标签：#IDE

Unravel the tangled world of cords and find the ones you need to charge your gadgets and transfer data.

I’ve tried every single Kindle. Here’s how Amazon’s ebook readers stack up.

I have been an audio reviewer for 20 years. My time as a freelance headphones panelist at Wirecutter, and the multitude of reviews I’ve written for sites like Reviewed, Digital Trends, IGN, and now The Verge, have given me the chance to listen to hundreds of earbuds. Some were truly excellent, and some were pretty […]

Kit out your Apple tablet with our favorite stands, cases, keyboards, and styli.

Laptops for college should be portable, offer long battery life, and remain reasonably affordable. Based on testing hundreds of laptops, these are my top picks.

The 48-team World Cup is not the only historic soccer event this year. Four titans are vying for control of video game soccer in the fiercest battle the industry has ever seen.

IBM and HashiCorp have announced new LDAP secrets management capabilities in IBM Vault Enterprise 2.0, introducing a redesigned architecture to manage LDAP credentials, support password rotation, and automate the identity lifecycle. By Craig Risi

These bird feeders come with cameras and connected apps to let you see and learn about the birds in your neighborhood.

This article was originally published on aicoderscope.com TL;DR : Gemini 3.5 Flash went GA on May 19, 2026 and costs 50% less than Claude Sonnet 4.6 on input tokens ($1.50 vs $3.00/M). It generates code at ~284 tokens per second — roughly 4.7× faster than Sonnet 4.6. Cursor already lists it natively; Cline needs one extra config step. The trap: Flash's default thinking level is "medium," which is slower and pricier than "low," the setting Google specifically tuned for coding and tool-use loops. Gemini 3.5 Flash Claude Sonnet 4.6 DeepSeek V4-Flash Best for Fast agent loops, context-heavy analysis Complex refactors, instruction fidelity Cost-capped high-volume tasks Input / Output per 1M tokens $1.50 / $9.00 $3.00 / $15.00 $0.14 / $0.28 Context window 1M tokens 200K tokens 1M tokens Terminal-Bench 2.1 76.2% — — Output speed ~284 t/s ~60 t/s — Max output per request 65,536 tokens 64K tokens 64K tokens The catch Output at $9/M erodes savings on code-gen 15× pricier output than Flash No vision, MIT-licensed Honest take : Use Gemini 3.5 Flash with Cline for multi-step agent tasks where round-trip latency compounds and context windows run large. Stay on Claude Sonnet 4.6 when you need a hard refactor to land perfectly on the first try — Sonnet's 79.6% SWE-bench Verified score still leads Flash's on correctness benchmarks. The cost math that does and doesn't work Gemini 3.5 Flash charges $1.50 per million input tokens and $9.00 per million output tokens. Against Claude Sonnet 4.6 at $3.00/$15.00, the input side is a genuine 2× saving. The output side is almost the same story: $9 vs $15 is 40% cheaper per generated token. Run the numbers on a typical Cline coding session: 8 tool calls, reading 12 files (roughly 20,000 context tokens), generating 500 lines of code output (~7,000 output tokens). Sonnet 4.6: (20K × $3 + 7K × $15) / 1,000,000 = $0.165/session Gemini 3.5 Flash: (20K × $1.50 + 7K × $9) / 1,000,000 = $0.093/session That's 44% cheaper per session. At 50 sessions a m

With Father's Day on the horizon, happening June 21st, it's time to start thinking about what kind of gifts you want to buy for the fathers you care about. You know your dad best - he may be a man of simple pleasures who wants nothing more than to share a meal or drinks with […]

