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AI 资讯

TypeScript TS2802 Error: Resolving Observer Pattern 'Set' Spread with Array.from Conversion

TypeScript Compile Error TS2802: Resolved with Observer Pattern by Converting Set Spread to Array.from If you're stuck implementing the observer pattern due to TypeScript compile error TS2802, this post might help. I resolved the issue with a simple conversion: changing Set spread to Array.from() . Attempts and Pitfalls While implementing the observer pattern, I encountered TypeScript compile error TS2802 when trying to spread a Set. Initially, I suspected the Set's type might be the problem, so I tried various approaches. class Observer { private subscribers = new Set < () => void > (); subscribe ( callback : () => void ) { this . subscribers . add ( callback ); } notify () { // TS2802 error occurs here for ( const callback of [... this . subscribers ]) { callback (); } } } When attempting to spread the Set into an array using [...this.subscribers] as shown above, TypeScript failed to recognize it properly, throwing an error similar to TS2802: Cannot find module '...' or its corresponding type declarations. . At first, I thought it was a library configuration issue and spent a considerable amount of time lost. The Cause In the end, the problem lay with the Set spread syntax itself. When TypeScript applies the ... spread operator to a Set, there were instances where it couldn't accurately infer the types internally. This issue can be more pronounced in certain versions or environments. The Solution To resolve this, I used the method of explicitly converting the Set spread to an array using Array.from() . class Observer { private subscribers = new Set < () => void > (); subscribe ( callback : () => void ) { this . subscribers . add ( callback ); } notify () { // Resolved by converting with Array.from for ( const callback of Array . from ( this . subscribers )) { callback (); } } } By using Array.from(this.subscribers) , TypeScript clearly recognizes the Set as an array, allowing the loop to execute correctly. The Outcome The TypeScript compile error TS2802 was cleanl

2026-06-13 原文 →
AI 资讯

Flutter Agent Skills: How to Make Your AI Agent Actually Good at Flutter

TL;DR: Your AI coding assistant is a generalist. It writes Flutter that looks right but quietly reaches for 2022 patterns. Agent Skills are a new, official way (from the Dart and Flutter teams) to hand your agent task-specific, battle-tested workflows it loads on demand. Two repos, flutter/skills and dart-lang/skills , ship ready-to-use skills for responsive layouts, routing, testing, localization, static analysis, and more. Install in one command: npx skills add flutter/skills --skill '*' --agent universal npx skills add dart-lang/skills --skill '*' --agent universal This post breaks down what they are, how they differ from rules files and MCP, the full catalog, what a real skill looks like under the hood, and whether they actually move the needle. (Spoiler: mostly yes, with one honest caveat.) Let me tell you about a fight I have almost every day. I ask my AI agent to make a screen adapt to tablets. It confidently hands me code that switches layout based on MediaQuery.orientationOf(context) . It looks clean. It compiles. It even runs . And it's wrong, because device orientation has nothing to do with how much window space your app actually has on a foldable, in split-screen, or in a resizable desktop window. The model isn't dumb. It's a generalist trained on a giant pile of Flutter code, much of it old. And here's the uncomfortable truth the Flutter team said out loud when they launched this feature: Flutter and Dart ship new features faster than LLMs can update their training data. That lag has a name, the knowledge gap , and it's why your agent keeps writing rookie Flutter with a straight face. Agent Skills are the Flutter team's answer to that gap. I've been running them on real projects, and they're one of the few "AI workflow" things in 2026 that earned the hype instead of borrowing it. Let's get into it. Table of Contents The real problem: your AI is a generalist What are Agent Skills, exactly? Skills vs Rules vs MCP: who does what The full catalog: every of

