Learn Angular-material, Cloudinary and Reactfire

cloudinary

We'll learn how to integrate Cloudinary into our Strapi application so that we can upload image assets in our Strapi dashboard and the resulting image will be stored in Cloudinary and ready for use in our application.

We'll create a `config/plugins.js` file and paste in some config code that sets Cloudinary as the provider with `cloud_name`, `api_key`, and `api_secret`.

Then we'll install the Cloudinary provider plugin with `npm install @strapi/provider-upload-cloudinary`, add the middleware security that lets us use Cloudinary, and finally add Cloudinary credentials to our `.env` file.

Install and Add the Cloudinary Provider to a Strapi Application

Media is an important part in creating a good UX for potential customers of your store, but when serving large unoptimized images, you can end up giving them a poor experience with long page loads.

We can instead use Cloudinary to automatically optimize our images and resize them on the fly with Cloudinary's programmable media API to deliver a more performant online store.

* [Cloudinary URL-Gen for JS - cloudinary.com](https://cloudinary.com/documentation/sdks/js/url-gen/index.html)

Optimize Media with Cloudinary to Deliver Smaller and Performant Images

🚨The Cloudinary UIX has been deprecated. If you are using it, you need to replace it with the App. [Here](https://hygraph.com/docs/guides/integrations/connect-cloudinary#migration) is a step-by-step guide on how to do it. 🚨

We will take an existing UI extension, Cloudinary, clone it down, and create our own instance, installing it into our GraphCMS content editor. Once we add that Cloudinary asset as a field, we will select those images directly from our Cloudinary account and serve those images right inside of our app.

Add and Configure Cloudinary UI Extension to Add Images From a Cloudinary Media Library

AngularJS is an open-source JavaScript framework, maintained by Google, that assists with running single-page applications. Its goal is to augment web-based applications with model–view–controller (MVC) capability, in an effort to make both development and testing easier.

angularjs

Themes convey meaning through color, tones, and contrasts. And the theme color palettes, alphas, and shadows deliver a consistent tone to your application and a unified feel for all Angular Material UI components. Theming allows developers to change the intention and meaning of the application by changing the colors and shadows. 

Accessibility is a huge - often overlooked - feature in modern web applications. Angular Material components all implement ARIA features whenever possible. And for usage scenarios where the ARIA attributes are not explicitly provided and cannot be inferred, then Angular Material will provide details console warnings alerting the developer.

Let’s use the Angular Material Theming service to change the background, primary, accent, and warning colors used within the entire application. These will be configured at startup using the $mdThemeProvider.  

Let’s also resolve the two ARIA warnings shown in console. These originate from icon buttons where the ARIA label cannot be inferred. So let’s add a static aria-label and a dynamic, interpolated aria-label to those buttons.

> This course presented by Thomas Burleson and Aaron Frost

Angular Material: Theming and ARIA

Most Angular Material UI components are declarative and used directly in the HTML markup. Some components, however, are programmatic and must be configured and invoked from Javascript. Programmatic components have a short-term, limited DOM lifespan and include Dialogs, Toast, and BottomSheet.

Let’s use the BottomSheet service to configure and display an Angular Material BottomSheet container which in turn will display a nested, custom Contact Sheet view.

> This course presented by by Thomas Burleson & Aaron Frost.

Angular Material: Using a BottomSheet

Both flexbox CSS and the Angular Material Layout allow web applications to `respond` to the size of the browser at any given point. No matter what the browser width may be, the web app adjusts its layout sizing accordingly. Combine responsive functionality with media query support and your web applications will have `adaptive` features to adapt to the width of the browser at a specific points. More than fluidly adjusting the widths and heights of elements, Adaptive applications can change the rendered UX with new positions, new components, and new styles. Angular Material Layout hides the complexities of implementing adaptive features with a singularly unique and simple HTML syntax.
Let’s use the Adaptive extensions of the Angular Material API to hide the SideNav on small devices (like iPhone or Android). We will explore the use of the $mdMedia service to easily lock open the SideNav on larger devices. And we will see how the $mdSideNav service can be used to programmatically close the SideNav after a user is selected.

> This course presented by Thomas Burleson and Aaron Frost.