We've all been there. Your first encounter with authorization looks something like this: if ( user . role === " ADMIN " ) { // allow access } It works. It's simple. It ships fast. And then, three months later, your application has grown, requirements have shifted, and you're staring at a codebase where authorization logic is scattered everywhere—APIs, services, UI components—like a puzzle that nobody remembers how to solve. The truth is: this approach doesn't scale. Not because it's inherently flawed, but because it conflates two very different concepts that should never be mixed. The Core Mistake: Confusing Identity with Capability Here's the problem we're actually trying to solve. As your application grows, you inevitably end up writing code like this: if ( user . role === " BRANCH_MANAGER " || user . role === " SYSTEM_ADMIN " ) { // allow access } Then a stakeholder asks: Can we create a hybrid role? Or: We need Auditors who can export reports but not edit records. And suddenly your role logic explodes into an unmaintainable mess. The fix isn't adding more conditions. The fix is understanding that roles and permissions answer fundamentally different questions. Roles Define Identity Roles are categories of users. Examples: SYSTEM_ADMIN CLIENT BRANCH_MANAGER AUDITOR Roles answer: Who is this user? They establish high-level authorization boundaries. Examples: Staff Portal vs Customer Portal Internal Admin Area vs Public Application Employee Features vs Client Features Think of roles as identity labels . Permissions Define Capability Permissions represent atomic actions. Examples: LOAN_APPROVE USER_DELETE REPORT_EXPORT ACCOUNT_EDIT Permissions answer: What can this user actually do? Your application should not constantly ask: What role are you? Instead, it should ask: Do you have permission to perform this action? Because: Users have Roles Roles contain Permissions Code checks Permissions That distinction changes everything. Always Decouple Identity from Capability T

The FTX co-founder is serving a 25-year sentence, doled out in 2024.

Two weeks ago I shared a collection of 6 financial calculators. The response was incredible, so I kept building. Today, fi-calc.com has 25 completely free calculators covering every major personal finance need: 🏠 Housing • Mortgage Calculator (full PITI + amortization schedule + pie chart) • Rent vs Buy Calculator • House Affordability Calculator • Refinance Calculator 💰 Investing & Retirement • Compound Interest Calculator • Investment Return Calculator • Future Value & Present Value Calculators • ROI Calculator • Retirement Savings Calculator • 401(k) Calculator • FIRE Calculator (Financial Independence) 💳 Debt & Loans • Loan Comparison Calculator • Auto Loan Calculator • Student Loan Calculator • Credit Card Payoff Calculator • Debt Payoff Calculator (Avalanche method) 📊 Everyday Finance • Budget Planner (50/30/20 rule) • Savings Goal Calculator • Inflation Calculator • Salary & Take-Home Pay Calculator • Net Worth Calculator • Currency Converter (15+ currencies) • CD Calculator • Sales Tax Calculator ✨ Tech Stack • Pure vanilla HTML/CSS/JS — no frameworks • Chart.js for animated interactive charts • Responsive design (mobile-friendly) • All calculations run client-side in your browser • No data collection, no accounts, no cookies 🔗 Give it a try: fi-calc.com The entire site is free and open. I built it because I was tired of calculator sites with paywalls, signup walls, and bloated ad experiences. Would love feedback from the community! What other calculators should I build next?

Three years ago we had our first real outage. Six hours of downtime. Thousands of angry users. Multiple executives on the call. Here's what we did right, what we did wrong, and what we'd do differently. What we did right 1. Communicated immediately. The moment we knew we had a problem, we updated the status page and emailed our biggest customers personally. Not when we had answers. When we had a question. 2. Had a single incident commander. One person making calls. Not a committee. When the CEO tried to direct technical work, the IC politely rerouted and told her where her help was actually needed (talking to customers). 3. Took care of our people. During hour 4, I ordered food. During hour 5, I forced the primary engineer off the call for 20 minutes to walk outside. Long incidents destroy people. You have to feed them and force them to rest. 4. Wrote it down as we went. We had a shared doc with a live timeline. When the post-mortem came, we had every decision captured. What we did wrong 1. Tried to fix the root cause during the incident. For the first 2 hours, we were digging into why the database was struggling. We should have been mitigating (rolling back) first. 2. Let too many people 'help.' By hour 3, we had 12 engineers in the call. Half of them were useless. The IC should have kicked people out sooner. 3. Gave optimistic estimates. 'We'll be back in 30 minutes.' We were not back in 30 minutes. That miscommunication was worse than saying 'unknown.' 4. Didn't prepare the executive communication. The CEO had to answer customer questions in real time with no script. We should have drafted talking points for her after hour 1. What we'd do differently Mitigate first, investigate second. Always. Cap the number of active engineers at 4 during an incident. Others go on standby. Default to 'unknown' for estimates. Only give a number when we're sure. Assign someone explicitly to 'executive liaison.' Their job is to keep the C-suite informed without interrupting the tec

After 16 weeks of daily use, our WIRED testers saw visible hair regrowth with these red-light therapy devices.

