Learn Algolia, Ios and Redwoodjs

Today’s users expect great things from their search experiences — speed, relevance, and usability, to name a few. Algolia provides developers with out-of-the-box and customizable search experiences that are a joy to build.

This introductory course on the Algolia search solution focuses on the user-facing part of search. Using the Algolia InstantSearch.js front-end library, we’ll see how to build an engaging search experience in no time. (28 minutes, to be exact.) 

**Prerequisites:** 
You don’t need previous experience with search to follow this course — we’ll use an example index with an e-commerce data set preconfigured. We will work mainly in JavaScript, so basic JS knowledge is expected.

If you want to play with your own index settings and data set, you can [create a free Algolia account here](https://www.algolia.com/users/sign_up/hacker/?utm_medium=link&utm_source=egghead&utm_campaign=education), but this is not required to follow along with this first course. 

Algolia's full suite APIs enable teams to develop unique search and discovery experiences for their customers across all platforms and devices. Type a query. Click a link. Open an app. Everything your customers do sends a signal about what they want. Algolia decodes that intent to deliver the right content - instantly.

algolia

Getting Started with Algolia InstantSearch.js

The stats widget is used to display useful insights about the current results like the number of hits and the time taken to compute the results inside the engine.

Inform users about the current result set with Instantsearch JS Stats widget

When you have a large result set for a specific query and usually not displaying more than a few dozen simultaneously. Pagination is a popular widget that allows the user to switch between pages of the results.

Paginate Large Sets of Algolia Data with Instantsearch JS Pagination widget

When performing a complex query, based on several active facets and filters, its tedious for the user to start from scratch if she has to unset all refinements one by one. Thanks to the clearAll widget, this task becomes a one click action for the user and is trivial to implement for us developers as it requires no configuration.

Reset all active refinements with the clearRefinements Instantsearch JS widget

The range input is a simple but useful widget that allows a user filter the results by selecting a numeric range with a minimum and maximum input. In an e-commerce website for instance, this widget would be useful to limit the results where the price is comprised between $X and $Y.

Refine a dataset using a numeric range in Instantsearch JS with the Range Input widget

The hierarchical menu widget is used to create a navigation based on a hierarchy of facet attributes. We generally implement it for categories with subcategories.

Browse results based on a hierarchy of Facets (HierarchicalMenu) in Instantsearch JS

Searching is obviously not limited to inputting text in a searchbox. If your dataset allows it Algolia can leverage of attributes and values. To make use of those facets on the front end, one of the most common widget that you can find in a search UI is the refinement list. With this widget, the user can filter the dataset based on facets. This widget only displays the most relevant facets for the current search context.

Filter Datasets with Facets using Instantsearch JS to add a Refinement List

Every  good search UX make users understand instantly why a given hit is being displayed as part of the result set. One way to achieve that is to highlight the keywords from the query directly inside the Hits. This is built in the API JSON response and in this video we’ll explain how to leverage it easily.

Highlight Keywords in Query Results using the Instantsearch JS Hits Widget

Displaying barebones Hits won’t catch your user’s attention. The UI is key to provide a good search experience and hits are the meat of this experience so they need extra attention. By using Mustache templating we’ll see how to display rich results to your users. 

Display Rich results with templates in the Hits widget for Instantsearch JS

In this lesson we’ll build a search experience reduced to it’s 2 essential components : a search input and the displayed results. As simple as it is, to build this from scratch would require a fair amount of work. Between listening to the input, making the api call, parsing and displaying the result... To build this using Algolia’s Instantsearch library requires a few lines of code with simply two widgets: the Searchbox and the Hits widget.

Search an Algolia Index with Instantsearch JS searchbox and hits widgets

All Instantsearch widgets are added to the page in a similar fashion and they also share a number of common options that we’ll cover in this video. We will be playing with a dummy menu widget that won’t be part of the final project just to showcase all those options.

How to Add Instantsearch JS widgets and their common attributes 

The first step to implement Algolia on the front end using Instantsearch : importing and setting up the library with your credentials. This is what will allow the library to initiate the connection to Algolia servers and the first step to complete before adding some useful widgets.

Set up the Instantsearch JS Library

React Native lets you build mobile apps using only JavaScript. It uses the same design as React, letting you compose a rich mobile UI from declarative components.

react-native

Once our app is finally complete, we have to build it in a special way in preparation for uploading to the iOS app store.  We’ll look at exactly how to build and upload the app to the app store, which will allow us to release to beta users using TestFlight, or to release publicly on the store!

Build an iOS React Native App for Uploading to the iOS App Store or TestFlight

Once navigation is setup, we’ll pass data between screens using params.  

Pass Data Between Screens when Navigating with StackNavigator

React Native uses Flexbox to layout most components, which makes it easy to run your app on devices of many different screen sizes.  We’ll learn the basics of Flexbox in React Native, and how to use it to build a flexible screen layout.  We’ll also look at some differences between flexbox on the web and on mobile.

Layout React Native Components with Flexbox

In this lesson we’ll use `fetch` to get data from an HTTP server, and store it in state in our React Native application. `fetch` works almost identically on the web and React Native - with the possible exception of how it handles cookies.  We’ll also take a look at `axios` - which is an alternative to `fetch`.

Fetch Data from an HTTP Server in a React Native Application using fetch or axios

React Navigation’s StackNavigator has a default header, which you may or may not want for your application.  We’ll look at how to totally disable the header, as well as how to customize the default header on a per-screen basis.

