Learn Babel, Flow and Lighthouse

React is one of the web’s most popular frameworks for building JavaScript applications. 

If you know what you’re doing, React can drastically simplify how you build, use, and maintain code.

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react

We take the opengraph image we wrote in codesandbox and copy it into our serverless function. We use Rollup to compile the component into an IIFE (immediately invoked function expression) that can run in our headless browser environment and cover a wide set of rollup plugins that we need for compatibility. We end the lesson having successfully screenshot our opengraph react component from our Netlify Function

**Note**:  Due to Netlify changing their handling, the path in `fs.readFileSync` is affected. Update to:
```js
const script = fs.readFileSync(path.resolve(__dirname, "image.js"), "utf-8");
```

Compiling a React to an IIFE with Rollup to execute and render in a headless browser

Babel has support for the latest version of JavaScript through syntax transformers. These plugins allow you to use new syntax, right now without waiting for browser support.

babel

In this lesson, we'll configure webpack to use the Babel loader for our JavaScript files, allowing us to transpile our source files and generate a bundle for deploying our application.

Configure webpack to Load JavaScript Files through Babel with babel-loader

Converting all of our modern JavaScript into ES5 compatible syntax is a great way to use modern features while targeting older browsers. What happens when the browsers natively support these language features? Then it no longer makes sense to transform that code or to include polyfills that will go unused. In this lesson, we’ll add the `@babel/polyfill` package and configure `babel-preset-env`

Target specific browsers with babel-preset-env and the babel pollyfill

We transpile our JavaScript code so we can use modern language features, even if browser support isn't quite where we need it to be. This includes proposed features that aren't yet part of the official language specification. In this lesson, we'll see how we can support the proposed class property syntax for JavaScript with a Babel plugin.

Support Proposed JavaScript Features with Babel Plugins

One approach to building high performance applications with `webpack` is to take advantage of code-splitting to only load the needed JavaScript on initial load and asynchronously load additional JavaScript bundles when needed. In this lesson, we'll create add some code-splitting to our placeholder application and configure our project to support the dynamic `import()` syntax.

Asynchronously Load webpack Bundles through Code-splitting and React Suspense

In this lesson, we'll add React and ReactDOM to our project and create an entry point for the React application. We'll also configure Babel with the React preset so Babel can transpile our JSX into JavaScript that will run in a browser.

Configure babel for React with preset-react

In this lesson, we’ll install Babel and use it from the terminal to see how it can take JavaScript that uses modern language features and output JavaScript that will run in down-level browsers.

Transform Modern JavaScript Features with Babel

In this lesson we are going to add types throughout our basic todo list component. This includes type checking the component props, local state, and property methods. 

Type Check React Components With Flow

In this lesson we are going to take a React and Redux application and add flow types throughout. This includes type checking a react component, a reducer, some actions, and a connect method. 

Type Check Redux Apps with Flow

flow

We'll go over some of the built-in types in Flow and how to add them to our projects by adding type annotations to our variables in JavaScript. We'll also learn about type mismatch errors when we give a variable a value that doesn't match its type annotation and how to fix it.

Primitive Types in Flow

Nuclide is the IDE Facebook employees use to write React code. But setting it up to use Flow type checking and Eslint to lint files on the fly is tricky. This video shows you how. 

Setup Nuclide to use Flow and Eslint (Mac)

Let's learn how to set up Facebook's Flow inside of a project and write a simple typecheck task that will let us run Flow against any files in our codebase.

Up and Running with Facebook Flow for Typed JavaScript

What is already a nice workflow using Gulp, Browserify, Watchify & Browsersync to enable auto rebuilds & live browser reloading can be further improved by adding Babelify. A simple wrapper around the popular transpiler Babel, Babelify can ‘transform’ source files as they pass through our stream to enable certain Javascript features not yet available in the Browser or Node. We end the lesson by looking at how to generate & extract sourcemaps using `exorcist`.

Gulp and Browserify - Adding Babel & Source Maps

<p>Henry Zhu is currently a steward for Babel, and today he'll be discussing the management and lifestyle side of working on an open source project full-time.</p><p>The financial side to open source is interesting. Henry talks about where he gets his money and how he can be financially independent while still working on open source full time. Most of the money comes from donations through Open Collective and Patreon. A lot of the donations come from users, but corporations do donate as well. Henry also discusses the stability of it, and how the NPR model of asking for donations can lead to uncertainty about the next month.</p><p>Henry says he's enjoying the management and marketing side of being a steward about as much as he enjoys coding. It's a side that people don't often think about with open source. This side of it includes a lot of marketing and interacting with the greater community, as well as the other maintainers and contributors to babel.</p><p>How does Henry handle all this responsibility when there is no one above him telling him when to take a break, or when to go on vacation? Henry and Joel talk about having a positive "selfishness", and taking care of yourself so that the project can prosper. If you want to be doing it for years you have to make sure that you don't burn out.</p><hr /><h3>Transcript</h3><p><a href="https://egghead.simplecast.com/episodes/henry-zhu/transcript">"Henry Zhu, Maintainer of Babel" Transcript</a></p><h3>Resources:</h3><ul><li><a href="https://babeljs.io/">Babel</a></li><li><a href="https://www.amazon.com/Power-Habit-What-Life-Business/dp/081298160X">The Power of Habit</a></li><li><a href="https://www.amazon.com/You-Are-What-Love-Spiritual/dp/158743380X">You Are What You Love</a></li><li><a href="https://www.tinyhabits.com/">Tiny Habits</a></li><li><a href="https://kaidavis.com/articles/">Kai Davis</a></li></ul><h3>Henry Zhu:</h3><ul><li><a href="https://twitter.com/left_pad?lang=en">Twitter</a></li><li><a href="https://www.henryzoo.com/">Website</a></li><li><a href="https://github.com/hzoo">Github</a></li><li><a href="https://www.patreon.com/henryzhu">Patreon</a></li><li><a href="https://opencollective.com/babel#">Open Collective</a></li></ul><h3>Joel Hooks:</h3><ul><li><a href="https://twitter.com/jhooks">Twitter</a></li><li><a href="https://joelhooks.com/">Website</a></li></ul>


Today, Henry Zhu, the lead maintainer of Babel, discusses what it's like to work on a large and important open source project. Henry gets into how Babel receives funding, how corporations are involved in open source, stewardship of an open source project, mental and physical health, and not compromising his values.  

Henry Zhu, Maintainer of Babel

 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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