role-playing games, from his improvisational beginnings as a Dungeon Master to creating a sophisticated encounter builder using Large Language Models (LLMs). He details his development of an automated system leveraging AI to generate immersive and tailored RPG encounters. By instructing an LLM and refining its responses, Murphy effectively reduces preparation time, enabling more dynamic game sessions. T...See More
  • Mike recounts his transition to a Snapdragon-powered Copilot+ PC ARM computer, emphasizing how its Hexagon NPU significantly enhances AI tasks. Despite minor software compatibility issues and delayed AI features like Phi Silica and Recall, Mike appreciates the device's speed and efficiency for development tasks, such as using Visual Studio and engaging in programming on Windows ARM64. He experiments with AI capabilities using ONNX models and remains optimistic about the ...See More