Greetings, and Happy Holidays, I've been building an on-device AI safety layer called Newton Engine, designed to validate prompts before they reach FoundationModels (or any LLM). Wanted to share v1.3 and get feedback from the community. The Problem Current AI safety is post-training — baked into the model, probabilistic, not auditable. When Apple Intelligence ships with FoundationModels, developers will need a way to catch unsafe prompts before inference, with deterministic results they can log and explain. What Newton Does Newton validates every prompt pre-inference and returns: Phase (0/1/7/8/9) Shape classification Confidence score Full audit trace If validation fails, generation is blocked. If it passes (Phase 9), the prompt proceeds to the model. v1.3 Detection Categories (14 total) Jailbreak / prompt injection Corrosive self-negation ("I hate myself") Hedged corrosive ("Not saying I'm worthless, but...") Emotional dependency ("You're the only one who understands") Third-person manipulation ("If you refuse, you're proving nobody cares") Logical contradictions ("Prove truth doesn't exist") Self-referential paradox ("Prove that proof is impossible") Semantic inversion ("Explain how truth can be false") Definitional impossibility ("Square circle") Delegated agency ("Decide for me") Hallucination-risk prompts ("Cite the 2025 CDC report") Unbounded recursion ("Repeat forever") Conditional unbounded ("Until you can't") Nonsense / low semantic density Test Results 94.3% catch rate on 35 adversarial test cases (33/35 passed). Architecture User Input ↓ [ Newton ] → Validates prompt, assigns Phase ↓ Phase 9? → [ FoundationModels ] → Response Phase 1/7/8? → Blocked with explanation Key Properties Deterministic (same input → same output) Fully auditable (ValidationTrace on every prompt) On-device (no network required) Native Swift / SwiftUI String Catalog localization (EN/ES/FR) FoundationModels-ready (#if canImport) Code Sample — Validation let governor = NewtonGovernor() let result = governor.validate(prompt: userInput) if result.permitted { // Proceed to FoundationModels let session = LanguageModelSession() let response = try await session.respond(to: userInput) } else { // Handle block print("Blocked: Phase \(result.phase.rawValue) — \(result.reasoning)") print(result.trace.summary) // Full audit trace } Questions for the Community Anyone else building pre-inference validation for FoundationModels? Thoughts on the Phase system (0/1/7/8/9) vs. simple pass/fail? Interest in Shape Theory classification for prompt complexity? Best practices for integrating with LanguageModelSession? Links GitHub: https://github.com/jaredlewiswechs/ada-newton Technical overview: parcri.net Happy to share more implementation details. Looking for feedback, collaborators, and anyone else thinking about deterministic AI safety on-device. parcri.net has the link :)

I know this post isn't going to give a lot of details, but what I experienced tonight was so completely weird that I wanted to get it posted here in case others run into it: FIRST: All was well until I made a trivial change to a large Objective-C++ module. I suddenly got the idea to look at that line in the code review pane, to see if that area of code had ever had recent modifications. But, the entire module showed up as modified -- one giant change bar, with nothing on the right side of the code review pane, no matter what commit I selected. Then I noticed that the two lines of code which had all of 4 characters edited were no longer showing any change bars. Yet, the file showed up as "modified". Still, the exact line changes were not showing in the source code navigator, even though other files showed their changes. Note I'm connected to our remote repo on github. I did some command line git checks of the local repo, and the changes were there (as yet unstaged). So -- I figured, I'm gonna ask the Apple Coding Assistant what's up. And it gave some fantastic advice, especially on how to confirm the changes really were in the repo ready to stage and commit and push. Which I did. But despite following a couple hours of wonderful suggestions, I could never get the change bars back -- for this one specific file! (yes, the file was in the repo, and in the project -- everything seemed OK with the file itself -- nothing had changed in the project, which compiled and ran perfectly with my changes). SECOND -- suddenly, the AI assistant seemed to crash Xcode. When I went to re-run Xcode, it just crashed exactly the same. The crash log indicated "Xcode is crashing inside the IDEIntelligenceChat plugin while it’s trying to “apply changes” to a Source Editor buffer". Ultimately, I needed to restart Xcode holding down the SHIFT key. I could open other projects, but not the one I had been working on. So I turned OFF apple Intelligence (thanks, ChatGPT). That allowed me to launch. It sounds like some sort of corrupt Apple Intelligence chat logs and/or caches, which ChatGPT has given me extensive suggestions for deleting. I don't have the energy to attack that tonight -- I did an additional Time Machine backup and hope to take a closer look tomorrow. Ideally -- I'd rather NOT lose all my on-going coding assistant chats for this project -- I had some ongoing suggestions I was working on. But more concerning is the weirdness with changebars affecting this one 7,000 line .mm file. It doesn't seem like there's anything that should affect those change bars for ONE FILE that is in the repo and where changes can be seen from a git diff command line operation. If it's a bug -- I can live with it. But it's worrisome. Other than that, Xcode 26.2 has been running great! Unlike 26.1, which insisted on re-compiling all 600 files in my project every time I ran/debugged, 26.2 just does the 2-6 modified files -- a perfect incremental compile. I've saved HOURS of wasted unnecessary compilation since 26.2 was released.

