Learn Alpine, Grunt and Ruby

Rails is a web-application framework that includes everything needed to create database-backed web applications according to the Model-View-Controller (MVC) pattern.

rails

If you make a mistake when naming your database column, and have data that you want to keep unchanged. You can use the change method with the rename_column definition in your migrations files to update a single column name in your database.

Rename A Database Column with Ruby on Rails Active Record Migrations

Alpine.js offers you the reactive and declarative nature of big frameworks like Vue or React at a much lower cost.

You get to keep your DOM, and sprinkle in behavior as you see fit.

alpine

Welcome to this beginner level series on Alpine JS! 👋🏞

Alpine JS is a rugged, minimal framework for composing JavaScript behaviour in your markup. It brings declarative, reactive, data-driven nature of libraries like React or Vue to your HTML templates.

This is the series intro video. Let's get started!

Series Intro - Beginner Level Alpine JS

In this lesson, we build a little app that fetches dog photos from the dog.ceo API, based on a "breed" search field. We want the API call to happen again when the search value changes, and to do so we use the `$watch` property from Alpine JS, which lets us define what state property we want to watch, and what callback function to run when a change happens.

We also use the `debounce` modifier on the `x-model` property to avoid firing an API call on each keystroke.

Refetch API data when a state value changes with the `$watch` property in Alpine JS

Welcome to this beginner level series on Alpine JS! 👋🏞

Alpine JS is a rugged, minimal framework for composing JavaScript behaviour in your markup. It brings declarative, reactive, data-driven nature of libraries like React or Vue to your HTML templates.

In this series, you will learn about Alpine's handy **directives**. You'll discover how to define a component scope with `x-data`, run code on mount with `x-init`, attach event listeners with `x-on`, display data with `x-text`, decide wether or not to show an element with `x-show`, iterate through data with `x-for`, retrieve a DOM element with `x-ref`, learn how to achieve _two-way data binding_ with `x-model`, and much more.

You'll also learn how **"modifiers"** can be applied and chained to directives to provide additional functionality: control the animation transition of entering and leaving DOM elements, debounce an event listener, etc.

We'll also touch on what Alpine calls **"magic properties"**, which give you access to native browser events (`$event`), reference to DOM elements (`$refs`), and more.

You'll gradually discover Alpine's API and syntax, from building simple tabs to a mini app that fetches a dog picture based on a "breed" search field. 🐶

**Get ready to breathe some fresh air** - it's time to walk into cool, green Alpine pastures! 🏞

Sprinkle declarative, reactive behaviour on your HTML with Alpine JS

In this lesson, we see how the `x-model` directive makes achieving "two-way data binding" effortless in Alpine JS.

We see what it would take to recreate the same functionality with an `x-bind` directive for the input value, as well as an `@input` event listener which, thanks to an access to the browser's native events via the `$event` magic property, sets the state value to `$event.target.value`.

Keep a DOM input and state value in sync with the `x-model` directive in Alpine JS

In this lesson, we learn how to retrieve a DOM element via the `x-ref` directive in Alpine JS, which gives us a reference to the element it is applied on. In our case, an input field.

We can then use the `$refs` object, and reach for the ref we need to target.

This allows us to trigger the focus state of the input field, with the `.focus()` method.

Focus an input field on button click with `x-ref` and the `$refs` property in Alpine JS

In this lesson, we learn how the `x-init` directive in Alpine JS lets us run a JavaScript expression once the component has initiated.

We see the nuances that allow us to trigger that code before Alpine performs initial DOM updates, or after these updates have been made.

Focus in input field on page load with `x-init` in Alpine JS

In this lesson, we smoothen the transitions between tabs by applying a `transition` modifier to our `x-show` directive.

We see how we can ignore the leaving elements, and focus the animation on the entering elements. We tweak the transition duration and origin by chaining additional modifiers to our `x-show` directive.

Control enter and leave transitions with the `x-show.transition` modifier in Alpine JS

In this lesson, we create a set of tabs with Alpine JS, where only the content of the currently active tab is visible. To do this, we define an `activeTab` state value with `x-data. We then wire up our buttons to change the value of `activeTab` on click, and use `x-show` to determine if the tab content should be visible or not, based on the value of `activeTab`.

We also take control of the `class` attribute with `x-bind`, and we conditionally output an "active" class based on, you guessed it, the value of `activeTab`.

Toggle visibility and styles based on state with `x-show` and `x-bind` in Alpine JS

In this lesson, we define a "count" state value with the `x-data` directive provided by Alpine JS. This defines a new scoped component, which can have access to this state.

We then display the "count" value in our HTML with the `x-text` directive, which updates an element's `innerText` value.

We also hook up buttons with click event listeners with `x-on:click`, which allows us to modify the count value as desired.

Update a count state value with the x-on event listener directive in Alpine JS

In this lesson, we move the component definition to a function, defined in a script tag in the HTML document.

We then iterate through an Array of Objects with the `x-for` directive in Alpine JS. We use a `<template>` tag to wrap the HTML element we want to repeat for each item, and put the `x-for` directive on that template tag.

We also define a "computed" property by adding a method on our function, which checks if a given ID matched the currently active tab id. This computed property allows us to determine wether or not to apply the "active" classname to our tab buttons.

Iterate through data with the `x-for` attribute in Alpine JS

Jekyll is a parsing engine bundled as a ruby gem used to build static websites from dynamic components such as templates, partials, liquid code, markdown, etc. Jekyll is known as "a simple, blog aware, static site generator".

jekyll

[Jekyll](https://jekyllrb.com/) is a static site generator built in [Ruby](https://www.ruby-lang.org/en/) and available to generate and host websites on [GitHub Pages](https://pages.github.com/). In this course, you'll install the Jekyll gem, use the command line tool to generate a new project, inspect the scaffolded project, and finally, serve the starter website.

Install Jekyll and generate initial, scaffolded website

grunt

Grunt will clean up your build with the grunt-contrib-clean to make sure that no artifacts from previous builds are hanging around.

Cleaning your build folder with grunt-contrib-clean

For production we want to use minified javascript to reduce the payload that is sent from the server. This can easily be accomplished with grunt-uglify.

Minifying your output with grunt-uglify

You can use Grunt to combine all of your Javascript files into a single concatenated file.

Concatenating Your Javascript with grunt-contrib-concat

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

With Grunt you can automate core tasks for your AngularJS project. In this lesson we will take a look at converting Stylus files to CSS, and add a watch task to convert those files automatically whenever a change is detected.

Development Automation Tasks with Grunt

Task automation is critical for any AngularJS single-page application. Grunt gets the job done.

Introduction to Grunt for Angular

Build and watch ECMAscript 6 using traceur compiler and Grunt.

traceur compiler and Grunt

Create a search directive with AngularJS and Rails. You'll want to take a look at the related [Rails TODO API Part 1](https://egghead.io/lessons/angularjs-rails-todo-api-part-1) and [Rails TODO API Part 2](https://egghead.io/lessons/angularjs-rails-todo-api-part-2). This is **not** a Rails how-to, so some knowledge there is expected to get up and running.

Search Directive with Rails

Expanding on [Part 1](https://egghead.io/lessons/angularjs-rails-todo-api-part-1), this lesson will look at how to bootstrap AngularJS in a rails application as part of the asset pipeline. With Angular available, you'll see how to communicate with the Rails API using $resource.

Rails Todo API Part 2

Rails makes an excellent choice for delivering data to AngularJS via REST apis. In this first lesson of a two part series, you'll see how to create a simple API for CRUD operations on TODOs using Rails. This isn't an introduction to Rails, and assumes you know the basics. 

Rails Todo API Part 1

 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

The GitHub CLI allows you to search issues and filter on different criteria like amount of comments. This allows you to search for real-world situations and pains/solutions people have using different technology. 

With the GitHub CLI in hand we'll drop 100s of issues as context in Googles AI Studio and have Gemini determine the 10 most frequently asked questions. This will give us a sense of how people use a library and where people get hung up.

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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