I’ve tried every online recommendation but nothing works, someone helps me out , my WiFi is pretty good, 100GB storage space and I have left the phone plugged in for 5 consecutive days

I'm experimenting with using the Foundation Models framework to do news summarization in an RSS app but I'm finding that a lot of articles are getting kicked back with a vague message about guardrails. This seems really common with political news but we're talking mainstream stuff, i.e. Politico, etc. If the models are this restrictive, this will be tough to use. Is this intended? FB17904424

Hi, testing latest tensorflow-metal plugin with tensorflow 2.20 doesn't work.. using python Python 3.12.11 (main, Jun 3 2025, 15:41:47) [Clang 17.0.0 (clang-1700.0.13.3)] on darwin simple testing shows error: import tensorflow as tf Traceback (most recent call last): File "", line 1, in File "/Users/obg/npu/venv-tf/lib/python3.12/site-packages/tensorflow/init.py", line 438, in _ll.load_library(_plugin_dir) File "/Users/obg/npu/venv-tf/lib/python3.12/site-packages/tensorflow/python/framework/load_library.py", line 151, in load_library py_tf.TF_LoadLibrary(lib) tensorflow.python.framework.errors_impl.NotFoundError: dlopen(/Users/obg/npu/venv-tf/lib/python3.12/site-packages/tensorflow-plugins/libmetal_plugin.dylib, 0x0006): Library not loaded: @rpath/_pywrap_tensorflow_internal.so Referenced from: <8B62586B-B082-3113-93AB-FD766A9960AE> /Users/obg/npu/venv-tf/lib/python3.12/site-packages/tensorflow-plugins/libmetal_plugin.dylib Reason: tried: '/Users/obg/npu/venv-tf/lib/python3.12/site-packages/tensorflow-plugins/../_solib_darwin_arm64/_U@local_Uconfig_Utf_S_S_C_Upywrap_Utensorflow_Uinternal___Uexternal_Slocal_Uconfig_Utf/_pywrap_tensorflow_internal.so' (no such file), '/Users/obg/npu/venv-tf/lib/python3.12/site-packages/tensorflow-plugins/../_solib_darwin_arm64/_U@local_Uconfig_Utf_S_S_C_Upywrap_Utensorflow_Uinternal___Uexternal_Slocal_Uconfig_Utf/_pywrap_tensorflow_internal.so' (no such file), '/opt/homebrew/lib/_pywrap_tensorflow_internal.so' (no such file), '/System/Volumes/Preboot/Cryptexes/OS/opt/homebrew/lib/_pywrap_tensorflow_internal.so' (no such file) tf.config.experimental.list_physical_devices('GPU') Traceback (most recent call last): File "", line 1, in NameError: name 'tf' is not defined I fixed this error by copying _pywrap_tensorflow_internal.so where it's searched.. 1)mkdir /Users/obg/npu/venv-tf/lib/python3.12/site-packages/tensorflow-plugins/../_solib_darwin_arm64 2)mkdir /Users/obg/npu/venv-tf/lib/python3.12/site-packages/tensorflow-plugins/../_solib_darwin_arm64/_U@local_Uconfig_Utf_S_S_C_Upywrap_Utensorflow_Uinternal___Uexternal_Slocal_Uconfig_Utf/ 3)cp /Users/obg/npu/venv-tf/lib/python3.12/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so /Users/obg/npu/venv-tf/lib/python3.12/site-packages/tensorflow-plugins/../_solib_darwin_arm64/_U@local_Uconfig_Utf_S_S_C_Upywrap_Utensorflow_Uinternal___Uexternal_Slocal_Uconfig_Utf/ then fails symbol not found: Symbol not found: __ZN10tensorflow28_AttrValue_default_instance_E in libmetal_plugin.dylib full log: with import tensorflow as tf Traceback (most recent call last): File "", line 1, in File "/Users/obg/npu/venv-tf/lib/python3.12/site-packages/tensorflow/init.py", line 438, in _ll.load_library(_plugin_dir) File "/Users/obg/npu/venv-tf/lib/python3.12/site-packages/tensorflow/python/framework/load_library.py", line 151, in load_library py_tf.TF_LoadLibrary(lib) tensorflow.python.framework.errors_impl.NotFoundError: dlopen(/Users/obg/npu/venv-tf/lib/python3.12/site-packages/tensorflow-plugins/libmetal_plugin.dylib, 0x0006): Symbol not found: __ZN10tensorflow28_AttrValue_default_instance_E Referenced from: <8B62586B-B082-3113-93AB-FD766A9960AE> /Users/obg/npu/venv-tf/lib/python3.12/site-packages/tensorflow-plugins/libmetal_plugin.dylib Expected in: <2FF91C8B-0CB6-3E66-96B7-092FDF36772E> /Users/obg/npu/venv-tf/lib/python3.12/site-packages/_solib_darwin_arm64/_U@local_Uconfig_Utf_S_S_C_Upywrap_Utensorflow_Uinternal___Uexternal_Slocal_Uconfig_Utf/_pywrap_tensorflow_internal.so