Customize the StackNavigator Header with React Navigation in a React Native App

We’ll use React Navigation to add a modal screen to our app, which will pop up from the bottom, and cover the entire screen. 

Add a Modal Screen that Pops Up from the Bottom with React Navigation

If a Text Input is on the bottom half of the screen, then it will get covered by the on screen keyboard when a user selects that input.  We’ll show two ways to automatically avoid this by using `KeyboardAvoidingView` or `keyboard-aware-scroll-view`

Ensure Text Fields Don't Get Covered by the On Screen Keyboard

Once the user submits the form, we’ll take all the information in the text inputs and the camera image, and upload it to our HTTP server.  While the data is uploading, we’ll show the native spinner, and disable the submit button so the user cannot click submit multiple times.

Show a Spinner while Submitting a Form in React Native with ActivityIndicator

We’ll use `AsyncStorage` to save and load simple text data on the device.  `AsyncStorage` is built into React Native (so it’s easy to get working), but it’s text only, it’s global to your app, and it isn’t built to handle large or complex data.  However - it’s perfect for saving and loading small bits of data like settings and configuration values.

Save and Retrieve Data on the Device in a React Native App with AsyncStorage

Hey Everyone 👋,

John Lindquist here with the third issue of AI Dev Essentials! Another week, another whirlwind of updates in the AI development space. We saw Google drop Gemini 2.5 Flash, OpenAI counter with o3/o4-mini and a new Codex CLI, Anthropic beef up Claude with research tools, and continued evolution in the MCP and agent framework landscape. Personally, I've been digging into Gemini 2.5 Flash – it's impressive to see Google pushing the performance frontier for smaller models and comparing it directly against the competition like O4-mini. Let's dive in!

___

### New egghead.io Lesson This Week:

* **[Generate and Debug MCP Servers from Scratch using GitHub Examples and AI](https://egghead.io/generate-and-debug-mcp-servers-from-scratch~k98ad):** Building complex components like Model Context Protocol (MCP) servers from scratch can be challenging, especially without good reference implementations. This lesson demonstrates a powerful workflow combining the `ghx` CLI tool (a wrapper I built for the GitHub CLI - find it [here](https://www.npmjs.com/package/@johnlindquist/ghx)) with AI assistants (like Google's AI Studio and Cursor's agent) to overcome this hurdle. Learn how to scrape real-world examples from GitHub using `ghx` ([see scraped examples here](https://gist.github.com/johnlindquist/b19673bbf6a396406dff869beecace1d)), feed them to an AI to generate a new server, and then integrate and debug it within Cursor. It's a practical look at bootstrapping complex tools using AI and targeted code searching.

___

Here are the highlights that caught my eye this past week:

## Model & Major Platform Updates

* **Gemini 2.5 Flash Arrives:** Google released Gemini 2.5 Flash ([Google Developers Blog](https://developers.googleblog.com/en/start-building-with-gemini-25-flash/)), their first unified reasoning model with thinking budgets. It's positioned as a high-performance, cost-effective option. Notably, Google's benchmarks included comparisons against OpenAI's very recent O4-mini, drawing praise for transparency ([Nathan Lambert](https://x.com/natolambert/status/1912958672881303943)). It's available via the Gemini API, AI Studio, Vertex, and the Gemini app. The [Live API docs](https://ai.google.dev/gemini-api/docs/live) are also updated.
* **OpenAI Counters with o3/o4-mini & Codex CLI:** OpenAI launched [o3 and o4-mini](https://openai.com/index/introducing-o3-and-o4-mini/), highlighting their agentic capabilities and tool use during Chain-of-Thought. Alongside these, they released the open-source [Codex CLI](https://github.com/openai/codex), a coding agent designed to leverage these new models. Interestingly, the OpenAI dev behind Codex CLI was spotted [using Cursor](https://x.com/chuhang1122/status/1912786904812294312).
* **Claude Gets Research Superpowers:** Anthropic rolled out a major [Claude upgrade](https://x.com/jowettbrendan/status/1912446262756151732) introducing a "Research" agent capability. It can search the web and internal docs, chain queries, and explore topics agentically, building citations along the way. They also added Google Workspace integration (Gmail, Calendar, Docs) for paid users. (Official blog post link pending confirmation).
* **Cursor 0.49 Update:** The latest Cursor update ([Changelog 0.49](https://www.cursor.com/changelog/0-49)) brings several enhancements: improved Cursor Rules generation and attachment, better chat history access, built-in diff reviews, image support in MCP context, agent command editing/skipping, global ignore files, added models (Gemini 2.5 Pro, Grok 3, GPT-4.1), and project structure context for the agent. [AGIdevice](https://x.com/agidevice/status/1913575514670776520) shows how to enable the beta features.

