Your membership gets you more than free two-day shipping. Here’s what you may be missing ahead of Amazon Prime Day.
Used Waymo batteries will bolster California and Texas energy storage projects.
Most days in her chambers, Judge Maritza Braswell, a federal magistrate judge in Colorado, sifts through stacks of documents written by people without a lawyer. Many of them can’t afford to hire a lawyer, and others have cases too weak or too small to interest one. She reads each one carefully, mindful of how daunting…
From app-controlled security to electronic shifting and radar alerts, Segway’s Myon may have more tech than you need. That’s not always a bad thing.
Here is the situation of the website. If someone in Canada enters www.example.com they are redirected to www.example.com/ca and ALL the mention of "USA" is hidden and replaced with "Canada"! For example in Canada, instead of people seeing "Home Improvement in the USA and Canada", people in Canada just see "Home improvement in Canada", and vice versa; someone in USA and everywhere other than Canada on the globe does NOT see Canada on the website pages . My question is: Shouldn't a website have unified info and list BOTH USA and Canada, because with current situation someone accessing the homepage in Canada would NOT know that the company can also do Home improvement in the USA and vice versa . Even for AIs, I asked Chatgpt where is the company located and did NOT see Canada. P.S. The only mention of both countries is in the contact page. submitted by /u/RadiantQuests [link] [留言]
Samsung will roll out an update for its Health app before launching its new Galaxy Watches.
The speakers discuss the architectural challenges of executing safe data deletion across distributed datastores. Balancing durability, availability & correctness, they explain how to orchestrate multi-system deletion propagation without impacting live traffic. They share lessons on controlling tombstone accumulation, building continuous audit loops, and gaining trust with a centralized platform. By Vidhya Arvind, Shawn Liu
A homeschooling center in Manhattan is part of the company’s nationwide expansion. Internal documents reveal its strategy: “Opening date > safety.”
The group has "due process concerns" over how the company handles account bans.
I tagged v0.9.0 of LaraFoundry this week: billing. Except the honest headline is that I shipped the billing seam , not billing. The free core now has the whole shape of a subscription system, a payment-gateway contract, a driver manager, a real access gate over subscription columns, and it cannot take a single cent. That is on purpose, and the reason is the most interesting part of the phase. LaraFoundry is a SaaS core I'm extracting in public from a live CRM, one module at a time. The deal I made with myself early on: the core is free and stays free for everything except money. Auth, multi-tenancy, RBAC, the admin console, the activity log, i18n, files: all free. The day a business wants to charge its customers , that is the paid part. So billing could not just be "another module." It had to split cleanly down a line, with the free side carrying real, useful structure and the paid side carrying the parts that actually move money. The donor habit I would not carry Here is what the original CRM did when a company "paid" for its subscription: // TODO: real payment gateway integration // TEMPORARY: every payment is successful, for testing $paymentStatus = 'success' ; That success was hardcoded. There was no Stripe, no Paddle, no gateway at all. "Paying" wrote a row into a company_payments table and flipped the subscription date forward. For a CRM I run myself, with one real user, that was fine: I never needed the real thing, so the placeholder sat there indefinitely. The moment this becomes a reusable core, that placeholder is poison. A success that is always true is worse than no gateway, because it looks like billing works. So the rule for this phase was simple: the fake gateway does not get extracted. Whatever stands in its place has to be honest about the fact that it takes no money. What the seam actually is The free core ships a PaymentGatewayInterface : subscribe, cancel, refund, status, and verify a webhook. It describes only the mechanics of moving money. It d
Marketing wants an A/B landing page by Friday. Product wants to gracefully deprecate a legacy API without breaking old mobile clients. Growth wants ten thousand short links, and Ops does not want ten thousand Nginx edits. At some point, a single return 301 in your CDN stops being a configuration problem and becomes a routing product . Someone has to answer, on every HTTP request: Given this host, path, query, and method—where does this visitor go, and with which status code? I built that answer as a pipeline at LinkShift . Not a pile of special cases, but a fixed sequence of steps that runs the exact same way for real visitors and for the tools you use to test rules before rollout. Here is how I designed a deterministic redirect engine, the pipeline that powers it, and the edge cases that kept me up at night so they don't have to keep you up. Why "Usually Works" Is Not Enough A redirect engine fails