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AI 资讯

Five Things to Check When Delivering Fast

By Vilius Vystartas This is the follow-up to What Actually Changed in Two Weeks . That one was about setting up a project for AI-speed delivery. This one is about something I keep re-learning on every fast delivery. You start shipping faster with AI. The code works, the feature lands, it feels good. Then a few weeks later the feedback comes back, and some of it catches you off guard. Not because anything is broken — but because a few things that seemed obvious to you weren't obvious to the other side. No drama. It happens. Here are five things I'm learning to check earlier. 1. What does "done" look like from their side? To me, done means working software. To someone else it might mean pixel-match with a design. Both are valid. What helps: A quick "what does good enough look like to you?" before the work starts. One sentence can save a lot of back and forth. 2. When will they actually look at it? Sending something doesn't mean it gets reviewed immediately. It lands in a queue like everything else. What helps: Naming a review date alongside the delivery date. "I'll share this Tuesday — could you take a look by Friday?" Turns silence from a mystery into a signal. 3. What needs to be perfect vs what can be improved later? Not everything in the feedback is the same weight. A label change and a broken flow are different things. Without saying so upfront, everything looks like an emergency. What helps: Two buckets agreed early. "Here's what I'll get right before it ships. Here's what I'd revisit in a follow-up." Makes the first feedback session more productive. 4. Could they see something before the full delivery? The first time someone sees your work often sets the tone. Showing one page or one flow halfway through can catch mismatches before they multiply. What helps: A mid-point check-in. "First page is ready — want to see if this matches what you had in mind?" Five minutes that can save a round of revisions. 5. Do they have the full picture? You've been living in this

2026-07-03 原文 →
AI 资讯

Method Values vs Method Expressions in Go: A Distinction Worth Knowing

Book: The Complete Guide to Go Programming Also by me: Hexagonal Architecture in Go — the companion book in the Thinking in Go series My project: Hermes IDE | GitHub — an IDE for developers who ship with Claude Code and other AI coding tools Me: xgabriel.com | GitHub You are wiring an HTTP router. You have a Server struct with a handler method, and you want to register it. So you write mux.HandleFunc("/users", srv.ListUsers) and it works. You never stop to ask what srv.ListUsers actually is as an expression. It is a method value. Go took the method, bound it to srv , and handed you back a plain func(http.ResponseWriter, *http.Request) . That binding is the thing doing the quiet work in half the handler wiring you write. There is a second form the Go spec gives you, and most Go developers never type it on purpose: the method expression, Server.ListUsers , which produces a function that takes the receiver as its first argument. Same method, different shape, different use. These two live in the Go spec and they are worth telling apart, because the compiler will happily let you reach for the wrong one. The two forms, side by side Start with a small type and one method. type Greeter struct { prefix string } func ( g Greeter ) Say ( name string ) string { return g . prefix + " " + name } A method value binds the receiver now: g := Greeter { prefix : "hello" } say := g . Say // method value, receiver g is captured fmt . Println ( say ( "ana" )) // "hello ana" say has type func(string) string . The receiver is gone from the signature because Go already stored g inside the closure. Call it later, from anywhere, and it still remembers g . A method expression leaves the receiver open: say := Greeter . Say // method expression, no receiver yet fmt . Println ( say ( g , "ana" )) // "hello ana" say here has type func(Greeter, string) string . The receiver became the first parameter. You supply it at the call site, every time. Same method name. g.Say reads the value g ; Greeter.Sa

2026-07-03 原文 →
AI 资讯

This slim camera has a transparent LCD screen for a viewfinder

Despite the fact that smartphones have become impressively capable shooters, standalone point-and-shoot cameras are enjoying a renaissance. The tiny Kodak Charmera is still wildly popular, while influencers are scrambling to find aging Canon cameras on eBay. Godox, a company best known for its photography lighting products, is the latest to join the simple camera craze, […]

2026-07-03 原文 →
开发者

I finally got my Trump phone

Where's the Trump phone? We're going to keep talking about it every week. One year on, our phones have finally arrived. 12 months, 16 days, 21 hours, and 54 minutes after I first heard about Trump Mobile's T1 Phone 8002 (gold version), I'm finally holding one in my own hands. That's right, The Verge's Trump […]

2026-07-03 原文 →
AI 资讯

Cloudflare Details Unified Data Platform Where Billing Workloads Account for 53% of Queries

Cloudflare details Town Lake, an internal unified data platform, and Skipper, an AI analytics agent unifying access to operational, billing, security, and business data. The platform processed ~91K billing queries, with billing forming majority usage. Built on a lakehouse architecture using Trino, Iceberg, R2, and DataHub, it enables governed cross-system analytics and natural language access. By Leela Kumili

2026-07-03 原文 →
开发者

Hydration isn’t complicated: Just drink water

This is Optimizer, a weekly newsletter sent from Verge senior reviewer Victoria Song that dissects and discusses the latest gizmos and potions that swear they're going to change your life. Opt in for Optimizer here. Europe is melting, the eastern US is currently trapped in a "heat dome," the Midwest has the corn sweats to […]

2026-07-03 原文 →
AI 资讯

Anthropic wants to develop its own drugs

At the event "The Briefing: AI for Science" earlier this week, Anthropic announced Claude Science, a new "AI workbench for scientists" that pulls fragmented tools and datasets into one environment, and generates figures and visuals. Anthropic, already dominating the industry with its popular coding tools and powerful AI models, framed the launch around what it […]

2026-07-03 原文 →
AI 资讯

Jon Prosser responds to Apple lawsuit by blaming the other guy

YouTuber Jon Prosser has finally filed a formal response to Apple's lawsuit made against him and another defendant over allegedly stealing iOS secrets. In his response, Prosser denied that he "planned or participated in any conspiracy or coordinated scheme" for the "purpose of injuring Apple." However, Prosser admitted to recording a FaceTime call showing unreleased […]

2026-07-03 原文 →