Nick's .NET Travels

There’s been quite a bit of hype around the use of AI for vibe coding applications.

For most of my career, I’ve been a proud Windows developer.

The world of software development has been inverted by the introduction of AI.

With every update to the various models and tools, AI becomes more capable and in a lot of ways more independent.

Earlier this year Microsoft was touting all the work they’re putting into Windows in order to make it AI ready.

One of the things about software development is that it is still inherently expensive to do; well at least, to do it well.

In my previous post on Click to Do we created an application that is activated via a URI triggered by Click to Do.

This was going to be a post about using COM Server activation in a WinAppSdk application to interact with Click to Do.

I’ve talked a lot in the past about how XAML applications lend themselves to being styled using data and control templates.

With the latest generation of Copilot+ PCs, Microsoft is integrating AI deep into the core of Windows with features like Recall and Click to Do.

I decided to ask ChatGPT what suggestions it had for building cross platform applications.

As I discussed in my previous post the Uno Platform team have release a subscription based offering, Uno Platform Studio, which includes a runtime visual designer, Hot Design.

As the .NET ecosystem continues to grow and evolve, so does the need for robust tooling that helps developers build cross-platform applications faster and more efficiently.

Quite often I hear the complaint that WinUI, and thus Uno Platform, doesn’t include validation.

The Model-View-ViewModel (MVVM) pattern has long been a cornerstone in building maintainable and testable UIs across frameworks like WPF, Xamarin, Uno Platform, and others.

In this post we’re going to do two things.

Last week v6.0 of the Uno Platform was released marking the cumulation of a number of years of investment in both the core cross platform framework, as well as the new Uno Platform Studio (including Hot Design), a set of tools that are designed to acceler…

In the past three posts about working with AI on Windows, we covered connecting to Phi Silica, getting progress response, and building a chat experience.

In the past two posts we covered connecting to Phi Silica and then getting progress response to provide a more real time experience.

In my previous post I covered the basics of creating an Uno Platform application that consumes Phi Silica in order to build a very basic prompt-response based user interface.

Last year Microsoft introduced Phi Silica and recently made an experimental release of the Windows App Sdk that can be used by Windows application to interact with Phi Silica.

Recently Microsoft has been promoting Copilot+ PCs as the next wave of tablets, laptops and PCs capable of handling your AI requirements.

In my previous attempt with TempoLabs I was able to successfully build the ABN lookup scenario that I’d been testing with other app builders.

Ok, so the title is a bit of a mouthful but here’s the scenario – you want to quickly spin up an application but you don’t want to mess around downloading and installing any of the usual development tools required to build an Uno Platform application.

I was watching overview of TempoLabs and my initial impression was “wow, that’s a lot of stuff” as they not only have AI generation but it seems they understand at least the basics of a software devlelopment process.

Following from my previous attempt at building a simple app to retrieve the ABN for a business, I figured I’d give lovable.dev a go.

I figured I’d take some of these AI app builders for a run to see how capable they are.

The default template for a Windows application comes with almost no guidance for how developers should do even basic things like logging.

Following my previous posts that introduced the AI Dev Gallery, added AI code to an Uno Platform application and adjusting the AI code to work with Android, in this post we’re going to look at the adjustments required to get the AI code to work on iOS.

In the last two posts I introduced the AI Dev Gallery that Microsoft has been working on, and then demonstrated how code exported from the AI Dev Gallery can be added to an Uno Platform application.

In my previous post I introduced the AI Dev Gallery that Microsoft has been working on, as a way of creating a Windows application that can use AI.

Recently, Microsoft announced an open-sourced project that they’ve been working on, AI Dev Gallery.

The Figma Windows UI kit file has been updated by the WinUI team.

Earlier this month Microsoft introduced the preview of Microsoft.Extensions.AI.Abstractions and Microsoft.Extensions.AI libraries with the aim of making it easier for .NET developers to integrate AI services into their applications.

XAML is often criticised for being verbose, hard to read and unnecessary as an additional language for defining the interface for an application.

In my previous post I looked how the Windows UI 3 Figma file components and variants map to styles and visual states in Windows UI but glosses over some of the details of how resources and in particular, Styles, are defined in Windows UI.

In a previous post I covered using Figma to design and develop applications for Windows and the Uno Platform.

OAuth2 is quite a common authentication standard for web services to use.

Designing applications for Windows and the Uno Platform can be difficult if you attempt to start from a clean slate and assume that you have to design everything from the ground up.

This post is going to walk through using the Microsoft tool, Kiota, to generate client code from a Swagger / OpenAPI definition that can be used within a Windows (WinUI/Windows App Sdk) / Uno Platform application.

In all but the simplest single page application, the layout of an application has to be dynamicaly changed in order to display information, or capture input from the user.

Out of the box, applications built using WinUI / Windows App Sdk or the Uno Platform have access to a wide range of controls, such as Frame, TabBar and NavigationView that can be used for navigation.

The Uno Platform supports many third party control libraries, such as Mapsui and LiveCharts, but sometimes there are components that you want to use that haven’t been adapted to work with Uno.

This has been a work in progress over the last couple of releases in order to deliver a better developer experience for the Uno Platform.

In my previous post I walked through how to connect to ChatGPT in order to integrate AI into a multi-platform (Windows App SDK and the Uno Platform) based application.

In today’s digital world, integrating AI into your applications has become increasingly important.

As with all software managing dependencies in often a lot harder than it seems, particularly when there are conflicting priorities.

Ok this post took a bit of inspiration from the C# Markup support that’s available for the Uno Platform where it’s easy to build a template selector (for a ListView for example) using a set of Case statements.

In this post I’m going to experiment using ChatGPT and Copilot to help generate the XAML for pages in a Windows application.

Last week, the Uno Platform officially launched their Figma Plugin which works in parity with the Uno Platform Material Toolkit to support both designers and developers with the process of designing applications.