Siri can finally do things inside your apps without you babysitting it. Apple's iOS 27.3 update, rolling out Tuesday, lets Siri AI carry out actions across third-party apps, and a new "app skills" feature lets developers bundle multiple tasks into one action.
If you ship an iOS app, this is the part to read twice. Developers can package workflows into app skills, and users won't need to say the app's name while it's in the foreground, during a Live Activity, or mid-conversation with Siri AI. That means fewer dead-end voice commands and more chances for your app to be the thing that actually completes the request. Ride-share apps get the most obvious win: users can request a ride and follow the Live Activity, then say "Hey Siri, change my ride pickup to a new address" while they wait.
Apple is also turning the same capabilities loose on its own apps, including Calendar, Files, Finder, Journal, Mail, Maps, Messages, Music, Notes, Photos, Preview, Reminders, Safari, Shortcuts, and Weather. Users can ask Siri AI what it can do in each app, find a coffee shop they visited last week, or archive files untouched for over a year. The update runs on personal context, natural language, and on-screen awareness. Apple had previously opened a smaller set of features to third-party developers, so this is a real expansion, not a rename.
Revolut just ran AI coding at scale on its own models, and the bill fell roughly 90%. The fintech made self-hosted models its default. Yes, really.
If you're paying per token for Claude Code or Codex, this should make you itchy. Revolut's team found that self-hosting GLM 5.1 cost about a tenth of the big API options. Debugging and wiring the model into Jira and Confluence tickets consumed the effort. Code generation was the easy part, and most teams underestimate that gap.
The numbers: Revolut rolled AI coding tools out to roughly 2,000 engineers and saw 60% faster coding time and 70% faster lead time. It now serves GLM-5.3 on 56 Nvidia B200 GPUs, with sub-3-second time to first token at around 256K context. Engineers get about 200 tokens per second, and around 800 after 5 pm. The catch? GLM is text only, so UI work still goes to Gemini or GPT through a model router. Let's dive deeper…
In today's ContentBuffer update: