#netlify

#netlify

TanStack RSCs are supported through three primitive APIs that allow manipulation of RSCs as any other stream of data, compatible with tools like React Query and TanStack Router.

The dynamic type hints feature in Module Federation 2.0 dramatically streamlines the development process by automatically generating and loading types from remote modules, eliminating the need for shared type packages.

One of the most significant changes is the move to integrate CSS module support directly into webpack's core. Currently available behind the experimental.css option, this feature eliminates the need for mini-css-extract-plugin. The team expects to complete integration into core around early 2026, with the feature remaining experimental until webpack 6, at which point plugin-based CSS handling will no longer be necessary.

Modern web applications are no longer just "sites." They are long-lived, highly interactive systems that span multiple runtimes, global content delivery networks, edge caches, background workers, and increasingly complex data pipelines. They are expected to load instantly, remain responsive under poor network conditions, and degrade gracefully when something goes wrong.

The request for its API val request = Request[IO](Method.POST, uri"/jobs")val api = new AsyncJobApi // this will not compile since AsyncJobApi is not defined yet Minimal implementation to make it green: class AsyncJobApi Red test: The API should return a 202 Accepted response: "POST /jobs returns Accepted" in { val request = Request[IO](Method.POST, uri"/jobs") val api = new AsyncJobApi api.routes.orNotFound.run(request).asserting : response => response.status shouldBe Status.Accepted} Make it green: class AsyncJobApi { val routes: HttpRoutes[IO] = HttpRoutes.of[IO] : case req @ POST -> Root / "jobs" => Accepted()} 5.2 Add headers (Trivial Implementation) Red test: add X-Total-Count and Location headers with job ID (only the assertion is shown)

I'm currently building a web app using NuxtJS 2 for the frontend and NestJS for the backend, relying on third-party APIs (like Replicate) for the heavy lifting. I'm using Cloudflare R2 to store the generated output images. I'm running into some performance bottlenecks when rendering specific landing pages that contain heavy, dynamic image galleries. For instance, I'm trying to optimize the SEO and load speed for my AI Pet Portrait Generator free tool page.

React tutorial: Get started with the React libraryDespite the endless churn of new frameworks, React remains the quintessential reactive engine. This updated guide walks you through the fundamentals of React development, including a This is Spinal Tap variant on the canonical counter application. Sometimes, your components just need to go to 11.

Vercel, the cloud platform behind Next.js, has released react-best-practices, an open-source repository containing over 40 performance optimization rules for React and Next.js applications. The framework, which encapsulates over a decade of engineering knowledge from Vercel's production codebases, is structured specifically for consumption by AI coding agents and LLMs, though the team notes it is equally valuable for human developers.

The release marks a change from the previous hosted platform to a fully self-hosted approach, giving developers complete control over their content editing infrastructure with no external dependencies. Nuxt Studio introduces a set of features designed to bridge the gap between developers and content creators. The module provides a Notion-like visual editing experience with full MDC component support, allowing users to insert Vue components, edit props visually, and drag-and-drop content blocks directly within the production site.

The most complete example of what the new development server makes possible is support for Cloudflare Workers. With Astro 6 Beta, astro dev can now run applications using workerd, Cloudflare's open-source JavaScript runtime, which is the same runtime that powers Cloudflare Workers in production. This means developers can now develop directly against real platform APIs rather than simulations or polyfills.

The web is full of AI assistants that appear to understand application UIs, user data, and intent. In practice, however, most of these systems operate outside the application itself. When you try to build one from scratch, you quickly run into a core limitation: large language models have no native understanding of your React state, component hierarchy, or business logic.