标签：#IDE

These are the AC units we’ve trusted to cool our homes for months, if not years.

From musical instruments and games to play pieces that encourage balance and dexterity, these toys will engage your child’s mind and body.

When you're building a multi-tenant SaaS, the first architectural question is usually: how do you keep tenant data isolated? The options range from separate databases per tenant (maximum isolation, maximum cost) to a shared database with row-level filtering (minimum cost, more careful coding required). But there's an equally important question that gets less attention: how does your API know which tenant context a request belongs to? This post covers a pattern we've used in production: a custom request header for tenant scoping, combined with JWT authentication. Simple to implement, easy to audit, and flexible enough to support multi-tenant access from a single user account. The Three Common Approaches 1. Subdomain-based ( tenant.yourdomain.com ) The tenant is encoded in the hostname. Each subdomain routes to the same backend, which extracts the tenant from the Host header. Good: Intuitive, visible in the URL. Bad: Requires wildcard TLS certs, more complex DNS setup, awkward in development, doesn't work for mobile API clients the same way. 2. URL path-based ( /api/tenants/{tenantId}/... ) The tenant identifier is part of every route path. Good: RESTful, self-documenting. Bad: Bloats all route definitions, requires every endpoint to include the tenant segment, makes API versioning messier. 3. Header-based ( x-tenant-id: <id> ) A custom header carries the tenant context. Routes stay clean. The tenant scope is resolved in middleware before the handler runs. Good: Routes stay simple, middleware handles scoping uniformly, works well with JWT auth, easy to test. Bad: Less visible (the tenant isn't in the URL), requires clients to always include the header. We use the header approach. The Implementation The API accepts two forms of auth: A JWT token in the Authorization header — identifies who is making the request A tenant ID in the x-tenant-id header — identifies on behalf of which tenant POST /api/v1/members Authorization: Bearer eyJhbGciOiJIUzI1NiIs... x-tenant-id: ten

I build products solo. Every single one of them sits on top of somebody else's API — Stripe for payments, OpenAI and Anthropic for AI features, Meta for ads, print-on-demand APIs, map APIs. My code is maybe half of what actually runs in production. The other half belongs to vendors, and it changes whenever they decide it changes. Twice this year the first notice I got about a breaking change was a production error. Not an email, not a warning. An error, and then me digging through the vendor's changelog trying to figure out what they changed and when. The information was public the whole time. It was sitting in a changelog page I never visit, because nobody visits changelog pages until something is on fire. So I'm building the thing I wanted to exist BreakWatch is simple: you tell it which APIs your product depends on, and it reads their public changelogs for you. It fetches each changelog page once a day Diffs it against yesterday's snapshot Classifies the real changes: breaking (endpoint removed, field deprecated, "migrate by September") vs. informational (new feature, docs clarification — stuff you can ignore) Alerts you only when something looks like it will break an existing integration Keeps everything in a searchable timeline, so six months later "what changed on their side right before this broke" takes ten seconds instead of an afternoon No SDK, no credentials, nothing installed in your codebase. It only reads public pages. What I tested this week I ran it against the real changelogs of the ten APIs I'm watching first: Stripe, Twilio, OpenAI, Anthropic, Shopify, GitHub, Slack, Cloudflare, Google Maps and Plaid. Some honest findings: 10/10 scrape cleanly now, but it took fixes. Stripe's changelog page alone is 3.3 MB. SendGrid's standalone changelog doesn't exist anymore (it merged into Twilio's). PayPal's developer site serves a JavaScript shell with an HTTP 404 to anything that isn't a full browser, so it's out until I add rendering. The thing I was most a

Also, the full trailer for Zach Cregger's Resident Evil features a likable everyman.

Amazon is hoping the addition of games can turn Prime Video into a one-stop entertainment destination, borrowing a strategy from Netflix, which has increasingly embraced party games over the past several years.

Deck out your room and make class a cinch with these WIRED-tested favorites.

Cordless, handheld, robot, and traditional—we tested them all to find the vacuum that’s fantastic for fur.

The slim and convenient magnetic wallets you’ll actually want stuck to the back of your phone.

Here are the best delivery services and meal kits in 2026, including Martha Stewart’s meal service, a GLP-1–supportive plan, and a budget-friendly option.