## Tooling & Protocol Developments

* **MCP Nuances:** David Cramer cautioned against simply [proxying OpenAPI specs via MCP](https://x.com/zeeg/status/1913289979368796671), arguing it misuses the protocol and ignores LLM limitations in tool selection and JSON handling.
* **MCP Transport Clarification:** Harald Kirschner clarified the newer "Streamable HTTP" transport ([MCP Spec](https://modelcontextprotocol.io/specification/2025-03-26/basic/transports)), noting it's primarily HTTP-based, with Server-Sent Events (SSE) as an optional upgrade for streaming server messages, deprecating the older standalone SSE transport. Discussions on implementation and future streaming enhancements are ongoing ([TS SDK Issue #220](https://github.com/modelcontextprotocol/typescript-sdk/issues/220), [MCP Roadmap](https://modelcontextprotocol.io/development/roadmap)).
* **Agent2Agent (A2A) Protocol Announced:** Google unveiled the Agent2Agent (A2A) protocol ([Google Developers Blog](https://developers.googleblog.com/en/a2a-a-new-era-of-agent-interoperability/)), an open standard aiming to allow AI agents from different frameworks and vendors to communicate and collaborate. This is a significant step towards agent interoperability. Akshay Pachaar also provided a clear explanation contrasting [MCP vs. A2A](https://x.com/akshay_pachaar/status/1912123161883345321). ([GitHub Repo](https://github.com/google/A2A))
* **New MCP Tools:** Ishan Goswami released an open-source [Twitter MCP Tool using Exa](https://x.com/TheIshanGoswami/status/1914226695118168331) (GitHub: [exa-labs/exa-mcp-server](https://github.com/exa-labs/exa-mcp-server)) for searching tweets/profiles without the official API. Eyal Toledano shipped [TaskmasterAI v0.12](https://x.com/EyalToledano/status/1914084622918455572) with multi-PRD parsing, smarter breakdowns, and easier MCP setup, alongside a new [website](http://task-master.dev).
* **Cursor Workflows & Tips:** Ryo Lu shared [12 tips for using Cursor effectively](https://x.com/ryolu_/status/1914384195138511142), emphasizing clear rules, specific prompts, and iterative testing. Prajwal Tomar detailed his ["Context Boundary Method"](https://x.com/PrajwalTomar_/status/1913961327711633601) using structured docs (PRD, Flow, Tech Stack etc.) to guide AI coding tools like Cursor and reduce errors. Andrew Jefferson noted potential issues with [Markdown tab completion](https://x.com/EastlondonDev/status/1913967886521053688) in Cursor.
* **AI UI Builders Compared:** Damien shared a comparison of [Replit, Bolt.new, Lovable.dev, and v0](https://x.com/damienghader/status/1913248328302608482) for generating a multi-step onboarding flow from the same prompt.

## Building AI Agents: Frameworks & Best Practices

* **Agent Framework Discussion:** Harrison Chase (LangChain) published a deep dive on [how to think about agent frameworks](https://blog.langchain.dev/how-to-think-about-agent-frameworks/), sparking discussion comparing approaches (agents vs. workflows, declarative vs. non-declarative) and frameworks like LangGraph, OpenAI's Agents SDK, CrewAI, and AutoGen. Key themes include balancing flexibility vs. predictability and choosing the right abstraction level. OpenAI also released its own [practical guide to building agents](https://cdn.openai.com/business-guides-and-resources/a-practical-guide-to-building-agents.pdf).
* **Production Agent Principles:** Dex Horthy shared principles for production-grade LLM apps in ["12-factor-Agents"](https://github.com/humanlayer/12-factor-agents), arguing successful systems often use focused LLM loops within well-engineered software rather than fully autonomous, monolithic agents. This resonated with many builders facing reliability challenges.
* **Agent Memory:** Taranjeet from [mem0.ai](https://x.com/taranjeetio/status/1912185506559053855) emphasized the importance of persistent memory (beyond session history) for truly intelligent agents that learn and adapt over time ([Blog Post](https://mem0.ai/blog/memory-in-agents-what-why-and-how/)).
* **Key Best Practices:** Common advice emerging from various discussions includes: start simple (maybe not even an agent), use structured outputs (like JSON schemas) to reduce hallucinations, prefer multiple specialized agents over one complex agent, own your control flow rather than relying solely on the framework, and carefully manage context windows. ([Anthropic Guide](https://www.anthropic.com/research/building-effective-agents), [Dev.to Summary](https://dev.to/isaachagoel/read-this-before-building-ai-agents-lessons-from-the-trenches-333i)).

___

**✨ Workshop Spotlight: Conquer the Complexity of Cursor ✨**

Master practical AI development workflows in Cursor. This hands-on workshop covers Agents, Ask, Custom Modes, multi-file analysis, effective prompting, Cursor rules, and strategies for handling AI failures.

* **When:** **This Thursday!** April 24, 2025, **9:00 AM - 2:00 PM (PDT)**
* **Where:** Zoom (Live Q&A included)
* **Investment:** $249

Unlock Cursor's potential and streamline your development process.

➡️ [**Read More about the Workshop**](https://egghead.io/workshop/cursor) ➡️ [**Register Now ($249)**](https://buy.stripe.com/9AQaG5ftF5P22eAfZ3)

_(Team training also available)_

___

## Notable Prompts

* **o3 Fact-Checking:** A prompt structure for using o3 to thoroughly fact-check an entire article by parsing individual facts. (See [Matt Shumer's Tweet](https://x.com/mattshumer_/status/1914412812891570199) for the prompt start).
* **Multiple Experts Method:** A system prompt that instructs the AI to analyze problems from multiple expert perspectives (e.g., Systems Thinker, Risk Assessor) and synthesize their insights. (See [God of Prompt's Tweet](https://x.com/godofprompt/status/1914370848032497906) for the full prompt and example).
* **Personality-Infused Prompt:** A detailed persona prompt instructing the AI to adopt a specific, informal, and slightly critical tone using modern slang and abbreviations. (See [Kitze's Tweet](https://x.com/thekitze/status/1913719205007937825) for the full prompt, originally from [@threepointone](https://x.com/threepointone)).