Every interface you create is a constraint on future behavior. Every abstraction emphasizes certain patterns and discourages others. You are not just building tools. You are shaping how people think about problems. I have been paying attention to how API design encodes values, not just technical decisions, but philosophical ones. What Your API Communicates Consider these design choices: Mutability vs Immutability. Do you encourage stateful modification or pure functions? This is not just about performance. It is a philosophy about side effects and reasoning. If your default is mutable state, you are telling users that local mutation is fine, that they can reason locally. If your default is immutability, you are telling them to think about data flow. Explicit vs Implicit. Do you make users specify parameters or infer from context? This trades convenience for transparency. I lean toward explicitness. Magic is convenient until you need to debug it. Fail Fast vs Fail Safe. Do you throw exceptions or return error codes? This encodes beliefs about who should handle errors and when. Fail-fast says "don't let bad state propagate." Fail-safe says "keep running if you can." Both are defensible, but they lead to very different code. My Design Values When I build libraries, I try to encode: Explicitness over magic. I would rather make users type more than hide behavior behind conventions they have to discover. Composition over inheritance. Small pieces that combine flexibly beat deep class hierarchies. Clarity over cleverness. Code should be obvious, not impressive. Safety by default. The easy path should be the safe path. Why This Matters Your API is a value statement. It says what you think is important, what you think is dangerous, and how you think about the problem domain. This is why I spend so long on interface design. The APIs we create shape future thought. They outlast the code that implements them, because the patterns they teach persist in the minds of the people wh

I tried all the top models to find the best 3-in-1 Apple charging stations, pads, and more. Keep your iPhone, Apple Watch, and AirPods topped up with these WIRED-tested docking systems.

These are the best Bluetooth, Wi-Fi, GPS, and cellular gadgets to ensure you never lose anything ever again.

We logged thousands of test miles to bring you the best running shoes for every pace, ability, and running goal.

Up front, so there's no confusion: the app I'm describing (Nightmare TV) is a player only . You bring your own M3U / Xtream Codes playlist — it ships with no channels and no content. This post is about the playback engineering, not about where streams come from. Think "VLC for IPTV," not a content service. The problem that started it I watch a lot of live content on my PC — sports, mostly. And every IPTV player I tried on Windows fell into one of two buckets: An Android app running in an emulator. TiviMate and the good mobile players are Android-only, so on a desktop you end up in an emulator or a VM. Input lag, no real HDR path, fans spinning. A thin ExoPlayer / libVLC wrapper. These run natively, but most of them treat HDR as "pass the HDR10 metadata to the display and hope." On an SDR panel — or even a lot of HDR panels — bright skies in a football match blow out to a flat white blob, and 4K HEVC with a DTS track stutters because the decode path isn't doing what you think it is. I wanted the thing that didn't exist: a native Windows player with a reference-grade video path. So I built it on libmpv — the same playback core mpv uses — with a Flutter desktop shell on top for the UI. This post is the part I actually find interesting: the HDR tone-mapping pipeline. Why HDR "just passing through" isn't enough HDR10 content is mastered in the PQ (ST.2084) transfer function against a mastering display — often 1000 nits, sometimes 4000. Your screen is whatever it is: a 350-nit SDR laptop, a 600-nit "HDR400" monitor, an 800-nit OLED. If you map PQ straight to the panel, everything above the panel's peak just clips — all the highlight detail collapses to maximum white. Tone-mapping is the process of intelligently compressing the mastering range into the display range so you keep highlight detail instead of clipping it. The naive version (a fixed curve, or clipping) is what most wrapper players ship. The good version adapts to both the content and the display. The pipeline H