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AWS Builder Center now offers free 8-hour sandbox environments for workshops. Here's how it works, who it's for, and how it compares to Free Tier, Skill Builder, and Educate.

AWS just announced free Sandbox environments which lets any AWS Builder Center user to provision...

Introduction: Unveiling littlebag Meet littlebag , a reactive UI framework that defies conventional expectations by packing essential features into a mere 343 bytes (minified and brotlified). This isn’t just a technical curiosity—it’s a proof of concept that challenges the notion that UI frameworks must be bloated to be functional. littlebag includes: Reactive state management via state and effect , enabling dynamic updates without manual DOM manipulation. An html element factory that inherently supports reactivity, reducing boilerplate code. Conditional rendering with keyed , allowing efficient updates to specific UI segments. Reactive lists using each , simplifying the handling of dynamic data collections. TypeScript declarations , ensuring type safety and developer productivity. The framework’s size is achieved through aggressive tree-shaking and code minimization , stripping away all non-essential logic. However, this comes at a cost: performance limitations due to the absence of optimizations like virtual DOM diffing or batch updates . Each reactive update triggers direct DOM manipulation, which can lead to layout thrashing —a mechanical process where frequent reflows and repaints cause frame rate drops, making the UI feel sluggish. Inspired by VanJS (1 kB) and its dependency on an additional 1.2 kB library (Van X), littlebag aims to eliminate such overhead. Yet, its current state is experimental. Without user feedback, it risks remaining a niche project, failing to address its performance bottlenecks or evolve into a viable alternative to larger frameworks. The creator’s plan to add Server-Side Rendering (SSR) hinges on community interest, but SSR itself introduces complexity—requiring a custom DOM implementation to avoid client-side hydration costs. If users engage, littlebag could become a lightweight SSR solution; if not, it may stagnate as a curiosity. The stakes are clear: littlebag’s utility depends on whether it can balance its minimalism with practical

Quick note before we dive in — I know I've been off track from the iOS/Swift series lately. I just...

I just submitted another Chrome extension to the Chrome Web Store. I have submitted multiple extensions overtime. Mostly for my own tooling and community share or just because idea was fun. The first time took 3 attempts. The second time I got rejected in 12 hours for something completely avoidable. Here's every gotcha I hit — so you don't have to. 1. Manifest description has a 132-character hard limit Not documented prominently anywhere. You'll get a cryptic upload error: "The description field in manifest is too long." Your package.json description or wxt.config.ts description gets baked into manifest.json — check it BEFORE you zip. Fix : Count characters. 132 max. Put the detailed description in the CWS form, not the manifest. 2. Don't put a "Keywords:" line in your description I literally had: Keywords: pinterest seo, pin score, pin quality, pinterest optimizer... Rejected within 12 hours for "Keyword Spam." CWS explicitly bans keyword lists in descriptions — even if they're relevant. Your keywords should be woven naturally into prose. Fix : Write human sentences that include your keywords. "Score your Pinterest pin quality before publishing" contains 3 keywords naturally. 3. upload-artifact@v4 silently skips hidden directories If your build tool outputs to .output/ (like WXT does), GitHub Actions' upload-artifact won't find it. The glob path: .output/*.zip returns nothing because .output starts with a dot. Fix : Add include-hidden-files: true to your upload-artifact step. - uses : actions/upload-artifact@v4 with : path : .output/*.zip include-hidden-files : true 4. optional_permissions need justification too I added sidePanel as an optional permission (reserved for a future feature). CWS asked me to justify it. Optional doesn't mean invisible to reviewers. Fix : Add a justification for EVERY permission — required AND optional. Explain what it'll do and why it's optional. 5. "Support URL" is not your email address The form has separate fields: Support email : yo

The Redbelly Network EligibilitySDK is the compliance backbone for any dApp that needs to verify user eligibility (KYC, KYB, investor accreditation) before letting a wallet in. The official documentation covers each piece well on its own reference page, but there is no single walkthrough connecting the frontend widget to the backend verifier to the on-chain permission check to a production deployment. This guide is that walkthrough. Everything here was verified against the live documentation at https://docs.redbelly.network/ in July 2026: contract addresses, route names, config fields, issuer DIDs and every error string in the reference section. Every code example was then compiled against the published SDK package (v0.0.31) on React 19 with Vite and on Next.js 16 with the App Router, and the backend verifier was booted and exercised for real. Where the docs and reality diverge (a quickstart repo that is not publicly visible, a credential faucet still under development, three undocumented behaviours the builds surfaced), the guide says so and gives you the workaround. What you will build, in order: A mental model of the two verification mechanisms (and why conflating them costs you a day) A working backend verifier with the three routes the widget demands A plain React integration with full loading and error states A production-grade Next.js App Router setup: secure proxy, SIWE sessions, request gating, and both static and dynamic rendering approaches An end-to-end test run on Redbelly Testnet The decision logic for choosing between the three SDK flows, and the pattern for combining them A complete error reference: every documented error, its cause, and its fix A developer following this guide should have the widget running inside an existing dApp within about four hours. 1. Overview and Architecture What the EligibilitySDK actually is The Redbelly "Onboarding and Eligibility Kit" ( @redbellynetwork/eligibility-sdk ) is a set of React components and hooks for provin