2026-06-12 原文 →
AI 资讯

Model Context Protocol (MCP): Giao Thức Tương Lai Cho AI

Model Context Protocol (MCP): Giao Thức Kết Nối Thế Giới Cho Trí Tuệ Nhân Tạo Trong thế giới AI đang phát triển với tốc độ chóng mặt, việc xây dựng các ứng dụng thông minh, có khả năng tương tác linh hoạt với dữ liệu và công cụ bên ngoài là một thách thức lớn. Các mô hình ngôn ngữ lớn (LLM) như GPT, Claude, hay Gemini dù mạnh mẽ nhưng thường hoạt động trong "vùng cô lập", thiếu khả năng truy cập trực tiếp vào các hệ thống bên ngoài theo thời gian thực. Đây chính là lúc Model Context Protocol (MCP) xuất hiện như một giải pháp cách mạng. MCP là một giao thức mở, được thiết kế để tiêu chuẩn hóa cách thức các ứng dụng cung cấp ngữ cảnh (context) cho LLM, giúp phá vỡ rào cản giữa trí tuệ nhân tạo và thế giới thực. Bài viết này sẽ đi sâu vào phân tích Model Context Protocol , từ định nghĩa, kiến trúc, đến các lợi ích và ứng dụng thực tế, giúp bạn hiểu tại sao nó được coi là "ngôn ngữ chung" của tương lai AI. Model Context Protocol (MCP) Là Gì? Model Context Protocol (MCP) là một giao thức mở, được phát triển để tạo ra một chuẩn giao tiếp thống nhất giữa các LLM và các nguồn dữ liệu, công cụ bên ngoài. Hãy tưởng tượng MCP như một "cổng USB" dành cho AI. Thay vì mỗi ứng dụng AI phải viết mã tích hợp riêng lẻ với từng loại cơ sở dữ liệu, API, hay hệ thống tệp tin (mỗi loại một kiểu "phích cắm" khác nhau), MCP cung cấp một giao diện chuẩn. Bất kỳ ứng dụng nào hỗ trợ MCP đều có thể kết nối với bất kỳ nguồn tài nguyên nào cũng hỗ trợ MCP một cách liền mạch. Mục Đích Cốt Lõi Của MCP Mục tiêu chính của Model Context Protocol là giải quyết vấn đề "fragmentation" (phân mảnh) trong hệ sinh thái AI. Trước MCP, việc tích hợp thường diễn ra rời rạc: Mỗi nhà phát triển ứng dụng phải tự xây dựng các "kết nối" tùy chỉnh. Mỗi lần cập nhật mô hình hoặc công cụ có thể làm hỏng các tích hợp cũ. Khó khăn trong việc chia sẻ và tái sử dụng các công cụ AI giữa các dự án. MCP giải quyết những vấn đề này bằng cách cung cấp một lớp trừu tượng chuẩn hóa. Kiến Trúc Và Cách Thức Hoạt Động Của MCP Kiến

2026-06-12 原文 →
AI 资讯

Why modal.open() should return Promise , not Promise

How treating modals as typed async operations eliminates boolean state, callback chains, and runtime surprises in React apps. React applications often treat modals as UI details. A boolean flag. A conditional render. An onClose callback. That works fine for one dialog. But real products have modals that are actually business flows: confirm this destructive action rename this entity and return the new name pick a date range and apply it resolve a conflict before continuing complete a wizard step before the next one unlocks These flows need more than a boolean. They need typed input, typed output, and a way to await the result — just like any other async operation in your app. const result = await modal . open ( renameReportModal , { reportId : report . id , currentName : report . name , }); if ( result . status === " renamed " ) { await renameReport ({ id : report . id , name : result . name }); } That is the idea behind: npm install @okyrychenko-dev/react-modal-manager zustand A modal lifecycle manager. Not a component. Not a design system. A typed async contract between your app logic and your dialog UI. The problem with traditional modal state In most React apps, modal state starts locally: function ReportsPage () { const [ isRenameOpen , setIsRenameOpen ] = useState ( false ); return ( <> < button onClick = { () => setIsRenameOpen ( true ) } > Rename </ button > { isRenameOpen && ( < RenameModal onClose = { () => setIsRenameOpen ( false ) } /> ) } </> ); } And then real requirements arrive: const [ isRenameOpen , setIsRenameOpen ] = useState ( false ); const [ isDeleteOpen , setIsDeleteOpen ] = useState ( false ); const [ isShareOpen , setIsShareOpen ] = useState ( false ); const [ renameTarget , setRenameTarget ] = useState < Report | null > ( null ); const [ deleteTarget , setDeleteTarget ] = useState < Report | null > ( null ); const [ shareTarget , setShareTarget ] = useState < Report | null > ( null ); The UI is not the problem. The orchestration is: Where d

