 Courses from Murphy Randle

Tailwind is a utility-first CSS framework for rapidly building custom user interfaces.

tailwind

This lessons shows how to dynamically add a red border to an input when a validation error pops occurs using ReasonReact, Tailwind, and re-classnames.

Dynamically style an input border with Tailwind and ReasonReact

Node.js is a well established server runtime that many companies are using worldwide. Express.js is a server framework for Node.js used by over 5 million projects. ReasonML is a type-safe functional language that compiles to Javascript.

This playlist collects the basic pieces of information a programmer needs to get started building servers in ReasonML on Node.js and Express.js. Follow along to learn how to get the speed of Node, combined with the added type-safety of Reason.

Node.js is a platform built on Chrome's JavaScript runtime for easily building fast, scalable network applications. Node.js uses an event-driven, non-blocking I/O model that makes it lightweight and efficient, perfect for data-intensive real-time applications that run across distributed devices.

node

Making an HTTP server in ReasonML on top of Node.js

This lesson shows how the Serbet server library for ReasonML and Node.js makes handling JSON request bodies, and responding with JSON request bodies a simple task.

Handle JSON request bodies and send JSON responses from a Node.js server using ReasonML

This lesson shows how to use the `serbet` npm package to write a simple Node.js http server in ReasonML by implementing a simple "hello world" endpoint. Serbet is a convenient wrapper around Express.js. It's a young library, but its patterns are already used in production code.

Make a basic server with ReasonML and Node.js

Simple, fast & type safe code that leverages the JavaScript & OCaml ecosystems.

reason

Decco is a language extension that automatically generates JSON encoders and decoders from type signatures. When adding adding custom Decoders, the error messages that the compiler produces can be quite confusing. This lesson shows the viewer how to use explicit type signatures to narrow down where an error might be coming from in custom codec code. This same pattern can be applied whenever confusing error messages come from code that is written without explicit type signatures.

Working with cryptic error messages from ReasonML when writing custom Decco decoders.

Decco is a great library for automatically generating JSON encoders and decoders, but most real-world projects will quickly run into the need to add custom data types that Decco doesn't ship with support for. This lesson shows how to simply add a custom data type by implementing a codec that reads and writes Javascript dates as floats.

Write a simple custom JSON decoder for Decco in ReasonML

Although ReasonML has built-in libraries for working with JSON, they are low-level and difficult to use by hand. The Decco library offers automatically generated JSON decoders, and produce a result that keeps the programmer safe at runtime by telling them whether the data they got matched the shape of the data they expected. 

Automatically decode JSON into records in ReasonML using Decco

ReasonML is a fantastic way to write Javascript! But it doesn't yet have a built-in async / await syntax. Furthermore the built-in libraries for working with Javascript promises are awkward to work with, and produce code that's hard to read. This lesson will teach the viewer how to use the "bs-let" language extension (called a PPX) to achieve readable, easy to write promise-based code.

Async / Await in ReasonML

Elm is a programming language that provides a clean functional syntax for writing HTML web applications. It promises zero runtime exceptions, fast rendering, time-travel debugging, and much more.

Turning JSON strings into types, also known as JSON Decoding is an important part of using Elm. It allows the programmer to use json-encoded data while staying completely aware of when the JSON might not match the programmer's expectations, all without throwing a run-time error! This lesson will show the viewer how to turn a simple JSON object into an analogous Elm record and use it to render some content to the screen.

Turn a JSON string Into Typed Data in Elm

The Hypertext Transfer Protocol (HTTP) is an application-level protocol for distributed, collaborative, hypermedia information systems. It is a generic, stateless, protocol which can be used for many tasks beyond its use for hypertext, such as name servers and distributed object management systems, through extension of its request methods, error codes and headers.

http

Understand the three basic parts of making HTTP requests in Elm: 1) Building the request, 2) Writing a JSON decoder, 3) Sending the request using the Elm runtime, and reacting to the results with messages.

