Learn Elixir, Go and Reactfire

Elixir is a dynamic, functional language designed for building scalable and maintainable applications.

Elixir leverages the Erlang VM, known for running low-latency, distributed and fault-tolerant systems, while also being successfully used in web development and the embedded software domain.

elixir

Some common uses for pattern matching in Elixir include checking conditions and passing parameters into functions. It's useful for pulling out only specific variables from collections of data.

Additional resources:
- [Elixir docs on pattern matching](https://elixir-lang.org/getting-started/pattern-matching.html)

Pattern match in conditions and function parameters in Elixir

Elixir uses `=` as an operator, but rather than assigning values to variables with it, it *matches* values on the right hand side of the `=` with the left side. This can be used in simple values, more complex data structures, and powerful condition checking.

Put into simpler terms, pattern matching is Elixir's way of assigning variables.

Additional resources:
- [Elixir docs on pattern matching](https://elixir-lang.org/getting-started/pattern-matching.html)

Pattern match values in Elixir

These videos include the introductory steps to writing your first Elixir function and beginning to understand some key concepts in Elixir that make it unique. 

Some of those concepts include:
- the Mix build tool
- project structure
- collections of functions written in modules
- function *arity*
- pattern matching and common uses for it
- the pipe operator

Getting Started with Elixir

The syntax to pass arguments into functions is akin to many other languages. Elixir functions are uniquely recognized when running based off of the number of arguments passed in (a term called *arity*). This means you can define functions with the same name, so long as a different number of arguments is passed in.

Arity is a key concept to be aware of when reading documentation and writing your own code.

Additional resources:
- [Information about arity](https://elixir-lang.org/getting-started/modules-and-functions.html#function-capturing)
- [Default arguments in functions](https://elixir-lang.org/getting-started/modules-and-functions.html#default-arguments)

Pass arguments into Elixir functions and understand arity

Elixir code is organized into groups of functions called modules. You can create your own modules and built on top of predefined modules that are a part of Elixir by default.

Additional resources: 
- [Getting started with Modules and function from Elixir docs](https://elixir-lang.org/getting-started/modules-and-functions.html)

Write a New Function Inside of an Elixir Module

Bootstrap a new Elixir project using Mix (a build tool included when you install Elixir), with its built in project generation.

Additional resources:
- [Official introduction to Mix](https://elixir-lang.org/getting-started/mix-otp/introduction-to-mix.html#our-first-project)

Generate a new Elixir project using Mix

Go is a server-side language, but today we can compile Go code to WebAssembly as well - making it possible for us to bring programs written in minimalistic Go code into the browser!

With this collection, we will learn how to compile and run Go WebAssembly programs in Node.js and the browser, and how our Go code can interop with JavaScript and manipulate the DOM. We will also talk about configuring our VS Code workspace and optimizing the Go WASM binary size.

Go is an open-source programming language that makes it easy to build simple, reliable, and efficient software.

WebAssembly with the Go Language

*Go ^1.12*

When using Go modules related to WebAssembly, namely `syscall/js`, the default settings in VS Code will trigger error reports like *"Build constraints exclude all Go files"* in the editor. In this lesson, we will learn how to fix this and improve our coding experience.

Configure Go Build Constraints in VS Code to work with WebAssembly

*Go ^1.12*

In this lesson, we will see how we can expose Go lang functions from a WebAssembly module so that we can interact with them from the JavaScript environment.

Call a Go WebAssembly function from JavaScript

*Go ^1.12*

The ability to manipulate the DOM is sometimes crucial when it comes to working with apps powered by WebAssembly. In this lesson, we will see how we can utilize Go's `syscall/js` module to interact with the DOM by porting a sample JS code snippet to Go.

Interact with the DOM using Go's `syscall/js` module

*Go ^1.12*

In this lesson, we will see how we can interact with the JavaScript environment by using Go's `syscall/js` module to call and pass values into a JavaScript function, and access variables available in JS land.

