CODE Magazine

By the time asynchronous behaviour enters a form, most architectural decisions have already been made, whether consciously or not. In the first part of this series, we resisted the usual impulse to “wire things up” early. Instead, we stepped back and rebuilt a form from first principles. We treated form data as a state rather than as a stream of events. A registration form was modelled as a typed signal. Validation rules were declared against that model.

.NET Aspire is a unified, cloud-ready software development stack designed to efficiently handle orchestration, configuration, service integration, and observability in distributed applications. You can use Aspire to simplify the entire lifecycle of distributed applications—from development to deployment and monitoring—while promoting consistent architecture and operational practices that can help make your applications scalable, reliable, and easy to maintain.

The early days of AI-assisted code generation primarily involved developers sending prompts to an AI coding assistant, such as Anthropic's Claude Code, and taking the generated code and inserting it into a codebase.

Picture this: It's 7 p.m. on a Friday night. You and the nerds are gathered around the table. Snacks have been dispensed. Miniatures are laid out. Maps are drawn. Maybe someone is wearing a cloak. It's about to get weird. But these are modern times with modern problems. Gaming isn't the same as it was in decades past. It's not just paper, pencils, and dice. Sometimes it's virtual tabletops, digital libraries, and expensive subscription systems. Those dollars can add up.

This summer marks a turning point in how developers consume AI tooling. GitHub Copilot's transition from flat-rate subscriptions to usage-based billing, powered by token consumption and GitHub AI Credits, which started on June 1st, is more than a billing change. It's a clear signal that the economics of AI-assisted development are maturing, and that the era of treating AI as “free” is ending.

I have written many articles on AI, and it is really interesting to see how the landscape of AI has changed over time. The landscape of AI-driven IT is shifting from traditional support roles toward specialized “architects” of intelligence. As organizations move beyond simple chatbots, these distinct personas have emerged to handle the integration of large language models (LLMs) and agentic workflows. I'll identify a few of these roles.

Note: You are not currently logged in. If you log in, we can fill in some information and save you a lot of typing. Please provide all the missing information so we can properly sign you up for this event. Have you ever wondered about the power of quantum computing, and the threat it poses to our state-of-the-art cryptography?

For your first task at work, you check your emails. There is an urgent email from one of your coworkers, titled “Is our data safe?

A Short History of AI Frameworks in .NET The best way to build an AI solution is evolving almost as fast as LLMs themselves. ChatGPT was publicly released on November 30, 2022, and like many of us, I tried it for the first time in January 2023. My first attempt at incorporating it into an application came later that summer. Programming was an interesting experience involving using HttpClient(), and learning about some basic concepts like temperature and tokens and prompt engineering.

Building distributed applications has historically been difficult because of the many disparate components in the distributed application stack, such as user interface components, services, and data stores that need to be managed, configured, and orchestrated. Thanks to the code-first development methodology of .NET Aspire, you can now build your entire application using this cloud-ready development stack within your familiar Visual Studio IDE environment.