## Community Buzz & Resources

* **New Community Site:** [AGIdevice](https://x.com/agidevice/status/1913666033870647325) is building [cursorcommunity.com](http://cursorcommunity.com) in public.
* **Industry Chatter:** Deirdre Bosa discussed the potential [OpenAI bid for Windsurf](https://x.com/dee_bosa/status/1912906057791447294) and the shift towards the app layer. AI Native Dev reported on perceived [friction between Microsoft and Cursor](https://x.com/ainativedev/status/1912869556973949430) ([Article](http://ainativedev.co/spx)).
* **Android XR Demo:** Google showed off prototype smart glasses with Android XR ([Demo Video via 9to5Google](https://9to5google.com/2025/04/17/google-android-xr-smart-glasses-live-demo/)).
* **New Open Dialogue Model:** A new small open model, [Dia-1.6B](https://x.com/altryne/status/1914421817139454341), was released. It's focused on dialogue disentanglement – figuring out who's talking to whom in complex conversations. ([GitHub](https://github.com/nari-labs/dia), [Hugging Face](https://huggingface.co/nari-labs/Dia-1.6B)). I was extremely impressed with the demos – definitely worth checking out.
* **Video Generation with Veo 2:** Google's Veo 2 video generation model is now available in Gemini Advanced and Google AI Studio ([Google Blog](https://blog.google/products/gemini/video-generation/), [Developers Blog](https://developers.googleblog.com/en/veo-2-video-generation-now-generally-available/)). I've tried out a few videos and was really impressed with the quality. Pro tip: In AI Studio, you can use an image as a reference when generating video ([API Docs](https://ai.google.dev/gemini-api/docs/video#generate_from_images)), though surprisingly, Gemini doesn't support that yet. It's heavily rate-limited at the moment, but still fun to play with for generating short 8-second clips.

___

That’s the scoop for this issue! The pace isn't slowing down, particularly around agent capabilities, specialized models, and the tooling ecosystem supporting them.

If you have any feedback or questions, hit reply! Always happy to chat about the latest in AI dev tools.

John Lindquist


John Lindquist

AI Dev Essentials #3: Gemini Flash, o4-mini, Codex CLI, A2A Protocol & Agent Updates

AI Dev Essentials covers Gemini 2.5, O4-mini, Claude’s research tools, Codex CLI, and new workflows for building AI agents with MCP and Cursor.

Establish an automated, AI-driven workflow for implementing UI designs by comparing live development versions against target screenshots. This lesson integrates the Playwright MCP server for browser automation, a custom script using Pixelmatch for visual diffing, and Cursor Rules for persistent context. See how to instruct the Cursor Agent to iteratively implement design changes based on visual diff feedback, creating a robust loop where the AI refines the UI towards the target design.

**Workflow demonstrated in this lesson:**

*   Configure the Playwright MCP server within Cursor for browser control.
*   Use the Agent and Playwright MCP tools (`browser_navigate`, `browser_resize`, `browser_take_screenshot`) to capture baseline and current state PNG screenshots.
*   Install `pixelmatch` and `pngjs` dependencies.
*   Guide the Agent to create and run a TypeScript script (`compare-images.ts`) to generate visual diff images between screenshots.
*   Establish Cursor Rules (`visual-testing.mdc`, `project-setup.mdc`, etc.) to provide the Agent with necessary context about directories, scripts, dependencies, and the overall workflow.
*   Initiate an AI-driven design implementation loop:
    *   Agent captures the current state via Playwright.
    *   Agent runs the comparison script to get a visual diff.
    *   Agent analyzes the diff and implements code changes in the project (e.g., `app/page.tsx`, components, `globals.css`).
    *   Repeat the capture-compare-implement cycle, using the latest diff as feedback.
*   Use context files and prompts like "Please continue" to manage the multi-step process and guide the AI through potential interruptions.

**Key benefits:**

*   Creates an iterative, AI-driven workflow for implementing designs based on visual comparisons.
*   Combines browser automation (Playwright) and pixel-level diffing (Pixelmatch) within the Cursor environment.
*   Utilizes Cursor Rules to effectively manage context and guide the AI through complex, multi-step tasks.
*   Demonstrates how visual diffs can serve as direct feedback for AI-driven UI code generation and refinement.

AI-Driven Design Workflow: Playwright MCP Screenshots, Visual Diffs, and Cursor Rules

[Scraped MCP Examples](https://gist.github.com/johnlindquist/b19673bbf6a396406dff869beecace1d)
[ghx tool](https://www.npmjs.com/package/@johnlindquist/ghx)

Building complex components like Model Context Protocol (MCP) servers from scratch can be challenging, especially without good reference implementations. This lesson demonstrates a powerful workflow combining the `ghx` CLI tool with AI assistants (like Google's AI Studio and Cursor's agent) to overcome this hurdle.

