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AI 资讯

Big Tech’s desperate last push at AI regulation

For months, Big Tech's Washington lobbyists have chased after the holy grail of pro-AI legislation: preemption. This would be a comprehensive federal law, passed in Congress and signed by the president, applying one set of AI rules across the entire country and overriding the legally messy state-by-state approach to regulation. For months, lobbyists have run […]

2026-06-16 原文 →
AI 资讯

AI Isn't Something to Trust — It's Something to Design (Series Final)

Series Final. The four mechanisms covered across this series — knowledge graph, Auto Review, Self-Healing, Recurrence Prevention — plus the non-engineer-PR application that sits on top of them, all hang off a single conviction: AI isn't something to trust; it's something to design. The 'I don't trust AI to fill in the blanks for me' framing this lives inside isn't doubt about generation quality, but the clear-eyed acceptance that AI has no idea what context wasn't handed to it, and that 'ideal behavior with no spec given' is a fantasy. The starting point goes back to 2025, when I was trying to figure out how to make AI actually understand a large codebase — and ran into walls on both context window scaling (lost in the middle, attention dilution) and learning-based approaches (machine unlearning, destructive interference). GraphRAG + MCP became the way out: hand AI only the facts it needs, when it needs them, so it doesn't have to infer. From code-graph (which I burned two months on and threw away) to the current product-graph (cpg). This piece is the philosophy and the trial-and-error behind the whole series: harnesses confine where hallucinations are allowed to happen, design is translating principles into your own use cases, and Coverage 90% as a solo target breaks the implementation.

2026-06-16 原文 →
开发者

UI IP Toolkit - A standalone static visual catalog for CSS/JS components

UI IP Toolkit - A standalone static visual catalog for CSS/JS components I built UI IP Toolkit to solve my own workflow problem: I kept losing useful UI snippets (buttons, loaders, CTA blocks, glassmorphic cards, layout grids) across old projects and directories. Live site: https://ui-ip-toolkit.vercel.app/ GitHub Repository: https://github.com/ikerperez12/UI-IP-Toolkit-v4.0 Design Philosophy Zero dependencies: Raw HTML, CSS, and vanilla JS. No NPM packages, framework configurations, or build steps required. Copy-paste ready: Visual preview cards with one-click copy buttons for immediate use in any stack. Light/Dark mode: Clean design system focusing on micro-interactions, sleek gradients, and responsive layouts. Visual catalog: Catalog of gradients, buttons, fonts, loading states, hover treatments, glass surfaces, layout fragments, and UI patterns. How do you manage your personal code/CSS snippet collections? Hope this is useful to others!

2026-06-15 原文 →
AI 资讯

I built a browser-based desktop environment (IP Linux) with React, TypeScript and Vite

I built a browser-based desktop environment (IP Linux) with React, TypeScript and Vite I have been working on a project called IP Linux : a browser-based desktop environment that runs as a static web app. Live site: https://ip-os-linux.vercel.app/ GitHub Repository: https://github.com/ikerperez12/IP-OS-LINUX It is not a real Linux distribution, and it does not run native binaries. The idea is different: I wanted to explore how far a polished desktop-like experience can go inside a normal browser tab. The result is a small web OS-style environment with: A splash / entry screen A desktop with icons, folders, and widgets A top panel with system controls A dock and app launcher Resizable and draggable windows Virtual workspaces Snap assist A global search / Spotlight-style command palette Local-first apps (Files, Terminal, settings, player) Reactive wallpapers Glass UI and visual effects Why I built it Most web demos are landing pages, dashboards, or small single-purpose apps. I wanted to build something that feels more like an environment. I was interested in questions like: Can a web app feel physical and desktop-like? How should windows behave inside a browser viewport? How far can local-first storage go before a backend is actually needed? How do you organize many small apps without making the UI messy? IP Linux became a way to test all of that in one project. The app includes a catalog of built-in apps and tools: Files, Terminal, Browser, Settings, App Store, Music Player, Matrix Rain, games, developer tools, productivity apps, and visual utilities. The virtual file system and user preferences are stored locally in the visitor's browser with IndexedDB/localStorage. There is no backend, no account system, and no required environment variables for the public release. Would love to get feedback on the interaction design, responsiveness, or features!

