Issue: 2025 - Nov/Dec

  • Rod Paddock reflects on how a curated library of timeless software books has profoundly shaped his coding practice and view of the field. He explains why classic titles—from Weinberg’s psychology of programming to Brooks’s Mythical Man-Month, Game Developer postmortems, Kocienda’s Creative Selection, and Programmer at Work interviews—remain inspirational because they illuminate teamwork, real-world project challenges, and the social nature of software.
  • Paul introduces the ES6 JavaScript class keyword and shows you how to pass in arguments, create public read-only properties, and make private fields. You’ll learn how to override an inherited method in an extended class, call methods in the parent class, and extend the built-in classes.
  • Sahil Malik demonstrates how developers can use local, unsupervised machine learning—specifically Isolation Forest—to detect anomalous system behavior as a practical security measure in an AI-driven development world; he provides step-by-step code to generate synthetic logs, train and run the model, visualize results, and suggests real-world enhancements for monitoring, tuning, and alerting.
  • In this second installation of his series on Angular Signals, Sonu designs Angular Signals applications that replace lifecycle-bound input handling, remove boilerplate queries, update two-way binding, use signals and route parameters to improve navigation decisions, and connect to signal-powered API calls.
  • Joydip looks at how Microsoft’s cross-platform, open-source machine learning framework, ML.NET, brings AI and ML to .NET developers. You can build, train, and deploy models that get your business where you want it to go using tools already available in .NET.
  • Nevio, Enzo, and Vassili explore using a customized C# scripting language to develop server-side API scripts for web applications.
  • Jason Murphy argues for Model Context Protocol (MCP) as a foundational open standard that unifies how AI models access and use external context. He contends that current ad hoc solutions—plug-ins, vector stores, and RAG—are brittle, siloed, and non-transferable, and thus inadequate for scalable, secure real-world use. MCP provides a structured, interoperable, permissioned bridge between AI models and diverse data sources and tools, enabling context requests, controlled a...See More
  • Security is always on everyone’s minds, but it often comes too late in the development process to be handled quickly or comprehensively. Gaurav uses SecureCodeAgent, a GenAI-powered solution, earlier in the development cycle.