2026-06-12 原文 →
AI 资讯

How I Cut SQL Query Time from 45 Seconds to 8 Seconds on 2.3 Million Rows

I inherited a SQL Server database with 2.3 million rows. Queries took 45 seconds. Users were frustrated. Dashboards timed out. Here is exactly what I did. Step 1: Find the slowest queries I used SQL Server's query store to identify the top 10 worst performing queries. Step 2: Check the execution plan Missing index warnings everywhere. Also saw table scans on a 2 million row table. Step 3: Add targeted indexes Created two non-clustered indexes on the most filtered columns. No over-indexing. Just what the queries actually needed. Step 4: Rewrite the worst join One query was joining 6 tables with a cross apply that made no sense. Restructured to inner joins with proper filter ordering. The result 45 seconds down to 8 seconds. An 82% improvement. Real-time dashboards started working again. Key lesson Check what is actually slow before changing anything. Most people skip this and waste time optimizing the wrong thing. What is your fastest query optimization win?

2026-06-12 原文 →
AI 资讯

How I Cut SQL Query Time from 45 Seconds to 8 Seconds on 2.3 Million Rows

I inherited a SQL Server database with 2.3 million rows. Queries took 45 seconds. Users were frustrated. Dashboards timed out. Here is exactly what I did. Step 1: Find the slowest queries I used SQL Server's query store to identify the top 10 worst performing queries. Step 2: Check the execution plan Missing index warnings everywhere. Also saw table scans on a 2 million row table. Step 3: Add targeted indexes Created two non-clustered indexes on the most filtered columns. No over-indexing. Just what the queries actually needed. Step 4: Rewrite the worst join One query was joining 6 tables with a cross apply that made no sense. Restructured to inner joins with proper filter ordering. The result 45 seconds down to 8 seconds. An 82% improvement. Real-time dashboards started working again. Key lesson Check what is actually slow before changing anything. Most people skip this and waste time optimizing the wrong thing. What is your fastest query optimization win?

2026-06-12 原文 →
开发者

Indexes: Quickstart Using PostgreSQL (15 sec read)

Let's consider a table user . When we execute a query to find Emily , we are actually going through each record , looking whether the name column equals Emily . Indexes comes in when you want to speed this up. Let's create an Index with the name idx_users_name (the name can be anything, and it doesn't matter functionally): CREATE INDEX idx_users_name ON users ( name ); Now when you run SELECT * FROM users WHERE name = 'Emily' ; Postgres will use the index we just created (not by the name, the name is just for us) to execute that query, and the time complexity is reduced from O(n) to O(log n) .

2026-06-12 原文 →
开发者

Govee’s rechargeable smart table lamp is down to $60

Whether you’re planning a backyard barbeque or a World Cup watch party, Govee’s Table Lamp Classic can help set the mood with color-changing lighting effects. Right now it’s down to just $59.99 ($20 off) at Amazon, which is its best price yet. The rechargeable lamp can last up to 30 hours on a single charge, […]

2026-06-12 原文 →
AI 资讯

SpaceX’s massive IPO: all the latest news

SpaceX’s IPO on Friday allows the public to buy shares of the combined rocket, AI, and social media company for the first time, and is raising enough money to likely make Elon Musk the first trillionaire. He’ll have more wealth, on paper at least, than the economies of nations like Ireland, Sweden, or his home […]

2026-06-12 原文 →
科技前沿

SpaceX IPO: Everything you need to know

TechCrunch has followed SpaceX's start, struggles, and successes from the early days. And we're here for what happens next too. This package of SpaceX IPO coverage includes who stands to win (and maybe some who won't), pre-IPO deals, and what's tucked inside its S-1 registration document.

2026-06-12 原文 →
AI 资讯

SpaceX is now public

SpaceX is now a publicly traded company. In one of the most highly anticipated and controversial public offerings of all time, the rocket venture helmed by Elon Musk started trading on Nasdaq on June 12th at the take-it-or-leave-it price of $135-per-share - though most retail investors will likely pay far more. The IPO is historic […]

2026-06-12 原文 →
AI 资讯

Angular's Official Agent Skills Helps AI Coding Tools Write Modern Angular

Google's Angular team has released a repository called angular/skills, focusing on Agent Skills that enhance AI coding agents' ability to write modern Angular code. The repository includes skills for generating code and scaffolding applications, reinforcing current Angular conventions. It serves as a snapshot, aiming to improve AI suggestions by providing updated context. By Daniel Curtis

2026-06-12 原文 →