quietly. The browser follows a broken 302 and nobody files a ticket. The damage shows up days later in analytics: wrong campaign, wrong locale, or an infinite loop that only appears when two rules on the same host point at each other. What I wanted early on was boring, bulletproof reliability: Same inputs → same decision. Two engineers simulating the same request against the same rule set should get the same target URL. Same resolution logic everywhere. Matching and destination resolution must not diverge between the "Test Rule" button in the dashboard and an actual click on a custom domain. Guards before cleverness. Rate limits and access checks run before anyone evaluates a ternary conditional in a destination string. Expressiveness is easy. Ordering is what saves you in production. The Pipeline, Told as a Story Picture a request hitting a hostname. Before the engine asks "which rule wins?", the request walks through a strict corridor of gates. Only then does it enter the rule loop. Gate 1: The Host Has to Exist If the hostname does not resolve to a domain or LinkShift
submitted by /u/nilukush [link] [留言]
Liquid syntax error: Variable '{{% raw %}' was not properly terminated with regexp: /\}\}/
Welcome to our weekly digest, where we unpack the latest in account and chain abstraction and the broader infrastructure shaping Ethereum. This week: Base ships its first independent upgrade with a TEE+ZK multiproof system and confirms native AA is next; Biconomy turns the ERC-8211 smart batching standard into a TypeScript SDK; LI.FI launches an enterprise intents engine for stablecoin and RWA flows; and Vitalik steps back from technical essays to write fiction. Base Launches Azul, Bringing Multiproofs to Coinbase's L2 Biconomy Ships Smart Batching SDK for ERC-8211 LI.FI Launches Intents Engine for Enterprise Cross-Chain Flows Vitalik Pivots to Fiction and Floats a "Trust Dependency" Framework Please fasten your belts! Base Launches Azul, Bringing Multiproofs to Coinbase’s L2 Base activated Azul on mainnet on May 28, its first network upgrade built entirely on its own stack. The headline feature is a multiproof system that pairs Trusted Execution Environment (TEE) proofs with Zero-Knowledge (ZK) proofs, advancing the Coinbase-incubated L2 toward Stage 2 decentralization. Either proof type can finalize a withdrawal independently, but when both agree, finality drops to as little as one day, far faster than the typical multi-day optimistic rollup wait. Crucially, permissionless ZK proofs can override permissioned TEE proofs if the two conflict, a design Base says meaningfully improves censorship resistance. The upgrade also makes base reth the sole execution client and introduces a new consensus client, phasing out older software. Node operators must migrate to the new stack to stay in sync. For AA and chain abstraction builders, the more important signal is what comes next: Base confirmed its end-of-June upgrade will include native account abstraction, an enshrined token standard and Flashblock Access Lists. The largest L2 by activity moving toward native AA is a meaningful pull on the whole ecosystem. Biconomy Ships Smart Batching SDK for ERC-8211 Biconomy released t
Introduction: The Controversial Rise of AI in Software Development The software development industry is at a crossroads. On one side, the rapid advancement of AI tools promises to revolutionize coding, automate repetitive tasks, and accelerate project timelines. On the other, a growing chorus of experts, led by figures like George Hotz , warns that the integration of AI agents into software development could become "one of the most costly mistakes in the field’s history." This bold prediction isn’t just hyperbole—it’s a call to scrutinize the mechanisms by which AI adoption could deform the very foundation of software engineering. At the heart of this debate are three critical failure points: over-reliance on AI without human oversight , insufficient real-world testing , and misalignment between AI capabilities and software development demands . Each of these factors acts as a stressor on the system, threatening to heat up development costs, expand systemic vulnerabilities, and ultimately break the delicate balance between innovation and reliability. Consider the causal chain: over-reliance on AI leads to a degradation of human expertise , as developers become less engaged in problem-solving. This, in turn, creates a feedback loop where AI-generated code, lacking nuanced understanding, introduces errors that go unnoticed. Without proper oversight , these errors propagate through systems, causing observable effects like reduced software quality and increased maintenance costs. Similarly, insufficient testing of AI agents in real-world scenarios means their failure modes remain unknown until they’re deployed at scale, risking systemic collapse in critical applications. The stakes are high. If unchecked, AI integration could lead to a loss of institutional knowledge , escalating development costs , and vulnerabilities in critical systems . The question isn’t whether AI has a role in software development—it’s how to implement it without deforming the field’s core princi