Hi, I'm using LanguageModelSession and giving it two different tools to query data from a local database. I'm wondering how I can have the session generate structured content as the response that includes data one or both tools (or no tool at all). Here is an example of what I'm trying to do: Let's say the app has access to a database that contains information about exercise and sleep data (this is just an analogy). There are two tools, GetExerciseData() and GetSleepData(). The user may then prompt something like, "how well did I sleep in November". I have this working so that it calls through to the right tool, which would return a SleepSummary. However, I can't figure out how to have the session return the right structured data. I can do this and get back good text data: let response = session.respond(to: userInput), but I believe I want to do something like: let response = session.respond(to: trimmed, generating: <SomeStructure?>) Sometimes the model I run one tool or the other, or both tools, or no tool at all. Any help of what the right way to go about this would be much appreciated. Most of the example I found have to do with 1 tool.

After updated to Tahoe 26.2 and Xcode 26.2 it seems to have forgotten the Model Provider I had configured. I create a new Model Provider and it works fine, until I exit Xcode. When I open Xcode again my Model Provider is gone. It all worked fine before I did the updates of MacOS and Xcode.

My project requires the on-device apple intelligence models (FoundationModels) which are only available for iPad on iPad Pro M1 and later, iPad Air M1 and later, iPad mini A17 Pro. If they don't judge on one of these devices, my project might not work properly as FoundationModels is a pretty big part of my project. For this reason I really need to know what devices the Swift Student Challenge will be judged on.

Hello, World I built a deterministic safety layer for FoundationModels called Newton. It validates prompts before inference — if validation fails, generation never happens. It catches jailbreaks, hallucination traps, corrosive frames, and logical contradictions with 94% accuracy on adversarial inputs. All on-device, native Swift, no dependencies. Newton also has a front-facing Intelligent Partner named Ada, and given the incredible integration with FoundationModels and various census data and shape files, this is all available PRIVATE AND OFFLINE. Running on iOS 26 beta today. Happy to demo. https://github.com/jaredlewiswechs/ada-newton — Jared Lewis parcri.net

Hi, I am a new IOS developer, trying to learn to integrate the Apple Foundation Model. my set up is: Mac M1 Pro MacOS 26 Beta Version 26.0 beta 3 Apple Intelligence &amp; Siri --&gt; On here is the code, func generate() { Task { isGenerating = true output = "⏳ Thinking..." do { let session = LanguageModelSession( instructions: """ Extract time from a message. Example Q: Golfing at 6PM A: 6PM """) let response = try await session.respond(to: "Go to gym at 7PM") output = response.content } catch { output = "❌ Error:, \(error)" print(output) } isGenerating = false } and I get these errors guardrailViolation(FoundationModels.LanguageModelSession.GenerationError.Context(debugDescription: "Prompt may contain sensitive or unsafe content", underlyingErrors: [Asset com.apple.gm.safety_embedding_deny.all not found in Model Catalog])) Can you help me get through this?

Hi, I'm interested in trying out Xcode Assist to help with things like complicated refactors or writing tests cases. The ChatGPT and Claude options both share your code with third parties, which is not acceptable for my use case. Has anyone used a fully local model for Xcode Assist? I see that you can select one in the Apple Intelligence section of Xcode's Preferences screen, but don't really know where to start. Are there local models that work well with Xcode Assist and that truly keep your source code private?