On iOS 27.0, PrivateCloudComputeLanguageModel refuses a large share of harmless requests, and the same requests often succeed when simply re-run. Our app writes a short, general-audience explanation of what a song is about. When the cloud model refuses, the on-device model with .permissiveContentTransformations answers the same prompt without trouble. PCC has no guardrail configuration, so there's nothing on our side to adjust. • Two refusals came within the first sentence of plainly benign text: "Tiny Dancer" (Elton John) at 167 characters, and "In the Ghetto" (Elvis Presley) at 169 characters, while describing snow on a Chicago morning. • Others include "Already Gone" (Eagles), "Do Ya" (ELO) and "We Didn't Start the Fire" (Billy Joel). • It's non-deterministic: "Question" (The Moody Blues) was refused, then succeeded 52 seconds later with an identical request. • Most failures are "Streamed response may contain sensitive or unsafe content", arriving mid-generation, so the rejection seems to target the model's own output rather than the input. • Rewording the instructions to steer the model toward mainstream, general-audience language didn't change the refusal rate. Filed as FB24938334 with 8 logFeedbackAttachment captures (.triggeredGuardrailUnexpectedly), each including the rolled-back rejected draft. Siri language English (US), iPhone 16 Pro. Is PCC's guardrail policy expected to be tuned for content-transformation tasks like this, or is there a recommended pattern for them?

I have successfully installed the macos 27 golden beta today 10 sep, 2026 on my macbook m4 air, activated siri beta. Have all my language and region and appstore in united states. Siri does set timer for 15 minutes for example but no other things that siri (with no ai) does normally. it sends me back sorry we have problem, we’ve had problems and all other kinds of error messages, writing tools unavailable( i also have checked the screen time section, no results) i am really having a difficult time to try this core and important feature. also tried with vpn on and off no difference!

I'm using the iOS 18+ RecognizedTextRequest, and with no change of code, iOS 27 gives poorer results: lines are dropped, all the text is not recognized it's not my code, because Live Text has the same issue and of course, back to 26 or 18 solves the issue What changed? Only interesting infos I could isolate: The simulator has not the issue Squashing the image horizontally (80% of its width for example) makes the detection significantly better