Angular Material: Adaptive Layouts

Angular Material UI components have been designed from the ground-up to use dynamic, live data. Supporting AngularJS interpolation, expressions, and databindings… each component exposes an intuitive API and fully supports the existing ng-<xxx> directives published in AngularJS.

Let’s replace the hard-coded, static HTML with dynamic, mock data using AngularJS data bindings, ng-repeat, and the ng-click directives. Our UX remains unchanged, yet now we are using custom application logic and dataservices.

> This course has been created by Thomas Burleson & Aaron Frost.

Angular Material: UI Components with Dynamic Data

Angular Material is an Angular-native, UI component framework from Google. It is a reference implementation of Google's Material Design and provides >30 UI components and services essential for mobile and desktop AngularJS applications.

In this course, we will quickly build a real-work application Angular UI application, take a tour of Angular Material, and learn how ngMaterial can be used in your projects.

*presented by Thomas Burleson and Aaron Frost*

Introduction to AngularJS Material

The Angular Material Layout API wraps the flexbox CSS features with an amazingly easy, powerful HTML markup API. The Layout API hides the complexities of the CSS, is intuitive to use, and eliminates the need for developers to become flexbox experts to implement modern page layouts. 

In this lesson we will learn how to use the Angular Material Container components and the Layout API to implement the layouts specified in design wireframe.

> This course has been created by Thomas Burleson and Aaron Frost. 

Angular Material: Containers with the Layout API

Learn how to install Angular Material with `npm install`  and load the required libraries and stylesheets into your blank web page.

> This course has been created by Thomas Burleson and Aaron Frost

Angular Material: Installing with NPM

Angular Material provides over 30 UI components and services. The framework offers a suite of components and containers: from simple Button components with built-in ink and hover effects, theming, and ARIA support… to more complex container components like mdList and Tabs.  

Let’s use some of those components in our SideNav and Content containers. For now we will use hard-coded, HTML markup. This allows us to confirm the UX matches that specified in the design docs before we start working on our application logic.

> This course has been created by Thomas Burleson and Aaron Frost.

Angular Material: Intro to UI Components

 We map over the initial set of results then use `Promise.all` to efficiently fetch the details of each pokemon rendered in the table. This allows us to add more columns to our pokemon table.

Fetch and display row details with Promise.all in Tanstack Table

map over the initial set of results then use `Promise.all` to efficiently fetch the details of each pokemon rendered in the tanstack table

Create a custom hook to fetch remote data by passing a promise to the React 19 `use` hook. Then render this data in Tanstack Table by memoizing the results and passing them to `useReactTable`.

Render remote data in a Tanstack Table with React 19's use hook and a promise

Create a custom hook using React 19’s use to fetch data with a promise. Render it in a Tanstack Table by memoizing and using useReactTable.

You know when you're deep in the code trenches and need someone to challenge your assumptions? That's exactly what this is about.

Instead of waiting for someone to poke holes in your master plan, you can paste that strategy straight into AI Studio and let it pressure test your ideas. We're talking about using this tool to validate everything from your feature proposals to your ambitious refactoring strategies.

The real magic happens when you hit that microphone button. Now you're in a real-time verbal sparring match. It's like rubber duck debugging but the duck actually pushes back and makes you defend every architectural decision you've made.

Here's the workflow:
1. Drop your master plan into the system instructions
2. Tell the AI to challenge every assumption
3. Hit that mic and defend your choices like you mean it
4. Watch your plan either emerge stronger or get rightfully dismantled

This approach is perfect when you're:
- Stuck in your own head with a complex problem
- Need to validate if your approach holds water
- Want to catch edge cases before they catch you
- Looking for opportunities you might have missed because you're too close to the code

It's like having a senior dev on call 24/7, ready to challenge your ideas and push you to think deeper about your solutions.

Now go forth and get your ideas challenged. Your projects will thank you for it.