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The MVP was a great idea that got misused. "Minimum viable product" was meant to be the smallest experiment that tests a hypothesis. In practice it became an excuse to ship something broken and call it strategy. The minimum lovable product — MLP — is the correction: the smallest release that people actually want to use, not just tolerate. Knowing which one you need is a scoping decision, not a philosophy. The difference in one line An MVP asks will they use it at all? An MLP asks will they love the part we built? The MVP tests demand with the roughest possible artifact. The MLP narrows scope but polishes what remains until it's genuinely good. Both are about doing less. They disagree on where the "less" goes — fewer features versus rougher features. Why the bar has risen When users had few alternatives, a rough MVP could win on novelty. Today almost every category is crowded, and people judge a new product against the polished tools they already use. A janky first impression doesn't read as "early" — it reads as "not for me," and they don't come back. In a saturated market, lovability is the viability test. When an MVP is still right Ship a true MVP when the core question is demand, not quality: You're genuinely unsure anyone wants this at all. The audience is early adopters who tolerate rough edges for access. You can learn what you need from a small, forgiving group. Speed to a signal matters more than the strength of the signal. Here, spending weeks polishing something nobody wants is the expensive mistake. When to reach for an MLP Choose an MLP when demand is fairly clear but the market is competitive: Users have real alternatives and will compare you to them. Your differentiation is the experience — feel, speed, design. First impressions are hard to reverse. Word of mouth depends on delight, not just function. Scope narrow, finish deep The trap with "lovable" is treating it as license to add features. It's the opposite. Pick fewer things and finish them complet

Multi-tenancy is the decision that quietly shapes your entire SaaS backend. Get it right and you scale smoothly to thousands of accounts. Get it wrong and you're rewriting your data layer under load, mid-growth, with customers watching. The good news: for most products the right answer is simpler than the internet suggests. The three models There are three canonical ways to isolate tenants, and they trade isolation against operational cost: Row-level (shared schema). Every table has a tenant_id\ column, and every query filters on it. One database, one schema, all tenants together. Schema-per-tenant. Each tenant gets its own PostgreSQL schema inside a shared database. Stronger isolation, more objects to manage. Database-per-tenant. Each tenant gets a dedicated database or instance. Maximum isolation, maximum operational weight. Why row-level wins for most SaaS For the overwhelming majority of B2B SaaS products, row-level multi-tenancy is the right default. It's the cheapest to operate, the easiest to run migrations against, and it scales further than founders expect. The objection is always "but isolation" — and Postgres has a strong answer. Row-Level Security (RLS) lets the database itself enforce that a query can only see its own tenant's rows. With Supabase , RLS is the native model: you set a policy once, and even a buggy query can't leak across tenants. Combined with a tenant_id\ on every table and an index that leads with it, this pattern comfortably serves large customer bases. One caution from hard experience: write RLS policies so helper functions run once per query, not once per row . A policy that re-evaluates a lookup for every row will quietly turn fast endpoints slow as tables grow. Wrap the check so the planner runs it as an init-plan. When to reach for stronger isolation Escalate deliberately, not reflexively: Regulatory or contractual isolation — a customer requires their data in a physically separate database. Noisy-neighbor risk — one whale tenant'

Picture a power plant burning fuel to spin a turbine. It is tempting to assume that with enough engineering — better seals, smoother bearings, cleaner combustion — the plant could be pushed toward converting nearly all its heat into useful work. It cannot. A large modern thermal power station turns only something like 40 to 45 percent of its fuel energy into electricity, and the missing majority is not lost to sloppy design. It is lost to a law of physics. That law sets a ceiling on every device that turns heat into work, from a car engine to a steam turbine to a jet. The ceiling is called the Carnot efficiency, and the remarkable thing about it is how little it depends on. Not on the working fluid, not on the mechanism, not on the cleverness of the builder — only on two temperatures. This article explains where that limit comes from, how to compute it, and why it reshapes how engineers think about efficiency. Why this calculation matters The Carnot efficiency is the benchmark against which every real engine is judged. When an engineer reports that a gas turbine runs at 38 percent efficiency, that number means little on its own. Compared against the Carnot limit for the same hot and cold temperatures, it suddenly tells you how much room is left — whether the design is already near the physical wall or still has slack worth chasing. It also redirects design effort toward the things that actually matter. Because the Carnot limit depends only on the ratio of cold to hot absolute temperatures, the single most powerful way to raise the ceiling is to raise the temperature at which heat enters the engine, or lower the temperature at which it is rejected. This is why turbine inlet temperatures have climbed for decades, pushing the limits of metallurgy and cooling. Polishing internal friction yields small gains; raising the hot-side temperature raises the ceiling itself. The core formula Sadi Carnot, in 1824, imagined an idealized engine running on a perfectly reversible cyc