HTTP requests are just pieces of data in Elm. When we want to send them, we hand them off to Elm's runtime, and it notifies us when the request is done. An important part of working with HTTP requests that fetch JSON is JSON decoding, the process by which we can turn untyped JSON data into Elm types that are safe to work with.

Specs:

- Editor: Atom
- Theme: [Nebula (with Nebula syntax theme)](https://atom.io/themes/nebula-ui)
- Font: [Iosevka with ligatures enabled](https://github.com/be5invis/Iosevka)
- Plugin used for imports: [Elmjutsu](https://atom.io/packages/elmjutsu)
- Plugin used for formatting: [Elm-format](https://atom.io/packages/elm-format)
- Plugin used for linting: [linter-elm-make](https://atom.io/packages/linter-elm-make)


Make an HTTP Request in Elm

Decoding JSON strings in Elm is a 2-step process:

1. Create a "recipe" for the decoding
2. Perform the decoding

This lesson gives a couple basic examples of the two steps in action.

Decode a List of Numbers From a JSON String in Elm

**Notice**:  This lesson uses Elm 0.17!

[Here's a document about the important differences between 0.16 and 0.17](https://github.com/elm-lang/elm-platform/blob/master/upgrade-docs/0.17.md).

This lesson gives a rapid-paced introduction to what's known as the Elm Application Architecture. You can read about it in greater detail here:

[guide.elm-lang.org](http://guide.elm-lang.org/architecture/index.html).

We'll build a counter that utilizes the standard Elm combination of a model, a view, and update function.

See the linked code for a good starting place.

Build a Tiny App Using the Standard Elm Architecture

Elm includes a data type called `Maybe` which is useful for working with values that may, or may not exist. This lesson shows a simple case where maybe types are encountered, and how to make them useful.

Using "Maybe" in Elm for values that may or may not exist

This lesson will take you from nothing to a small Elm app that prints text to the browser.

Create your first web page with Elm

Cursor's default inline edit (`Cmd+K`) has scope limitations, and using the full chat (`Cmd+I`) for simple refactors can be overly conversational. This lesson demonstrates how to create a custom chat mode specifically configured for direct code editing. By setting up a dedicated mode with custom instructions and a keybinding (like `Cmd+E`), you can bypass unnecessary AI chatter and apply targeted, file-aware modifications more efficiently than standard methods.

**Workflow Demonstrated in this Lesson:**

*   Create a "Custom Mode" within Cursor's chat interface.
*   Assign a name (e.g., "Edit") and a preferred AI model.
*   Set a dedicated keybinding (e.g., `Cmd+E`).
*   Configure allowed tools (enable `Edit`, disable `Run`/`MCP`).
*   Use "Advanced options" to enable `auto-run`.
*   Add "Custom instructions" to prompt the AI for direct edits without explanation.
*   Trigger the mode with the keybinding on a code selection to perform edits beyond the selection's scope (e.g., hoisting variables).

**Key Benefits:**

*   Perform refactors and edits beyond the scope of the initial selection, overcoming `Cmd+K` limitations.
*   Achieve a more direct, less "chatty" AI editing experience compared to standard chat (`Cmd+I`).
*   Streamline common AI-assisted modifications with a dedicated keybinding.
*   Gain fine-grained control over the AI's editing behavior using custom instructions.

**Want to Learn More? Sign-up for my Cursor Workshop!**

[https://egghead.io/workshop/cursor](https://egghead.io/workshop/cursor)

John Lindquist

Build a Better Edit Tool in Cursor with Custom Agent Modes

Stop waiting for a single AI agent! This lesson demonstrates a powerful workflow to massively parallelize your AI-driven development in Cursor. Learn how to use tools like `file-forge` to package your project context, prompt advanced AI models (like Gemini in AI Studio) to brainstorm features and generate setup scripts, and then leverage a custom `git worktree` CLI tool (`wt`) to automatically launch an "army" of isolated Cursor instances, each tackling a different task on its own branch.