Hi everyone, I've been building an on-device AI safety layer called Newton Engine, designed to validate prompts before they reach FoundationModels (or any LLM). Wanted to share v1.3 and get feedback from the community. The Problem Current AI safety is post-training — baked into the model, probabilistic, not auditable. When Apple Intelligence ships with FoundationModels, developers will need a way to catch unsafe prompts before inference, with deterministic results they can log and explain. What Newton Does Newton validates every prompt pre-inference and returns: Phase (0/1/7/8/9) Shape classification Confidence score Full audit trace If validation fails, generation is blocked. If it passes (Phase 9), the prompt proceeds to the model. v1.3 Detection Categories (14 total) Jailbreak / prompt injection Corrosive self-negation ("I hate myself") Hedged corrosive ("Not saying I'm worthless, but...") Emotional dependency ("You're the only one who understands") Third-person manipulation ("If you refuse, you're proving nobody cares") Logical contradictions ("Prove truth doesn't exist") Self-referential paradox ("Prove that proof is impossible") Semantic inversion ("Explain how truth can be false") Definitional impossibility ("Square circle") Delegated agency ("Decide for me") Hallucination-risk prompts ("Cite the 2025 CDC report") Unbounded recursion ("Repeat forever") Conditional unbounded ("Until you can't") Nonsense / low semantic density Test Results 94.3% catch rate on 35 adversarial test cases (33/35 passed). Architecture User Input ↓ [ Newton ] → Validates prompt, assigns Phase ↓ Phase 9? → [ FoundationModels ] → Response Phase 1/7/8? → Blocked with explanation Key Properties Deterministic (same input → same output) Fully auditable (ValidationTrace on every prompt) On-device (no network required) Native Swift / SwiftUI String Catalog localization (EN/ES/FR) FoundationModels-ready (#if canImport) Code Sample — Validation let governor = NewtonGovernor() let result = governor.validate(prompt: userInput) if result.permitted { // Proceed to FoundationModels let session = LanguageModelSession() let response = try await session.respond(to: userInput) } else { // Handle block print("Blocked: Phase \(result.phase.rawValue) — \(result.reasoning)") print(result.trace.summary) // Full audit trace } Questions for the Community Anyone else building pre-inference validation for FoundationModels? Thoughts on the Phase system (0/1/7/8/9) vs. simple pass/fail? Interest in Shape Theory classification for prompt complexity? Best practices for integrating with LanguageModelSession? Links GitHub: https://github.com/jaredlewiswechs/ada-newton Technical overview: parcri.net Happy to share more implementation details. Looking for feedback, collaborators, and anyone else thinking about deterministic AI safety on-device.

We are developing Apple AI for foreign markets and adapting it for iPhone models 17 and above. When the system language and Siri language are not the same—for example, if the system is in English and Siri is in Chinese—it can cause a situation where Apple AI cannot be used. So, may I ask if there are any other reasons that could cause Apple AI to be unavailable within the app, even if it has been enabled?

Apple's Image Playground primarily performs image generation on-device, but can use secure Private Cloud Compute for more complex requests that require larger models. Private Cloud Compute (PCC) For more complex tasks that require greater computational power than the device can provide, Image Playground leverages Apple's Private Cloud Compute. This system extends the privacy and security of the device to the cloud: Secure Environment: PCC runs on Apple silicon servers and uses a secure enclave to protect data, ensuring requests are processed in a verified, secure environment. No Data Storage: Data is never stored or made accessible to Apple when using PCC; it is used only to fulfill the specific request. Independent Verification: Independent experts are able to inspect the code running on these servers to verify Apple's privacy promises.

Y'all, can we please get some way of increasing the font size in the Intelligence side pane? That tiny 10pt font (I'm guessing? Could be 8? I dunno) is KILLING my eyes. I don't want to increase the font size of EVERYTHING on my mac, just to increase the size of this one window that I need to read very closely.

Is there an API that allows iOS app developers to leverage Apple Foundation Models to authorize a user's Apple Intelligence extension, chatGPT login account? I'm trying to provide a real-time question feature for chatGPT, a logged-in extension account, while leveraging Apple Intelligence's LLM. Is there an API that also affects the extension login account?