An Uncomfortable and Challenging Conversation with AI Studio

In this lesson, you'll learn how to effectively brainstorm your project ideas before working with AI agents. We'll cover:

1. The importance of having a clear plan before starting work with AI agents
2. Using traditional brainstorming techniques to gather your thoughts
3. Leveraging video recording to capture your brainstorming session
4. How to review and analyze websites for inspiration
5. Documenting likes, dislikes, and potential features for your project
6. Using AI tools (like AI Studio) to organize and process your recorded brainstorming session

The lesson emphasizes a modern approach to brainstorming that combines traditional techniques with video recording, making it easier to later process your ideas through AI tools. This method helps ensure that no ideas are lost and that your thoughts can be effectively organized by AI for future reference.

How to Brainstorm Your Project Features to Prepare for AI Agents

Many people share .cursorrules files, but trying to craft your own from scratch is a huge pain. Instead, this lesson shows you how to grab ALL community-created .cursorrules files to build a custom rule set for your projects. We'll use Gitingest and Google AI Studio to gather these examples and generate an awesome starting point customized to your specific project.

Generate Custom .cursorrules for Your Project Based on Community Examples

Learn how to leverage the GitHub CLI to efficiently search through issues across multiple repositories and use that data with AI Studio for deeper insights.

You learn how to:

-  Search for specific issues across repositories using GitHub CLI
- Filtering issues based on criteria like comment count
- Extracting issue content and comments
- Using the collected data as context in AI Studio
- Creating practical applications like FAQs from issue discussions

The example demonstrates creating a Framer Motion FAQ by searching GitHub for issues with multiple comments, but the technique can be applied to any framework or library.

This workflow helps developers:
- Research common problems and solutions
- Understand recurring issues in specific technologies
- Generate useful documentation from real-world problems
- Make better use of existing GitHub discussions

This approach combines the power of GitHub's vast knowledge base with AI tools to create valuable insights for development work.

Search 100s of Issues with GitHub CLI as Context for AI Studio

I often find myself wondering how to use certain APIs in certain situations, and I have a couple of keywords that I try and search up on Google. 

What you can do in this situation is turn to GitHub and see how other people have actually used this code on public projects. The GitHub CLI enables us to run searches like this, and we can take the results and work on them programmatically.

Inside of Cursor with their Composer AI agent, we can search for the files we want, tell the agent to download them, and inspect them for better understanding of how those things work together.

Search All of GitHub's Code and Pass the Results to AI Agents in Cursor

Implement virtual scrolling to handle large datasets in an HTML table. Start with a basic table that renders 10,000 rows of data. The browser can struggle with this amount of DOM nodes to render at one time, especially on low end devices. 

We implement tanstack react virtual to render only the necessary amount of rows the user is viewing. The implementation includes proper column sizing, accessibility considerations, and convenient scroll controls, resulting in a smooth and performant table experience regardless of the dataset size.

Create a row virtualized HTML table with Tanstack Virtual

Learn how to implement virtual scrolling in React tables using TanStack Table and Tanstack Virtual with the useWindowVirtualizer React hook.

The most difficult tasks will require the strongest AI models. And those models simply aren't available as AI agents inside of your tooling. So the best workflows are to drag and drop the files you need to be changed and analyzed inside of a reasoning model such as OpenAI's O1 Pro, then letting it create a giant plan for your dumber AI agents to work on. The key here is that instead of just copying and pasting the entire plan into Cursors Composer or your AI agent, it's to create a file inside of your project and ask your agent to tackle the plan one step at a time. This allows you ample opportunity between each step to test and verify the micro steps along the way. Otherwise, as I've experienced many times, a session can go way off track and you burn a lot of time and burn a lot of AI requests Cursors Composer and it starts churning through a plan Cursors Composer and making lots of unwanted changes. Cursors Composer and it's to guide an AI agent to hold its hand along the way, especially through the most complex tasks. Cursors Composer and the most complex tasks Cursors Composer and the most complex tasks require a step-by-step plan.

Planning AI Agent Sessions with Reasoning Models

AI agents will inevitably make mistakes—it's just a matter of when. A key tool in your toolbox, once they do make mistakes after working on a problem for a while, is to use **git diff** to capture all of the changes they've made. 

Once you have those changes in a text file, you have a portable document that you can test against other AI models. This allows you to move the problem into smarter reasoning models with smaller context windows, helping you isolate and focus on the issue at hand.

**git diff** has been invaluable when working with AI agents because they'll often make many good changes but also slip in one tiny error. Finding that one small mistake is **git diff**’s superpower.

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