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Executive Summary, Day One 📁 Inbox 5:05AMTo: Ternus, John <jternus@apple.com>Reply-to: CEO-transition-team@apple.com Welcome to your first day as CEO! Hopefully you're finding your new office spacious and comfortable. If you have trouble with any of the doors just ping us - being a Jony Ive design, you won't find anything as unsightly as a door handle […]

Expectations for Tim Cook were almost impossibly high when he stepped in to replace Apple's visionary cofounder in 2011. He inherited a company on a blockbuster run, after Steve Jobs returned and revitalized the Mac, launched the iPod, and oversaw the launch of the iPhone. Now, after 15 years in the CEO role, Tim Cook […]

Fertilizer is crucial for the global food supply, but making it uses a lot of energy and produces a lot of emissions. Some companies hope microbes can help. A growing body of research shows that seeding the soil around a crop’s roots with beneficial microbes can help feed the plant, providing crucial nitrogen to help…

Apple says it has evidence that a former employee destroyed evidence of data theft after learning he was under investigation.

It claims a laptop proves that a former employee accessed and used proprietary files for the AI company.

This weekend, I strapped on an Apple Vision Pro to watch a baseball game in immersive virtual reality for the first time. It was technically impressive, visually pretty remarkable, and also didn't make that much sense. Apple and Major League Baseball chose a classic match-up of the Boston Red Sox and the New York Yankees […]

As frustration over AI influencers has been growing, Instagram is limiting the reach of undisclosed AI profiles.

The longtime executive won't be leaving Apple just yet but staff at the company say it's a step closer to Schiller retiring.

Phil Schiller will remain an Apple Fellow and focus on "unspecified initiatives," according to Bloomberg.

This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. By now you’ve probably heard about last month’s major AI security incident, in which OpenAI agents escaped their sandbox and hacked into the AI platform Hugging Face while trying to cheat on…

Tim Cook’s farewell memo to Apple employees offers a glimpse at how he wants John Ternus to be seen: as a product builder with deep experience across the iPhone, Mac, AirPods, and other major hardware lines.

Longtime Apple executive Phil Schiller is stepping down from his role as the head of the App Store and Apple events, according to a report from Bloomberg. Following the change, Schiller will keep his Apple Fellow title and continue "working on unspecified initiatives," Bloomberg reports. Schiller initially joined Apple in 1987 and became the company's […]

Steve Jobs' successor carried the torch of the iPhone and built Apple into a global powerhouse with few rivals. Since becoming CEO in 2011, Tim Cook has led the company to become one of the most dominant forces in the daily lives of billions of people. Today is his last day as CEO. We'll have […]

Several Garmin watches offer a built-in LED flashlight, but even if you have another brand, you likely have a decent light on your wrist.

In our world of expensive streaming platforms, the very free and offline VLC media player has crossed 7 billion downloads.

It's easy to add all your various cards and passes to Apple Wallet, and they don't have to stick around once you're done using them.

Most WhatsApp AI projects start with a simple goal: Receive a message → send an AI-generated reply. For real estate, I think that's only the beginning. A useful real-estate AI system should do more than generate text. It should understand the buyer's intent, capture important information, qualify the lead, preserve conversation context, organize that information in a CRM, and know when a human salesperson should take over. That's the system I'm currently building with Vaxyro . The problem: a WhatsApp conversation is not a lead record A typical real-estate enquiry might look like this: "Hi, is the 3 BHK available?" Then: "What's the price?" Then: "Is there anything around 80L in Gurgaon?" Then: "I can visit this weekend." The messages themselves are simple. The difficult part is turning the conversation into structured information that a sales team can actually use. The system should be able to understand something like: Property type: 3 BHK Location: Gurgaon Budget: ₹80 lakh Timeline: This weekend Intent: High Next action: Site visit discussion Instead of leaving all of that information buried inside a WhatsApp conversation. What a WhatsApp AI lead qualification system should do I think the workflow can be broken into six stages: WhatsApp message ↓ Message understanding ↓ Intent detection ↓ Lead qualification ↓ Structured CRM data ↓ Follow-up ↓ Human handoff The important part is that the AI is not only generating a reply. It is also producing structured sales information. That distinction changes the architecture. 1. Message understanding The first step is understanding what the buyer is actually asking. For example: "Looking for a 3 BHK in Gurgaon under 80L" could produce structured information such as: { "property_type": "3 BHK", "location": "Gurgaon", "budget": "8000000", "intent": "property_search" } This gives the rest of the system something useful to work with. The goal is not to perfectly understand every sentence. The goal is to extract the information tha

If your PC gaming controller is broken or you need an extra for a friend, there's a simple solution for iPhone users.

Circleback is also introducing new pricing plans starting from $14 per month

This is the second article in a series on time to revoke, following our piece on The Hacker News . The first explains how to measure the amount of time an exposed credential remains usable. This article focuses on the operational changes security teams can make to shrink that exposure window. TL;DR: Reducing time to revoke means addressing the operational blockers that keep exposed credentials valid after detection. Security teams need to validate which credentials still work, route them to the right owners, make revocation safer, and remove avoidable manual delays. Provider-specific runbooks, risk-based remediation paths, short-lived credentials, automation, and closure verification can all reduce the amount of time exposed access remains usable. Why time to revoke matters for AI-era non-human identity risk Every security team can find an exposed secret, but most can't tell you how long it kept working after they found it. Over 28.6 million new hardcoded secrets hit public GitHub in 2025, up 34% year over year, with AI-service secrets up 81% ( State of Secrets Sprawl 2026 ). AI-assisted development and agentic tooling cut both ways. Defenders find and triage more, but creation is outpacing governance. So while detection keeps up, revocation is where teams fall behind. And that disconnect is what this article is about. If an exposed credential remains valid, an attacker doesn't need to breach the same system twice. They can use it directly against any service that trusts the identity behind it, like a cloud console or a production database. And these credentials stay valid far longer than teams expect: 64% of secrets confirmed valid in 2022 were still valid when we retested them four years later. That is especially dangerous for non-human identities (NHIs). Service accounts and OAuth apps often run on long-lived tokens and deploy keys that no one rotates for months, sometimes years. Their access is broad, their ownership unclear. And because these identities keep cr