You'll learn how to:

1.  **Use `ghx`:** Leverage the `ghx` command-line tool (which wraps the GitHub CLI) to search GitHub for real-world code examples based on specific import paths (e.g., `modelcontextprotocol/sdk/server/mcp.js`).
2.  **Refine Search Results:** Use `ghx` options (`--help`, `--limit`, `--max-filename`, `NOT demo`) within Cursor's chat to filter results, exclude simple demos, and gather a rich set of relevant MCP server implementations.
3.  **Provide AI Context:** Copy the aggregated code examples found by `ghx` into an AI environment like Google AI Studio (or ChatGPT).
4.  **Handle Context Limits:** See techniques for trimming large context files (like using Cursor's `Cmd+K` inline edit with `head -n` commands) to fit within model limits while retaining valuable examples.
5.  **Generate Code:** Prompt the AI (Gemini 2.5 Pro in AI Studio or ChatGPT O3) to generate a *new* MCP server (e.g., with five distinct tools) based *solely* on the provided real-world examples.
6.  **Integrate and Debug:** Set up the generated TypeScript code (`mcp_server.ts`) locally in Cursor, install dependencies (`pnpm install`), and use Cursor's agent (`Cmd+I`) or inline fixes (`Cmd+K`) to resolve TypeScript errors and path issues.
7.  **Configure in Cursor:** Add the newly created MCP server (running via `bun mcp_server.ts`) to Cursor's MCP settings, using the absolute path and the `bun` command.
8.  **Test the MCP Server:** Interact with Cursor's chat agent to call the custom tools (e.g., `add_note`, `list_notes`, `write_managed_file`) defined in the AI-generated MCP server, verifying its functionality.

This lesson showcases how combining targeted code searching (`ghx`) with the generative power of AI, fueled by relevant examples, can dramatically accelerate the process of building and bootstrapping complex tools and applications.

Generate and Debug MCP Servers from Scratch

Hey Everyone 👋,

John Lindquist here with the second issue of AI Dev Essentials! It's been another busy week in the AI tooling world. The biggest splash was probably GPT-4.1 hitting the streets, but there's plenty more action around MCP, Vercel's v0, Google's developer tools, and interesting community discussions. I've spent some time with GPT-4.1 already (specifically in Cursor), and while it shows promise, it didn't quite convince me to switch from Gemini 2.5 Pro yet. It stumbled on a few basic requests where Gemini usually shines on the first attempt.

---

### New egghead.io Lesson This Week:

* **[Create a Custom MCP that Calls Cursor Tools](https://egghead.io/create-a-custom-mcp-that-calls-cursor-tools~r77sw):** Learn how to build custom MCP server tools that allow Cursor's AI Agent to access your local project context. This lesson shows how to use Zod schemas and the crucial `.describe()` method to explicitly request information (like Git status or version) from the Cursor environment *before* your tool runs, enabling powerful, context-aware automation.

---

Here are the highlights that caught my eye this past week.

## Model Mania: GPT-4.1 Arrives, Plus Grok & Llama Updates

* **GPT-4.1 Lands:** OpenAI announced GPT-4.1, and it quickly became available via the [API](https://openai.com/live/) and showed up in [Cursor](https://x.com/cursor_ai/status/1911835651810738406). Cursor is offering it free for now to let users get a feel for it, though they don't recommend it as a default just yet. Curious to hear initial impressions from folks testing it out for coding tasks.

* **Grok 3 in Cursor:** Following other model additions, [Cursor also enabled Grok 3 models](https://x.com/amanrsanger/status/1910434915419906141), with the mini version available for free users. Aman Sanger noted it seems to "think upfront more than other models."

* **Community Hack: Llama 4.0 via Groq in Cursor:** Levi Dan shared a [detailed (and slightly hacky) guide](https://x.com/lxvi_brg/status/1908865544721154455) on how to wire up Groq's fast Llama 4.0 API into Cursor by using the OpenAI API key slot and intercepting requests. A clever workaround for the adventurous!

## Tooling & Platform Pulse

Lots of movement across different platforms and tools this week:

* **Vercel Ecosystem:**

  * Guillermo Rauch teased [v0 coming to VS Code](https://x.com/rauchg/status/1911524154458984515), hinting at tighter integration for the UI generation tool.

  * v0 also [added AI integrations](https://x.com/v0/status/1911912183149256943) with models from xai (Grok), FAL, Groq, and DeepInfra, including automatic API key setup and pay-as-you-go billing via Vercel Marketplace. They're offering a $10 credit for the Grok free tier.

  * Vercel shared insights on the [grep.app migration from CRA to Next.js](http://grep.app/), showcasing performance improvements. ([Source](https://x.com/rauchg/status/1911920410020757881)) I'm personally excited about this one – I rely heavily on examples when working with AI, and for me, a good example is often worth ten prompts. Tools like `grep.app` that make code discovery easier are invaluable.

* **Google's Growing Stack:**

  * Project IDX has officially become [Firebase Studio](https://x.com/_davideast/status/1909990728593453455), positioning itself as a cloud-based, agentic dev environment for full-stack AI apps, deeply integrated with Firebase. I've tried spinning up a few sites with it, and the speed is impressive. However, for more complex tasks like designing from images or intricate interactions, I still find myself leaning towards v0 for now.

  * Google quietly released the [Agent Development Kit (ADK)](https://x.com/omarsar0/status/1910004370864742757), a Python library (`pip install google-adk`) for building multi-agent systems with features like state management, tool usage, and orchestration. I haven't had a chance to dive into this yet, but it's right at the top of my list. Building robust agent systems is a huge area of interest, so this is probably the announcement I'm most excited about exploring this week.

  * Ramón Medrano Llamas shared his experience [moving back to VS Code from Cursor](https://x.com/rmedranollamas/status/1909516749612999149), highlighting the effectiveness of GitHub Copilot combined with the Gemini Code Assist extension (using Gemini 2.5 Pro in Agent Mode). I gave the Gemini Code Assist extension a try myself, but as someone deeply embedded in the Cursor workflow with established keyboard shortcuts and patterns, I struggled to find a flow I liked and didn't stick with it for long. It's interesting to see different perspectives, though!

  * AI features are rolling out more broadly in [Chrome](https://x.com/iam_chonchol/status/1909942954686636224), including text grabbing from YouTube videos and Google Lens integration.

* **Cloudflare Corner:**

  * Big news for edge compute: [Cloudflare Containers are coming to Open Beta in June](https://x.com/CherryJimbo/status/1910682562499850405), enabling running containerized apps (Next.js, Go, PHP confirmed) directly on the edge. This is huge news, in my opinion. Think about all the WordPress sites and other applications that rely on containerization. Opening this up on the edge unlocks incredible possibilities, including for AI applications. I'm super hyped to see what people build with this come June.

  * A new tool, [MCPify.ai](http://mcpify.ai/), launched for building MCP servers conversationally, built entirely on Cloudflare Workers and Durable Objects. ([Source](https://x.com/pbteja1998/status/1911723180445610149))

  * Securing MCP servers is getting easier, with examples shared using [WorkOS AuthKit](https://x.com/WorkOS/status/1910722639036874943) and [Auth0](https://x.com/dschenkelman/status/1910693265566728319).

* **IDE Updates:**

  * JetBrains shared the public [WebStorm roadmap for March-April](https://youtrack.jetbrains.com/issue/WEB-72310). ([Source](https://x.com/WebStormIDE/status/1909291367504748937))

> **✨ Workshop Spotlight: Conquer the Complexity of Cursor (Europe Friendly Time!) ✨**
>
> Missed the last workshop or found the timing tricky? This one's for you! Master practical AI development workflows in Cursor in a session scheduled for **12:00 PM UTC** to better accommodate European attendees.
>
> This hands-on workshop covers Agents, Ask, Custom Modes, multi-file analysis, effective prompting, Cursor rules, and strategies for handling AI failures. Unlock Cursor's potential and streamline your development process.
>
> * **When:** \[Check website for upcoming dates - This session is Europe-friendly at 12:00 PM UTC\]
>
> * **Where:** Zoom (Live Q&A included)
>
> * **Investment:** $149
>
> ➡️ [**Read More about the Workshop**](https://egghead.io/workshop/cursor)
> ➡️ [**Register Now ($149)**](https://buy.stripe.com/7sI7tT81dfpC06s28c)
>
> *(Team training also available)*

## Community Buzz & Resources

* **MCP Explained:** Kent C. Dodds wrote a piece explaining [why he's excited about Model Context Protocol (MCP)](https://www.epicai.pro/the-game-changing-potential-of-model-context-protocol) and its potential. ([Source](https://x.com/kentcdodds/status/1911840456432034112))

* **Prompting Guide:** Ian Nuttall surfaced [v7 of Google's Prompt Engineering Guide](https://x.com/iannuttall/status/1911086164196606314), a deep dive into techniques and best practices. Definitely worth a look.

* **Discussion Starter:** Eric Zakariasson asked the community about their [favorite CLIs and MCP servers to use with the Cursor agent](https://x.com/ericzakariasson/status/1910808935961088346). What are you all using?

* **Gemini 2.5 Pro Praise:** The positive buzz around Gemini 2.5 Pro continues to grow in the community. It's getting rave reviews and even achieving 'S-tier' status on social platforms like Reddit for its coding capabilities. ([Source](https://x.com/suchenzang/status/1911251230317490416))

That’s a wrap for this week! There's always so much happening, it's hard to keep up, but hopefully, this helps surface some of the more interesting bits for developers working with AI.

If you have any feedback or questions, feel free to respond to this email. Always happy to talk shop about the latest AI tools.

John Lindquist

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

AI Dev Essentials #2: GPT-4.1 Arrives, MCP Deep Dive & Google's Agent Dev Kit

AI Dev Essentials #2: GPT-4.1 & Gemini updates, MCP tools, Vercel v0, Google ADK, Cloudflare Containers news. Latest AI dev tooling highlights.

In this quick walkthrough, you’ll learn how to drop Nx into an existing npm or pnpm workspace and immediately benefit from project graph visualization, caching, and smart task orchestration, all without rewriting your setup.

You’ll start with a standard React monorepo containing a Vite app, a UI package, and utility functions. Then, using a single command (`nx init`), you’ll initialize Nx and see how it auto-detects your existing scripts, builds a dependency graph, and enables advanced features like affected commands and local caching.

We're also going to explore optional enhancements using Nx plugins for Vite and React. You’ll see how they help Nx infer tasks directly from your Vite config files, improve DX with the Nx Console VS Code extension, and leverage Nx plugin generators to scaffold code with a consistent structure.

What you’ll learn
- How to initialize Nx in an existing npm or pnpm monorepo
- How Nx understands your workspace structure and scripts
- How local caching and affected builds speed up development
- How optional Nx plugins improve DX without adding bloat
- How to scaffold new packages

Using Nx on an existing React and NPM workspace based monorepo

Applying Nx to an existing React monorepo to enable caching, task orchestration, and project graph analysis without changing your current setup.