**Workflow Demonstrated / Key Benefits:**

*   **Bundle Project Context:** Use `file-forge` to create an AI-friendly representation of your codebase.
*   **AI-Powered Brainstorming & Scripting:** Prompt a reasoning model (e.g., Gemini via AI Studio) to suggest features *and* generate a shell script (`zsh`/`bash`) to automate setup.
*   **Automated Worktree Creation:** Execute the generated script which uses a custom `git worktree` CLI (`wt`) to:
    *   Create new branches and worktrees for each suggested feature.
    *   Install dependencies automatically (e.g., `pnpm install`).
    *   Launch multiple, isolated Cursor instances.
*   **Parallel AI Development:** Assign different features or implementation approaches to each Cursor agent (Composer) simultaneously.
*   **Efficient Monitoring:** Easily switch between active Cursor projects/worktrees using `Ctrl+R` or OS spaces.
*   **Seamless Integration:** Merge completed features back into your main branch using `wt merge` or use agents to commit, push, and create Pull Requests via the GitHub CLI (`gh pr create`).
*   **Boost Productivity:** Dramatically speed up iteration and experimentation by running multiple AI agents concurrently without conflicts.

This approach transforms your workflow, allowing you to explore multiple development paths simultaneously and integrate the best results efficiently using standard Git practices.

**Resources** 

[https://www.npmjs.com/package/@johnlindquist/worktree](https://www.npmjs.com/package/@johnlindquist/worktree)
[https://www.npmjs.com/package/@johnlindquist/file-forge](https://www.npmjs.com/package/@johnlindquist/file-forge)

**Want to Learn More? Sign-up for my Cursor Workshop!**

[https://egghead.io/workshop/cursor](https://egghead.io/workshop/cursor)

Swarm Intelligence: Massively Parallelize Your AI Agents in Cursor

Creating powerful and context-aware tools for Cursor IDE becomes straightforward when leveraging information directly from your current project. In this lesson, you'll learn how to build a custom MCP (model context protocol) tool that intelligently requests essential details—such as the current project path and conversation summaries—from your Cursor project.

Workflow demonstrated in this lesson:

- Define MCP tool parameters to request specific project details.
- Pass project path and conversation summaries into your MCP tool.
- Automatically write or update files within your current project using these parameters.

Key benefits:

- Automate tasks with precision based on your active project's context.
- Simplify interactions by creating AI-driven CLI commands tailored to your needs.
- Open endless possibilities for integrating external APIs and advanced automation.

Through this practical demonstration, you'll gain a versatile technique for enhancing your development workflow in Cursor IDE.

[https://github.com/johnlindquist/mcp-cursor-tool-starter](https://github.com/johnlindquist/mcp-cursor-tool-starter)

Build MCP Tools Using Project Context for Custom Cursor IDE Automation

Setting up custom MCP (Machine Command Protocol) servers in Cursor can involve tedious steps, such as configuring node paths or referencing additional commands. This lesson shows how to streamline this process by bundling your MCP server directly into a standalone executable.

Workflow demonstrated in this lesson:

- Use a simple MCP server project starter.
- Run a single bundling command to create an executable.
- Right-click the generated executable, copy its full path, and add that directly to your Cursor settings.

Key benefits:

- Eliminates the need for complex node path configurations.
- Simplifies the setup and integration of custom MCP servers into Cursor.
- Makes the server executable instantly accessible within your Cursor environment.

By following this streamlined approach, you can quickly and easily integrate custom MCP servers into Cursor, making your development workflow cleaner and more efficient.

[https://github.com/johnlindquist/mcp-cursor-tool-starter]()

Easy MCP Server Setup in Cursor IDE with Bundled Executables

TanStack Router is the foundation for TanStack Start, which is gaining significant attention due to its innovative approach to application development.

This course focuses on getting effective TanStack Router, a modern and scalable routing solution for React applications. You will learn how to:
- set up and scaffold new applications,
- use file-based routing
- create nested routes
- manage dynamic route parameters and more.

The course covers advanced features like route loaders, caching strategies, and lifecycle hooks, which are crucial for enhancing application performance and user experience.

