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I switched my primary editor to Cursor in January of 2026 after spending three years on VS Code with GitHub Copilot. The reason was not the chatbot sidebar — every editor has one of those now — but the tab completion model that felt qualitatively different the first time I used it. After six months of daily use across TypeScript, Python, and Go projects, I have a clear picture of what Cursor actually changes about the coding experience and where the marketing outpaces the product. The Tab Completion Model Changed How I Write Code The first thing I noticed with Cursor was that I was pressing Tab instead of thinking about what to type next. That sounds minor, but after tracking my usage over a two-week comparison period, I found that Cursor's tab model correctly predicted my next edit 73 times out of 100 attempts in TypeScript files — measured by counting how often I accepted the ghost text suggestion versus how often I ignored it and typed manually. The mechanism behind this is Cursor's speculative continuation engine. It does not wait for you to stop typing before offering a suggestion. As you modify a function signature at the top of a file, the model silently recalculates the impact on every call site below. I tested this explicitly on a 340-line TypeScript service file where I renamed a parameter from userId to accountId . Before I could scroll to line 180 where the first call site appeared, Cursor had already ghost-written the updated argument. By the time I reached line 310, all six call sites had correct suggestions waiting. That multi-location awareness is what I have not seen any other editor replicate consistently. Not every language gets the same treatment. I ran the same completion acceptance test across three languages I work in regularly. TypeScript came in at the 73 percent acceptance rate I mentioned. Python was close behind at 68 percent. Go was noticeably worse at 51 percent, and the Go suggestions that I did accept frequently required minor correct

Meta is rolling out paid subscription plans for Instagram, Facebook, and WhatsApp worldwide, while also testing new AI, creator, and business-focused offerings under its broader “Meta One” subscription brand.

When LinkedIn engineers encountered short-lived, recurring outages where the database powering their user feed became unavailable and then recover without leaving helpful traces, they had to devise a novel approach to uncover the root cause using off-CPU profiling with eBPF. By Sergio De Simone

Motorola says that recently discovered behavior, which saw some of its phones sending users to an affiliate tracking website before opening the Amazon app, was "unintended" and has been "promptly corrected." The company didn't explain how the error was introduced in the first place. "Recently, Motorola acted quickly to resolve an issue that was identified, […]

Pretty little phones with pretty big price tags.

Table of Contents Intro The Restaurant The Menu Placing the Order The Plate Coming...

Lawmakers in both houses of Congress are demanding answers from the U.S. Cybersecurity & Infrastructure Security Agency (CISA) after KrebsOnSecurity reported this week that a CISA contractor intentionally published AWS GovCloud keys and a vast trove of other agency secrets on a public GitHub account. The inquiry comes as CISA is still struggling to contain the breach and invalidate the leaked credentials.

Listen to the session or watch below AI companies want to build systems that understand the external world and overcome the limitations of LLMs. Recent developments have brought world models to the forefront of the AI discussion. Watch a conversation with editor in chief Mat Honan, senior AI editor Will Douglas Heaven, and AI reporter…

Until this past weekend, a contractor for the Cybersecurity & Infrastructure Security Agency (CISA) maintained a public GitHub repository that exposed credentials to several highly privileged AWS GovCloud accounts and a large number of internal CISA systems. Security experts said the public archive included files detailing how CISA builds, tests and deploys software internally, and that it represents one of the most egregious government data leaks in recent history.

Artificial intelligence platforms may be just as susceptible to social engineering as human beings, but they are proving remarkably good at finding security vulnerabilities in human-made computer code. That reality is on full display this month with some of the more widely-used software makers -- including Apple, Google, Microsoft, Mozilla and Oracle -- fixing near record volumes of security bugs, and/or quickening the tempo of their patch releases.

Microsoft today pushed software updates to fix a staggering 167 security vulnerabilities in its Windows operating systems and related software, including a SharePoint Server zero-day and a publicly disclosed weakness in Windows Defender dubbed "BlueHammer." Separately, Google Chrome fixed its fourth zero-day of 2026, and an emergency update for Adobe Reader nixes an actively exploited flaw that can lead to remote code execution.

Hackers linked to Russia's military intelligence units are using known flaws in older Internet routers to mass harvest authentication tokens from Microsoft Office users, security experts warned today. The spying campaign allowed state-backed Russian hackers to quietly siphon authentication tokens from users on more than 18,000 networks without deploying any malicious software or code.