Typing repetitive or complex instructions for Cursor's AI agent can slow down your workflow. This lesson teaches you how to create custom slash commands (e.g., `/s term`, `/l`, `/c`) using Cursor's "Rules" feature. Learn how to map these simple shortcuts to specific AI actions, instructing the agent to use precise tools like `codebase_search`, `edit_file`, or `run_terminal_cmd` based on your command and the current conversation context.

**Workflow demonstrated in this lesson:**

*   List available AI tools (built-in and MCP) to get their exact names.
*   Navigate to Cursor Settings -> Rules.
*   Define custom rules under a heading (e.g., `## Slash Commands`).
*   Create rules mapping a slash command pattern (like `/s <term>`) to a detailed instruction specifying which tool to use and how (e.g., "Use the codebase_search tool to search for <term/>").
*   Define rules that leverage conversation context (e.g., for summarizing notes or creating commit messages).
*   Save the rules (potentially in `.cursor/rules/project.mdc` for team sharing).
*   Invoke the custom slash commands (e.g., `/s handle`, `/l`, `/c`) in the chat/agent window.
*   Observe the AI understanding the shortcut and executing the intended tool call.

**Key benefits:**

*   Creates efficient, reusable shortcuts for common AI interactions.
*   Reduces the need for typing lengthy, detailed prompts repeatedly.
*   Allows mapping simple commands to specific Cursor tool invocations.
*   Enables commands that leverage the ongoing conversation context.
*   Improves workflow speed and consistency when working with the AI agent.

Speed Up Your Agents with Cursor Slash Commands

Hey Everyone 👋,

John Lindquist here. Since I've been diving deep into AI tooling and workflows over the past year, I'm starting this weekly newsletter to share updates on what interests me and could be helpful to the community. The goal is to help everyone stay up-to-date with the latest in essentials tools for AI devs.

I'll focus on relevant community news, model evaluations for coding, notable tools like Cursor and Windsurf, and practical workflows (including tools I build myself 😇). This week kicks off Cloudflare Developer Week with major announcements around agent/MCP services that many of us will likely use soon (I'll dig in and share my thoughts next issue). There are also lots of hints about new coding models possibly coming to Cursor (though my preference remains Gemini 2.5). Personally, I'm hoping for a Gemini Flash 2.5 variant. So let's hop into the latest! For my detailed, up-to-date workflows, check out the workshop info below.

Recent egghead.io lessons about AI tooling:

* **[Swarm Intelligence: Massively Parallelize Your AI Agents in Cursor](https://egghead.io/swarm-intelligence-massively-parallelize-your-ai-agents-in-cursor~g7u2g):** A workflow using `file-forge`, AI scripting, and a custom `git worktree` tool (`wt`) to launch parallel Cursor agents on different branches.
* **[Build a Better Edit Tool in Cursor with Custom Agent Modes](https://egghead.io/build-a-better-edit-tool-in-cursor-with-custom-agent-modes~21rr0):** Create a focused 'edit mode' in Cursor for precise AI refactors without conversational overhead, overcoming Command-K limitations.
* **[Visually Clone Websites with Gemini 2.5 Canvas for Cursor](https://egghead.io/visually-clone-websites-with-gemini-2-5-canvas-for-cursor~s5ugk):** Use Gemini 2.5 Pro's Canvas feature within Cursor to analyze and replicate website structures.

---

## Cloudflare Developer Week: Agent & Platform Updates

Cloudflare announced several updates relevant to AI application development:

* **Durable Objects Free Tier:** Lowers the barrier for experimenting with stateful serverless and the Agents SDK. ([Rita Kozlov](https://x.com/ritakozlov_/status/1909231625855983939))
* **MCP Enhancements:** BYO Auth (incl. [Auth0](https://x.com/auth0/status/1909307220816228354)) and Hibernation for MCP servers aim to improve agent security and efficiency. Exercise caution with MCP, but these are steps toward production viability.
* **Workflows GA & autoRAG:** Orchestration tool is now GA; a new autoRAG product indicates more integrated AI solutions.
* **Outerbase Acquisition:** Expect Durable Objects usability improvements following this acquisition. ([Rita Kozlov](https://x.com/ritakozlov_/status/1909232149246492887))
* **OpenNext Adapter Beta:** v1.0-beta for deploying Next.js apps on Cloudflare Pages adds caching, PPR, middleware support. ([CloudflareDev](https://x.com/CloudflareDev/status/1909598450871652398))

**Summary:** Cloudflare is actively enhancing its platform for AI/agent development, particularly reducing friction with Durable Objects and MCP.

## Llama 4 & Nemotron-Ultra Released

Meta's Llama 4 models began rolling out, with initial reports of variable quality across implementations. Meta attributes this to implementation stabilization, denying training on test sets ([Ahmad Al-Dahle](https://x.com/Ahmad_Al_Dahle/status/1909302532306092107)). Nvidia subsequently released **Llama-Nemotron-Ultra** (253B parameters), derived from Llama-405B via pruning and reasoning-focused post-training. Open weights and data are available ([Oleksii Kuchaiev](https://x.com/kuchaev/status/1909444566379573646)).

**Summary:** More powerful open models are available. Llama 4's initial rollout highlights the importance of stable implementations. Nemotron-Ultra adds a high-end specialized option.

---

## Quasar Alpha: Stealth Model on OpenRouter

OpenRouter provides early access to "Quasar Alpha," a model with limited public details but notable claims: 1M token context, benchmarks reportedly surpassing Claude 3.7 Sonnet, and >4x faster speeds. Reports suggest strong coding performance comparable to O3 Mini/DeepSeek R1 but significantly faster ([Matthew Berman's Thread](https://x.com/TheMattBerman/status/1908286423976886371)). The originating lab remains anonymous; speculation includes GPT-5, Claude 4, or Gemini 3.