Access JS Functions and Variables from a Go WebAssembly Program

*Go ^1.12*

In this lesson, we will learn how to load and use a Go WebAssembly binary in a web app.

Manually load a Go WebAssembly binary in a browser

*Go ^1.12, TinyGo ^0.12.0, Node ^12.14.0*

The WebAssembly binaries generated by the standard Go compiler are often unnecessarily large. In this lesson, we will learn techniques to optimize Go Wasm binary size with an alternative compiler that is designed for microcontrollers - TinyGo.

Optimize Go WebAssembly binary size with TinyGo

*Go ^1.12, Node ^12.14.0*

Compiling Go programs to WebAssembly does not require Emscripten, and the process is pretty straight forward. In this lesson, we will learn how to compile a simple Go program to a WebAssembly binary, then execute it with Node.js.

Compile and execute a Go WebAssembly program with Node

There are numerous ways to sort slices in Go.

In this lesson, we will take a quick look at an easy way to sort a slice of structs or primitives. We will learn about using one of the handy built-in functions in Go's sort package called *sort.Slice*. This function takes a slice to sort as an argument and a *less function* or *less func* for short as the second argument. You will write this *less function* to sort the slice however you wish.

Go's sort.Slice function looks like this: *sort.Slice(someSlice, func(i, j int) bool)*. It's super-easy to write an anonymous *less function* to sort.

As you will see, it's easy to use this *less function* to do simple and even complex sorts of your structs with minimal effort.

Sort Slices of Structs using Go sort.Slice

There are numerous ways to sort slices in Go.

The simplest way uses some basic built-in functions from Go's **sort** package to allow you to easily sort slices of primitives, that being **Strings**, **Ints** and **Float64s**. Using these sort functions, we don't have control over the sort order as the data will be sorted in ascending alphabetical (for strings) or ascending numerical (for Ints and Float64s) order.

In this lesson, we will take a quick look at the easiest way to sort slices of primitives. We will learn about using some of the handy built-in functions in Go's sort package, including:

* sort.Strings: Sorting a slice of strings
* sort.Ints: Sorting a slice of ints
* sort.Float64s: Sorting a slice of float64s

Sort Primitives (strings, ints, and floats) in Go 

This collection of lessons will cover a variety of topics that teach you how to work with slices and arrays in go. You'll learn how to declare them, create them using literal syntax, iterate over them, add to them, remove from them and other useful things.

Learn about slices and arrays in Go

Go has a special indexing syntax that forms the basis of removing one or more elements from a slice. I will teach you this syntax and show you its various forms.

Based upon that, I'll show you how to remove a single element from a slice. However, you may find this somewhat limiting. I also will show you a more typical example of removing elements from a slice as we iterate over it. This technique shows you how to remove multiple elements from a slice.

Remove Elements from a slice in Go

There are a couple of different ways to iterate over an array or slice in Go. The primary approach is to use range, which handles the iteration for you. However, you can also use a traditional for loop if you need to do something out of the ordinary, like iterating in reverse or skipping every other element.

Iterate over an Array or Slice in Go

There is a built-in append function that is used to append elements to a slice. We'll see in this lesson that the append function works only with slices, not arrays. There are also some nifty alternate uses of the the append function that make appending super easy.

Checkout the sample code in my [github repo](https://github.com/JeffBNimble/GoLessons/tree/master/Array-Add).

Append Elements to a Slice in Go

There are numerous ways that you can declare and create arrays and slices in Go. This lesson will show you several and I talk about the advantages and disadvantages of one over another. After watching, you will better understand all of the possible ways you can declare/create as well as the idiomatic way.

These include:

* var
* the built-in function *new*
* the built-in function *make*
* Array and Slice literals

While it is not the main intent of this lesson, I do touch on some of the differences between slices and arrays.

Checkout the code in my [github repo](https://github.com/JeffBNimble/GoLessons/tree/master/Array-Declare).

Declare Arrays and Slices in Go

 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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