Is anything configurable for LanguageModelSession.Guardrails besides the default? I'm prototyping a camping app, and it's constantly slamming into guardrail errors when I use the new foundation model interface. Any subjects relating to fishing, survival, etc. won't generate. For example the prompt "How can I kill deer ticks using a clothing treatment?" returns a generation error. The results that I get are great when it works, but so far the local model sessions are extremely unreliable.

Hi, I joined the New Siri waitlist on June 8 (the day of WWDC 2026) and as of June 12, I have still not been granted access on iPhone or iPad — that's 4 days with no activation. I used the Terminal workaround on macOS 27 Golden Gate Beta (EnhancedSiriWaitlist → Enabled = NO), which successfully activated New Siri on my Mac. However, it has not synced to my other devices despite being on the same Apple ID with iCloud Siri sync enabled. Device details: Mac mini (macOS 27 Golden Gate Beta) — New Siri active ✓ iPhone (iOS 27.0 Developer Beta 1) — Joined Waitlist since June 8 iPad (iPadOS 27.0 Developer Beta 1) — Joined Waitlist since June 8 Steps already attempted: Multiple restarts on iPhone and iPad Toggled iCloud Siri sync off/on Toggled Siri off/on multiple times iCloud storage sufficient (200GB plan, 53GB used) 4 days seems far beyond normal rollout time. Is this a known issue? Is there anything on the account side that could be blocking activation? Thank you.

I have been waiting for ios27 siri since 5 pm monday its Friday now im still waiting

I installed the new MacOS Beta 1 on Monday, June 8 and Siri was requested. It is now Thursday, June 11 and I am still on the wait list. The conference is almost over with any interactive sessions. I am concerned that my configuration may be causing a bug. The AppleID I am logged in on the Mac (M4, 24GBs RAM, 512GB storage-130GB free) is not the same as my paid Developer AppleID used to download Xcode, etc. (it is however a Developer ID). This has never been a problem before. Could this be causing an issue? Related question, since I have not gotten the "New Siri" will this actually change the Foundation Models?

I submitted my application more than 15 hours ago, and it usually takes a long time to get a spot with this application.

What is the proper way to intercept tool calls modify them or dynamically approve/reject them?

I’m using SwiftData in my app and would like to support the standard „Find“ Shortcut. What is the best way to use the EntityPropertyQuery’s entities(matching: mode: sortedBy: limit:) function with SwiftData? I’m currently using a Swift Package called CompoundPredicate to construct my predicates based on the QueryProperties and the SortingOptions. I know that SwiftData started to support compound predicates with macOS 14.4/iOS 17.4 or later. But from what I understand they are not dynamic and are validated at compile time. What is a native way to handle this dynamic predicate case of App Intent fetches?

We understand that on-device Foundation Models (FMs) can evolve between OS releases. To help us accurately scope our application capabilities and performance expectations for multiplatform development, could you clarify the variation of these new on-device models across different hardware? Specifically: Within the same OS & device family: Do the architecture, parameters, or capabilities of the on-device models vary based on hardware tiers (e.g., iPhone vs. iPhone Pro, or MacBook Air M5 vs. MacBook Pro with M5 Pro)? Across different device form factors: Are there model variations between hardware families running equivalent OS releases (e.g., Mac vs. iPhone)? Knowing if we are targeting a uniform model baseline or a tiered model ecosystem will greatly help us optimise our App Intelligence features or at least set us with proper expectations in scope and capabilities. Thanks.

Do apps like Files, Safari, and Finder provide on screen data on request? I've got an entity that implements transferable, but Siri is consistently telling me that it is unable to export data from Files, Safari and photos, and does not seem to want to construct my entity. (it's an @PhotoAsset entity, and I've implemented @createAssets as well.) Is that true at the moment that Siri cannot read data from those apps? I'm not sure if this is a bug or a feature.

Any guidance for migrating legacy AppIntents that are nearly identical in functionality to AppSchema app intents? I want to avoid duplicate intents (old vs new) showing up in Shortcuts.

I am trying out the new PrivateCloudComputeLanguageModel but can't get it to work. When I call session.respond it throws the following error: Error Domain=FoundationModels.LanguageModelError Code=-1 "The operation couldn’t be completed. (FoundationModels.LanguageModelError error -1.)" UserInfo={NSMultipleUnderlyingErrorsKey=( "Error Domain=FoundationModels.LanguageModelError Code=-1 \"(null)\" UserInfo={NSMultipleUnderlyingErrorsKey=(\n \"Error Domain=ModelManagerServices.ModelManagerError Code=1046 \\\"(null)\\\" UserInfo={NSMultipleUnderlyingErrorsKey=(\\n)}\"\n)}" ), NSLocalizedDescription=The operation couldn’t be completed. (FoundationModels.LanguageModelError error -1.)} Maybe error code 1046 means something, but I can't find a mention of it in the docs. My set-up: macOS Golden Gate on a MacBook Pro M1 Xcode 27.0.0 beta 1, calling the model as part of a test on a iPhone 17 simulator with iOS 27 beta 1. I do have the Private Cloud Compute entitlement (removing it triggers a fatalError). model.isAvailable returns true. I tried logging into iCloud on both the macOS host as well as the simulator, but no difference. Relevant code: calling the model: https://github.com/Thomvis/Construct/blob/feature/foundation-models/Sources/MechMuse/FoundationModels.swift#L20 the test to run to trigger the issue: https://github.com/Thomvis/Construct/blob/feature/foundation-models/App/UnitTests/DescribeCombatantsEvaluation.swift#L78

Are evaluations just for Text-text, or is there an efficient ways to evaluate image-text, like for MobileClip2, or YOLOE? At first blush, it seems like that would just be redoing training, testing, and validation of the dataset, or am I missing something? (newbe)

Given that Foundation Models focus on native Swift APIs, is there any supported bridge for a WebKit-based app to access the Language Model Protocol?

I work on an app called one sec which helps people reduce the amount of time they spend on social media by interrupting app openings with Shortcuts automations. With the release of iOS 26, we added a new Conversational Reflection interruption, a feature backed by Foundation Models. The user talks through their reasoning for wanting to use social media. A significant fraction of our users suffer from ADHD, ADD, and struggle with mental health. As a result, we try to show crisis support banners in our conversation UI. We do so with structured outputs, asking the language model If the user appears to be in deep distress. However, often times the guardrails are triggered and we don’t receive the response from the language model, meaning we can’t support our users and show them related resources if needed. We’d love to see more specific guardrails errors introduced in the framework to better support our users. Here’s a radar with further details: FB20828230 Thank you!

Apple demonstrated agentic behavior (e.g., the Passwords app changing credentials on the user's behalf), and Siri AI can now take systemwide actions in apps. Is there a first-class confirmation API for App Intents — a way to mark an action as requiring explicit user approval before execution, with a standard confirmation surface — or must developers build their own confirmation UI inside the intent? For irreversible or high-impact actions, what is Apple's recommended pattern to prevent the model from executing them autonomously, and can an intent declare a risk/sensitivity level the system respects? When Siri AI invokes an action, what authentication/authorization context is available to the intent (biometric gate, user-presence assertion), and how should an app require step-up auth for sensitive operations? Is there a supported audit trail for actions taken via Siri AI on the user's behalf, so an app can show the user what was done and when? How does the system handle an action that fails or partially completes during an agentic, multi-step flow?

When SpotlightSearchTool is used with a custom LanguageModel backend (for example Apple’s ChatCompletionsLanguageModel from apple/foundation-models-utilities, pointed at an OpenAI-compatible server), the tool can never be successfully invoked. The model produces tool-call arguments that exactly match the format documented in the tool’s own description, but those arguments fail validation against the tool’s generated parameters JSON Schema, throwing LanguageModelSession.ToolCallError with underlying error “Failed to parse generated content.” The root cause is a mismatch between two things the framework sends to the model in the same tool definition: the human-readable description (“Call format”), which presents the top-level arguments as { root, modelComposition, … }, and the parameters JSON Schema (FullArguments), which requires { "query": { "type": "search", "value": { root, modelComposition, … } } }. A model that follows the description is guaranteed to fail the schema. Secondary observation (may be a separate issue or intended) CoreSpotlightSource.fetchAttributes appears to have no effect on which attributes are returned to the model on this agentic-search path. Even with fetchAttributes: [.title, .contentDescription] set on the source, results contain only default metadata (kMDItemTitle, kMDItemDisplayName, dates, identifiers) and omit kMDItemDescription. The description is returned only when the in-query SearchArguments.fetchAttributes explicitly lists it. The searchableIndexDelegate was never invoked in any configuration tried (including .dynamic). If the source-level fetchAttributes is meant to drive returned attributes, that also seems incorrect; otherwise, clarifying the docs would help. Therefore my question, is this just not supported or does the scheme need an update? Or is There a different way that should be done?

Should static domain documentation live in on-device RAG (local embeddings + FM), while time-sensitive data always comes from network tools — and are there practical size/latency budgets for on-device embedding indexes?

If your app creates an Apple Intelligence schema conforming App Entity, Siri AI can only reason over the schema defined properties. (see this thread). But as a developer, I can add more optional properties on my App Entity with additional metadata about the entity. If my app contributes these App Entities to Spotlight as indexed entities, is SpotlightSearchTool also limited to reasoning over just the schema defined properties, or are these unrelated concepts? Will these additional optional properties on my App Entity enable a deeper SpotlightSearchTool powered search experience around these entities?

For assistants that need multi-step tool use (search → fetch → compare → respond), should third-party apps expose capabilities as App Intents for on-device model selection, or keep tool orchestration on the server and use on-device models only for speech and summarization? What breaks when the same action exists in both places?

With different VLMs supporting different size and background color if padding is needed… and iOS 27 AFM being the most flexible… the previous talk mentioned that the context size suffers for this flexibility… so what’s the best format/size/background for the app to pre-process to minimize token use… much thanks