Transform from a coder into an AI architect. This guide demystifies generative AI, teaching you when to use conversational "Vibe Coding" versus structured "Spec Coding." Master prompt engineering to write better, more secure code and avoid common AI pitfalls.

Discover how generative AI is transforming the software architect's role from a hands-on coder to a strategic orchestrator. Learn what tasks to stop doing and what new, high-value responsibilities to embrace to stay ahead in an AI-driven world.

Low-code platforms promise incredible speed, but are they solving the right problem? Discover why the real bottleneck to developer productivity isn't coding, and how platform engineering is the key to unlocking true enterprise velocity.

Is migrating from.NET Framework to .NET 8+ worth it? Explore the huge performance gains, security benefits, and cross-platform capabilities. Discover how new AI tools and features make the upgrade more compelling and easier than ever.

Elevate your team's performance with a proven framework for architectural governance. Learn to Codify standards, Automate compliance, and Cultivate a culture of quality to build scalable, maintainable software.

Is your QA team a bottleneck? Learn why the traditional "inspection" model fails and how to build a culture of quality where engineers own their work, inspired by the principles of W. Edwards Deming.

Deciding on a tech stack? Learn why the choice between .NET and open-source languages like Python isn't about cost anymore. This guide explores TCO, developer salaries, and long-term maintenance for startups.

Ready to build AI-powered apps? Discover how .NET developers can create powerful generative AI solutions using C#, ML.NET, and Semantic Kernel. Learn to leverage existing skills to build enterprise-grade chatbots, content generators, and more - Python not required.

I explored Google Gemini and was impressed by its speed compared to ChatGPT! My hands-on experience, from coding .NET regex to using the free API tier in Google AI Studio, is detailed in this article. Even though Gemini's Semantic Kernel integration is new, I easily adapted an OpenAI example. If you're curious about a powerful OpenAI alternative, especially within the Google ecosystem, you need to read this.

Recently, I explored using Semantic Kernel and OpenAI for more accurate page scanning. By converting HTML to markdown and extracting metatags with XPath, I reduced input size and improved efficiency. OpenAI’s new JSON output feature further allowed me to receive structured data, making the process more reliable.