**Summary:** The combination of large context, speed, and reported coding strength warrants attention for agentic workflows and large codebase analysis, despite benchmark caveats. Worth testing via OpenRouter if accessible.

---

**✨ Workshop Spotlight: Conquer the Complexity of Cursor ✨**

Master practical AI development workflows in Cursor. This hands-on workshop covers Agents, Ask, Custom Modes, multi-file analysis, effective prompting, Cursor rules, and strategies for handling AI failures.

* **When:** **This Thursday!** April 10, 2025, 9:00 AM - 2:00 PM (PDT)
* **Where:** Zoom (Live Q&A included)
* **Investment:** $149

Unlock Cursor's potential and streamline your development process.

➡️ [**Read More about the Workshop**](https://egghead.io/workshop/cursor)
➡️ [**Register Now ($149)**](https://buy.stripe.com/dR67tT4P17Xa8CYfZ1)

*(Team training also available)*

---

## Quick Links

* **Nightwhisper Buzz:** Highly-rated coding model "Nightwhisper" (rumored Gemini 2.5 variant?) left LMSys Arena; release may be imminent. ([ʟᴇɢɪᴛ Tweet](https://x.com/legit_api/status/1908264443827351913), [AiBattle Tweet](https://x.com/AiBattle_/status/1907519430961025476))
* **AI SDK Speech-to-Text:** Vercel AI SDK added a `transcribe` function. ([AI SDK Tweet](https://x.com/aisdk/status/1909603418639155460))
* **Gemini 2.5 Pro Updates:** Supports YouTube URLs as input in AI Studio (transcribe, summarize, analyze); reported improvements reducing stop issues/displaying thinking tokens. ([Jean Gatt Tweet](https://x.com/jean__gatt/status/1909256747518226829), [Eric Zakariasson Tweet](https://x.com/ericzakariasson/status/1908619515023548880))
* **Baby Cursor Project:** Cursor's Ryo Lu is building a rapid prototyping environment for IDE ideas. ([Ryo Lu Tweet](https://x.com/ryolu_/status/1908328050154233863))
* **(Rumor) Qwen3 Soon?:** Hints suggest Alibaba's Qwen3 model release is near. ([Elaina Tweet](https://x.com/Elaina43114880/status/1909572798944841859))

---

If you have any feedback or any questions, feel free to respond to this email. Always happy to talk shop about the latest AI tools.

John Lindquist

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

AI Dev Essentials #1: Cloudflare agent updates, Llama 4/Nemotron/Quasar models, Cursor workshop

Cursor's AI Agent has the abilitly to invoke MCP tools, but they lack direct access to your project. This lesson shows how to build custom MCP (Model Context Protocol) server tools that bridge this gap. Learn to define tool parameters using Zod schemas and the crucial `.describe()` method to explicitly request necessary context from the Cursor environment *before* your tool runs. See how the AI gathers this information (like Git status or version via terminal commands, or web search results) and passes it to your tool, enabling powerful, context-aware automation.

**Workflow demonstrated in this lesson:**

*   Scaffold a basic MCP server using a Cloudflare template (`pnpm create cloudflare`).
*   Run the MCP server locally and configure it in Cursor settings.
*   Define MCP tools (e.g., `status`) within the server code (`index.ts`).
*   Specify required context for tools using Zod schema parameters and `.describe()` (e.g., requesting "The status of the git repository").
*   Interact with the Cursor Agent using natural language (e.g., "Please check the status").
*   Observe the Agent's thought process: identifying the need for specific context based on the `.describe()` text.
*   See the Agent automatically using its *own* tools (like `run_terminal_cmd` or `web_search`) to gather the requested context *before* calling your MCP tool.
*   Watch the Agent call your MCP tool, passing the gathered local context (Git status, version, etc.) as arguments.
*   Receive the final response from the Agent, incorporating the information provided by your local MCP tool.

**Key benefits:**

*   Allows Cursor's AI to access and reason about information from your local machine (Git status, versions, file contents, etc.).
*   Enables the creation of AI tools that directly interact with or report on your local development environment.
*   Demonstrates the power of using `.describe()` in Zod schemas to guide the AI in gathering necessary context automatically.
*   Unlocks advanced automation possibilities by combining AI reasoning with local machine access.

Create a Custom MCP that Calls Cursor Tools

Vimium's Vomnibar is a "command palette"-like search tool for your open tabs, browser history, and bookmarks. We can search through and jump to any tab open across browser windows. We can also do a generalized search with results that also include browser history and bookmarks which can either be opened in the current tab or a new tab. If you're anything like me, you open tons of tabs and visit hundreds of webpages over the course of a week. The vomnibar puts all of that at your fingertips.

Josh Branchaud

Open Tabs, Browser History, and Bookmarks with the Vomnibar

Vimium's Vomnibar is a "command palette"-like search tool for your open tabs, browser history, and bookmarks.

Another aspect of Vimium's configurability is customizable key mappings. We can add new mappings and override existing ones. If there is a certain Vimium feature you want to make easier to trigger, adjust the key mapping to suit your needs.

Configure Custom Vimium Key Mappings

Another aspect of Vimium's configurability is customizable key mappings. We can add new mappings and override existing ones.