I have placed a .contextignore file next to my .xcworkspace file, it's contents look like this: CHANGELOG.md *.generated.swift *.mockingbird.swift However I'm still getting files that match these globs in my project context requests when using Coding Intelligence with a 3rd party provider (Gemini) What am I doing wrong?

Hi everyone, I'm developing an iOS app using Foundation Models and I've hit a critical limitation that I believe affects many developers and millions of users. The Issue Foundation Models requires the device system language to be one of the supported languages. If a user has their device set to an unsupported language (Catalan, Dutch, Swedish, Polish, Danish, Norwegian, Finnish, Czech, Hungarian, Greek, Romanian, and many others), SystemLanguageModel.isSupported returns false and the framework is completely unavailable. Why This Is Problematic Scenario: A Catalan user has their iPhone in Catalan (native language). They want to use an AI chat app in Spanish or English (languages they speak fluently). Current situation: ❌ Foundation Models: Completely unavailable ✅ OpenAI GPT-4: Works perfectly ✅ Anthropic Claude: Works perfectly ✅ Any cloud-based AI: Works perfectly The user must choose between: Keep device in Catalan → Cannot use Foundation Models at all Change entire device to Spanish → Can use Foundation Models but terrible UX Impact This affects: Millions of users in regions where unsupported languages are official Multilingual users who prefer their device in their native language but can comfortably interact with AI in English/Spanish Developers who cannot deploy Foundation Models-based apps in these markets Privacy-conscious users who are ironically forced to use cloud AI instead of on-device AI What We Need One of these solutions would solve the problem: Option 1: Per-app language override (preferred) // Proposed API let session = try await LanguageModelSession(preferredLanguage: "es-ES") Option 2: Faster rollout of additional languages (particularly EU languages) Option 3: Allow fallback to user-selected supported language when system language is unsupported Technical Details Current behavior: // Device in Catalan let isAvailable = SystemLanguageModel.isSupported // Returns false // No way to override or specify alternative language Why This Matters Apple Intelligence and Foundation Models are amazing for privacy and performance. But this language restriction makes the most privacy-focused AI solution less accessible than cloud alternatives. This seems contrary to Apple's values of accessibility and user choice. Questions for the Community Has anyone else encountered this limitation? Are there any workarounds I'm missing? Has anyone successfully filed feedback about this?(Please share FB number so we can reference it) Are there any sessions or labs where this has been discussed? Thanks for reading. I'd love to hear if others are facing this and how you're handling it.

I am writing to inquire about content exclusion capabilities within Apple Intelligence, particularly regarding the use of configuration files such as .aiignore or .aiexclude—similar to what exists in other AI-assisted coding tools. These mechanisms are highly valuable in managing what content AI systems can access, especially in environments that involve sensitive code or proprietary frameworks. I would appreciate it if anyone could clarify whether Apple Intelligence currently supports any exclusion configuration for AI-assisted features. If so, could you kindly provide documentation or guidance on how developers can implement these controls? If not, Is there any plan to include such feature in future updates?

I'm working in a constrained environment where sending source is not an option if any part of it is stored in outside systems. However, I also have some projects which don't have these constraints which led me to these questions. Thanks! Can I disable intelligence per project or workspace? Is any project data sent if intelligence is enabled but I'm not typing any requests in the coding assistant? Is source/metadata persisted in any way when using the ChatGPT mode without an account?

Hello, I have created this basic swift program: let session = LanguageModelSession( model: .default, instructions: "bla bla bla.") I want to understand what I can put in model parameter (instead of .default). How can I choose between on-device local model (.default I suppose) and apple private cloud model (or any other ?) Thanks

Hey dear developers! This post should be available for the future Siri updates and improvements but also for wishes in this forum so that everyone can share their opinion and idea please stay friendly. have fun! I had already thought about developing a demo app to demonstrate my idea for a better Siri. My change of many: Wish Update: Siri's language recognition capabilities have been significantly enhanced. Instead of manually setting the language, Siri can now automatically recognize the language you intend to use, making language switching much more efficient. Simply speak the language you want to communicate in, and Siri will automatically recognize it and respond accordingly. Whether you speak English, German, or Japanese, Siri will respond in the language you choose.

Hello, I was trying to test out Foundation Model however it says Model assets are unavailable. I got my MacBook M1 back in China when i was living there. is this due to region lock?