By understanding TanStack Router, you can build more efficient, type-safe, and maintainable applications, leveraging its integration with data fetching libraries like TanStack Query.

This knowledge is essential for developers looking to improve their routing skills and stay ahead in the field.

Tomasz Ducin

Up and Running with Tanstack Router and React

Learn TanStack Router for React: set up apps, use file-based routing, manage routes, and boost app performance.


In this lesson, we explore how TanStack Router integrates with the [native browser history API](https://developer.mozilla.org/en-US/docs/Web/API/History) to manage navigation.

As we navigate through different routes, the URL changes are stored in the browser's history, allowing users to use the forward and backward buttons to traverse their navigation history.

This functionality also **enables permalinks**, meaning users can copy and paste URLs to access specific routes directly.

Additionally, we learn how to programmatically interact with the history object to move forward or backward through the navigation stack, enhancing the user experience by providing full control over navigation actions.

This compatibility with the native history API ensures that TanStack Router applications behave similarly to traditional websites, offering a seamless and intuitive user experience.

Browse History in Tanstack Router

Browse history in TanStack React Router using the native history API for seamless navigation

In this lesson, we explore how to hook into TanStack Router's lifecycle hooks to execute custom logic during route changes.

The hooks we'll look into are: `onEnter`, `onStay`, and `onLeave`, which are triggered when entering, staying within, or leaving a route, respectively.

All hooks receive a detailed match parameter, providing information about the route's path, ID, and tons of other details.

This allows for the implementation of features like animations or logging when navigating between routes.

We also learn how to use these hooks to track and manage state changes as users interact with the application, making it easier to implement complex behaviors based on route transitions.

Hook into Route Lifecycle Hooks in Tanstack Router

Hook into TanStack React Router's lifecycle hooks for custom route logic and animations.

In this lesson, we learn how to handle not found errors in TanStack Router by using the `notFoundComponent` at both nested and global levels.

To trigger the display of a `notFoundComponent`, we must throw a specific error using the `notFound` function within a loader or other lifecycle method of a route. This approach allows us to provide custom error messages for specific routes or globally across the application.

We explore how to define a notFoundComponent within a specific route's configuration and how to set a `defaultNotFoundComponent` at the router global level, which applies to all routes unless overridden locally. This flexibility ensures that users receive meaningful feedback when encountering non-existent routes.

Provide NotFoundComponent at Nested Route or Global Level in Tanstack Router

Handle notFound errors in TanStack Router with notFoundComponent at nested or global levels.



In this lesson, we learn how to access dynamic route parameters using the `useParams` hook in TanStack Router.

When used with a specific `Route` object, `useParams` provides type-safe access to route parameters, ensuring that TypeScript knows the exact types of these parameters.

This approach eliminates the possibility of undefined/optional values, making it safer for accessing parameters like `employeeId`.

However, when using `useParams` globally without specifying a route, it requires an options object with `{ strict: false }`, which reduces type safety.

In this case, the hook can access parameters from any route in the application, but it does not guarantee their existence or type. This flexibility allows components to be reused across different routes, but it requires careful handling of potential errors.



Access Dynamic Route Parameters with useParams in Tanstack Router

Access dynamic route parameters with useParams in TanStack React Router for type-safe routing.

In this lesson, we learn how to reorganize file-based routes in TanStack Router to accommodate nested routing structures.

We explore how to create additional nested routes by converting files into directories, allowing for further nesting.

For example, to create a nested route like `/employees/$employeeId/edit`, we can create a **directory** (!) named `$employeeId` and place an `index.tsx` file inside it to define the route component for this nested route.

This approach provides flexibility in organizing files while maintaining the convention that file names and locations align with route paths. We also see how to adapt existing components and loaders to work with these reorganized routes, enabling features like edit forms or delete actions (or whatever) within nested routes.


Reorganize File-Based Routes in Tanstack Router

Reorganize file-based routes in TanStack Router for flexible nested routing.



Murphy Randle

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