2026-06-15 原文 →
开发者

Challenges I Faced and How GoFr Helped

Why I Chose GoFr for My Backend Project When starting a new backend project, one of the first decisions I need to make is choosing the right framework. Over the years, I’ve experimented with different backend technologies, each offering its own strengths and trade-offs. For my latest project, however, I decided to try something different: GoFr. At first, I was simply exploring the Go ecosystem and looking for tools that could help me build production-ready services faster. What caught my attention wasn’t just that GoFr was built in Go—it was the philosophy behind it. Instead of forcing developers to spend days configuring infrastructure, wiring dependencies, and setting up observability, GoFr focuses on helping developers get from idea to deployment quickly. In this article, I’ll share the reasons why I chose GoFr for my backend project and what stood out during my experience. The Problem with Starting Backend Projects Every backend project begins with excitement. You have an idea, a feature roadmap, and a vision of what you’re trying to build. Yet before writing meaningful business logic, developers often spend hours or even days configuring: Logging Database connections Metrics Tracing Health checks API routing Environment management Deployment configurations While these tasks are necessary, they rarely contribute directly to solving the actual problem your application is meant to address. As a developer who frequently builds side projects and prototypes, I wanted a framework that reduced this setup overhead while still following good engineering practices. That’s where GoFr entered the picture. What Initially Attracted Me to GoFr The first thing I noticed was how quickly I could get a service running. Instead of navigating through multiple configuration files and third-party packages, GoFr provides many essential backend capabilities out of the box. This means less time deciding which libraries to install and more time focusing on application logic. The framework

2026-06-15 原文 →
AI 资讯

Your Hand-Rolled Two-Phase Commit Between Two Databases Isn't Atomic

I had a write that spanned two physically separate databases. A rename that had to propagate across several tables in one database and a couple of tables in another, and the two had to stay consistent. No distributed transaction coordinator was available to me. So I did the obvious thing: opened a transaction on each, did the work, and committed them one after the other inside a try/catch with rollbacks on both sides. It felt safe. It compiled. It passed tests. Then I drew the failure on a whiteboard, and the safety evaporated. The window that ruins everything Here's the structure, simplified: await using var txA = await dbA . Database . BeginTransactionAsync (); await using var txB = await dbB . Database . BeginTransactionAsync (); await DoWorkOnA ( dbA ); await DoWorkOnB ( dbB ); await txA . CommitAsync (); // <-- succeeds await txB . CommitAsync (); // <-- what if this throws? Two transactions do not make one atomic operation. CommitAsync is a point of no return, and there are two of them. Between the first commit returning and the second one starting, there is a window. If txB fails in that window — the connection drops, the process is killed, the database hiccups — then A is permanently committed and B never happens. Your rollback in the catch block is useless: you can't roll back txA , it's already durable. The two databases now disagree, and nothing in your code will heal that on its own. This is the dual-write problem , and it's not a bug you can fix by being more careful with try/catch. The atomicity you want simply isn't available from two independent commits. Ordering them, nesting them, wrapping them — none of it closes the window, because the window is inherent to having two commit points. Why "it's never failed" isn't reassurance The seductive thing about this pattern is that the window is small, so in practice it almost never triggers. You can run it for a year and never see an inconsistency. That's exactly what makes it dangerous: it trains you to tr

2026-06-15 原文 →
AI 资讯

OTP Verification in Playwright Without Regex

Every developer who has written a Playwright test for OTP verification has written this line: const otp = email . body . match ( / \b\d{6}\b / )?.[ 0 ]; It works. Until it doesn't. The email body changes format. The OTP appears inside an HTML table. The sending service wraps it in a <span> . Your regex matches a phone number instead of the code. The test fails intermittently and you spend an hour debugging something that has nothing to do with the feature you're testing. The regex problem OTP extraction via regex is brittle by nature. You're pattern-matching against a string that your email sending service controls — not you. Any time the template changes, your tests break. Here's what a typical OTP test looks like today: import { test , expect } from ' @playwright/test ' ; import { ZeroDrop } from ' zerodrop-client ' ; const mail = new ZeroDrop (); test ( ' user can verify OTP ' , async ({ page }) => { const inbox = mail . generateInbox (); // 1. Trigger OTP send await page . goto ( ' /login ' ); await page . fill ( ' [data-testid="email"] ' , inbox ); await page . click ( ' [data-testid="submit"] ' ); // 2. Wait for email const email = await mail . waitForLatest ( inbox , { timeout : 15000 }); // 3. Extract OTP — the fragile part const otp = email . body . match ( / \b\d{6}\b / )?.[ 0 ]; if ( ! otp ) throw new Error ( ' OTP not found in email body ' ); // 4. Enter OTP await page . fill ( ' [data-testid="otp"] ' , otp ); await page . click ( ' [data-testid="verify"] ' ); await expect ( page ). toHaveURL ( ' /dashboard ' ); }); The test works — but line 14 is carrying all the risk. Change the email template and the test breaks. Add a phone number to the footer and the regex matches the wrong number. Send a 4-digit OTP instead of 6 and you need to update the pattern. OTP extraction at the edge ZeroDrop extracts OTPs before they reach your test. The Cloudflare Worker that catches incoming emails runs a pattern match on the plain-text body and stores the result alongsi

2026-06-15 原文 →