2026 - Jan/Feb
This issue explores AI's transformation of development practices and data management. Wei-Meng Lee's cover story examines agentic AI through SmolAgents, while Sahil Malik builds a verifiable AI stock analyst with citation-backed insights. Sonu Kapoor reveals how Angular's Model Context Protocol enables intent-aware AI collaboration. Matthew Hess demystifies C#'s Nullable Reference Types, and Shawn Wildermuth guides .NET developers through PostgreSQL integration. Mike Yeager explains how Microsoft Fabric unifies fragmented data estates into a governed, AI-ready platform. These articles and others showcase practical implementations of emerging technologies reshaping modern software development.
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Accessibility
Rod is touched by a documentary about a disabled young man playing video games and explores accessibility when it comes to software.
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An AI Stock Analyst That Doesn’t Lie (Probably)
Sahil Malik presents a practical blueprint for building an AI-powered stock analyst that aims to deliver up-to-date, verifiable insights rather than false or outdated claims. The article walks through a client-side application that queries Google Gemini with grounding enabled, returns analyzed stock data, and attaches precise, clickable citations extracted from grounding metadata. Sahil emphasizes trust, robust error handling (including exponential backoff), clear user interface design, and citation formatting to enable users to verify every factual claim, arguing that such verifiable AI tools are essential in finance and beyond.
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PostgreSQL for the .NET Developer
Shawn Wildermuth encourages .NET developers to explore PostgreSQL as a powerful, cost-effective alternative to SQL Server. He explains how PostgreSQL’s open-source nature and advanced features make it suitable for various projects, especially those with budget constraints. Shawn provides practical guidance on setting up PostgreSQL using Docker, highlights key differences from SQL Server, and demonstrates seamless integration with Entity Framework.
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Much Ado About Nullable: Nullable Reference Types Explained
Nullable Reference Types are the ugly stepsister of the C# family of tools. Matthew shows you how, with a little attention, they can blossom into a very useful tool.
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Understanding AI Agents and Agentic AI: Concepts, Tools, and Implementation with SmolAgents
Wei-Meng Lee surveys the rise of agentic AI, shifting from passive prompt models to autonomous thinkers that reason, plan, and act using external tools. He introduces SmolAgents as a lightweight framework that lets LLMs orchestrate multi-step workflows, with two core types: CodeAgent for sandboxed Python code execution and ToolCallingAgent for API calls, web searches, and custom functions. Through practical examples and built-in vs. custom tools, Lee demonstrates how agents decompose complex tasks, combine data from various sources, and deliver cohesive, real-time insights, highlighting design choices for real-world applications.
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Building Distributed Apps Using Rust and C# with .NET Aspire
Joydip explores building scalable, high-performance distributed applications using a polyglot architecture that combines Rust and C# with the .NET Aspire framework. He highlights how Rust handles real-time, low-latency data ingestion and processing, while C# and .NET Aspire manage security, integration, and business logic. The article covers the benefits and challenges of polyglot microservices, details setting up Rust and .NET Aspire projects, and demonstrates interoperability via message brokers like RabbitMQ and serialization with Protocol Buffers, emphasizing the synergy of these technologies for modern cloud-native distributed systems.
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From Commands to Conversations: How AI-Assisted Tooling Is Transforming Angular Development
Sonu argues that Angular’s Model Context Protocol (MCP) and the Angular MCP Server elevate tooling from mere command execution to intent-aware collaboration. By exposing structured, workspace-aware capabilities via mcp.json, MCP enables AI assistants to reason about a project’s structure, conventions, and best practices, enabling context-driven code generation that aligns with modern Angular patterns (standalone components, Signals, typed forms). Kapoor envisions a future where developers interact with their workspace through intelligent assistants or GUI interfaces, improving reliability, safety, and onboarding while preserving control and auditability.
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What You Need to Know About Fabric
Mike argues that Microsoft Fabric is a unifying platform designed to tame fragmented data estates by consolidating diverse data into a single, secure, and governed system called OneLake. By standardizing storage in Delta Parquet across warehouses, lakes, and lakehouses, and pairing robust data engineering, governance (Purview), and AI-enabled Copilots with a simple pay-one-price model, Fabric enables real-time insights, scalable analytics, and AI readiness while maintaining lineage, security, and manageability across dispersed sources and subsidiaries.
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Four AIs, One Epic Barbarian Battle
Jason surveys four lead AI video models—OpenAI Sora 2, Google DeepMind Veo 3, Kling 2.5 from Kuaishou, and Alibaba Wan 2.5—through their architectural philosophies, tradeoffs, and real-world performance on a cinematic prompt. He argues that beyond specs, each tool reflects a stance on physics, control, motion learning, and multimodal integration, and demonstrates how creators will blend strengths from multiple models.