why-we-open-sour-c1f013bf.webp alt: Building Digital Identity Tools - Why We Open-Sourced Our SSI SDK relative: false Self-Sovereign Identity (SSI) is a framework that allows individuals and organizations to control their own digital identities and share verified credentials without relying on a central authority. This paradigm shift empowers users with greater privacy and control over their personal data, while also providing robust mechanisms for verifying the authenticity of credentials. What is Self-Sovereign Identity (SSI)? SSI is built around the concept of decentralized identifiers (DIDs) and verifiable credentials. DIDs are unique identifiers that are controlled by the entity they represent, enabling them to manage their own identity data. Verifiable credentials are digital assertions that can be issued by one party and verified by another, ensuring the authenticity and integrity of the information shared. Why did we open-source the SSI SDK? Open-sourcing the SSI SDK was a strategic decision driven by several factors. First, fostering innovation within the community is crucial for advancing the field of digital identity. By making our SDK available to everyone, we encourage collaboration and experimentation, leading to new ideas and improvements. Second, promoting transparency is essential for building trust in digital identity systems. Open-source projects allow others to inspect the codebase, understand how it works, and identify potential vulnerabilities. This transparency helps build confidence in the security and reliability of the SDK. Finally, enabling a broader community to contribute to and benefit from secure digital identity solutions aligns with our mission to democratize access to these technologies. By lowering the barriers to entry, we hope to empower more developers and organizations to adopt and improve upon our work. What are the key features of the SSI SDK? The SSI SDK provides a comprehensive set of tools for building digital identity app

Harrowing story of an identity theft victim. Yes, the person made a mistake—they gave the scammer a two-factor authentication code that allowed the scammer to take over their email address. But the real story here is how, for many of us, the security of most of our accounts hangs on the security of our email accounts.

The fitness trackers I’d recommend to beginners, athletes, and kids.

"Maybe that's my responsibility, to live alone with the truth."

The latest release of Android Studio, Quail 2, now stable, expands Gemini/AI Agent Mode inside the IDE by enabling multiple AI conversations in parallel and further advancing Google's push to integrate AI-powered workflows directly into Android Studio. It also enhances debugging and profiling capabilities and makes it easier to explore experimental features. By Sergio De Simone

Einride agreed to buy Flipturn for $38 million in stock.

You followed an old breeding guide. You put Penking + Bushi into your breeding farm, dropped the cake, waited for the egg... and out hatched Sibelyx , not the Anubis the guide promised. You're not alone. Your guide isn't broken. The recipe changed. When Palworld hit 1.0, the breeding table got quietly rewritten. Almost every pairing that players had memorized from early-access now produces a different Pal. There's no in-game notice, no patch note that lists the hundreds of changed combos — just a lot of confused hatchings. So I dug into the data. Here's what I found, and the small tool I built to make sense of it. What actually changed in 1.0 I compared two snapshots of the game's breeding data — the pre-1.0 set and the current 1.0 release — both sourced from the open-source PalCalc project. The headline number: 97.7% of comparable pre-1.0 parent pairs now produce a different Pal. That's not a typo. If you take the breeding pairs that existed before 1.0 and run them against the current data, nearly all of them hatch something new. A few concrete examples players keep running into: Old recipe (pre-1.0) What it makes now (1.0) Penking + Bushi Anubis → Sibelyx ... (more pairs in the tool) The mismatch matters because most breeding guides and calculators on the internet still show the old results. Players follow them, breed, and get confused. The subtle trap: renumbering vs. real change There's a detail that trips up every breeding tool that tries to track this. When Palworld 1.0 launched, it also renumbered parts of the Paldeck (Pal #139 vs #116, etc.). A naive diff tool would see the number change and wrongly report "the breeding result changed!" — when really only the number changed, not the actual Pal. To avoid that false signal, I match Pals by their internal game name , not their Paldeck number. A renumbering is not mistaken for a changed breeding result. Only genuine recipe changes are counted. The tool: PalShift I wanted a dead-simple way to answer one question:

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I spent a week using video editing Skills to build a video editing Agent. It feels amazing! It can automatically edit a 30-minute video in just 10 minutes. Video editing Agent demo: automatically editing a 30-minute video in 10 minutes. I often use CapCut to edit talking-head videos, but after using it for a long time, I found several problems. Problem 1: Smart talking-head editing does not understand meaning Because it cannot understand the meaning, it sometimes fails to identify repeated sections. If I speak continuously for 20 or 30 minutes, editing the video myself becomes exhausting. Problem 2: The subtitle quality is poor The automatically generated subtitles contain many incorrect words and typos. So I used the Skills feature in Claude Code to build a video editing Agent. The fundamental difference is simple: CapCut vs. Agent: a fixed tool vs. an adaptive assistant. The key difference is: CapCut = fixed tool + manual operation Agent = adaptive system + automatic learning I am not replacing CapCut with a better algorithm. I am replacing it with a system that can continuously improve itself. But that is not even the most impressive part. The most impressive part is this: the more I use it, the better it understands me, and the faster it becomes. Three Core Designs 1. Agent Logic It only takes four steps. Video editing Agent workflow: from the video file to the final video. 2. The Skills System At first, I put every function into one large Skill. I had to add instructions to distinguish between different tasks, which was very inconvenient. Now I have separated the five core video editing tasks into five independent Skills and placed them in the .claude/skills/ directory. This makes the structure clearer and the tasks easier to select. When I enter /v , Claude Code automatically lists the five available Skills. The list of five independent Skills. I select one, and the AI runs that Skill. Simple, right? A manual task that used to take 10 minutes now only requires