I am investigating an intermittent Siri AI failure on an eligible iPhone running iOS 27.2 beta (24B5089g). I captured three sysdiagnoses covering a previously blocked state, a working state, and the transition from working requests into a repeatable failure. I also exported the corresponding Apple Intelligence Report. The user-visible symptom is generic: Siri AI returns a variation of “Something’s gone wrong” for requests that require the agentic planner. Basic Siri functionality may remain available. The transition capture contains the following sequence. Identifiers, request content, account information, and retry dates have been removed: 16:48:55.069 privatecloudcomputed Ropes request finished successfully 16:49:08.770 privatecloudcomputed Ropes request finished successfully 16:49:13.742 privatecloudcomputed rate limit applied for rate with count=320, duration=86400.000000 16:49:13.790 privatecloudcomputed PrivateCloudComputeError Code=32073 16:49:13.837 privatecloudcomputed rate limit applied from cached denials 16:49:13.894 intelligenceflowd deniedDueToUserDeviceRateLimit 16:49:15.439 privatecloudcomputed Ropes request finished successfully The Apple Intelligence Report aligns the planner failure with 16:49:13 and identifies the execution environment as PrivateCloudCompute. Another PCC request completed at 16:49:15, after the planner denial. This is consistent with the restriction being scoped more narrowly than complete PCC unavailability, although the successful request’s metadata is redacted in the unified log. The log wording closely matches the rate limiter in Apple’s published PCC client source. In the 2026-05-15 source release, the client counts matching request records within a moving time window and denies a request when the count reaches a configured threshold. The same implementation stores cached denials and exposes an internal loggedCountSoFar field in TrustedCloudComputeRateLimit. Relevant source locations: RateLimiter.swift RequestLog.swift DeniedRequestLog.swift TrustedCloudComputeRateLimit.swift My current interpretation is limited to the following: 320 appears to be the configured maximum for a matching request class, rather than a reading of the current count. 86400 is consistent with a rolling 24-hour window. It does not necessarily mean that recovery occurs exactly 24 hours after the first visible denial. One Siri interaction cannot be assumed to equal one rate-limit record. The published implementation records a request when it may be sent to ROPES, before the final inference result is known. The evidence establishes rate limiting as the immediate cause of this planner failure. It does not establish how the rule is divided among device, iCloud account, feature identifier, workload type, or workload parameters. Because Apple’s public source predates this beta build and does not include error 32073, source-level behavior should not be assumed to match this build in every detail. I would appreciate clarification on these points: What is the intended scope of deniedDueToUserDeviceRateLimit in this Siri planner path: device, person/account, feature, workload, or a combination? Does count=320, duration=86400 describe a rolling window in current builds? Are attempts rejected from a cached denial excluded from the rolling request count? The published implementation appears to return the existing denial before the request-send accounting path, but I have not established that the current build behaves identically. Is there a supported diagnostic that reports the applicable rate-limit rule, loggedCountSoFar, and a non-redacted retry time to the device owner or through Feedback Assistant? Is it expected that another PCC workload can complete immediately after the Siri planner is denied? Should a user-visible generic Siri error distinguish this condition from network or service failures and offer a meaningful retry interval? For comparison, another developer has reported a cumulative PCC wall that surfaced as either rateLimited or quotaLimitReached while the public quota state remained healthy: Developer Forums thread 843046. My capture differs by providing the client rule parameters and a Siri-specific deniedDueToUserDeviceRateLimit result. I am retaining the original, unmodified sysdiagnoses and report export and can submit them through Feedback Assistant with precise timestamps. I am also running a low-frequency recovery observation and a same-account cross-device comparison. I will update this thread with recovery bounds and will correct the interpretation if later evidence does not support it.

Hello, My app fully relies on the new Foundation Models. Since Foundation Models require Apple Intelligence, I want to ensure that only devices capable of running Apple Intelligence can install my app. When checking the UIRequiredDeviceCapabilities property for a suitable value, I found that iphone-performance-gaming-tier seems the closest match. Based on my research: On iPhone, this effectively limits installation to iPhone 15 Pro or later. On iPad, it ensures M1 or newer devices. This exactly matches the hardware requirements for Apple Intelligence. However, after setting iphone-performance-gaming-tier, I noticed that on iPad, Game Mode (Game Overlay) is automatically activated, and my app is treated as a game. My questions are: Is there a more appropriate UIRequiredDeviceCapabilities value that would enforce the same Apple Intelligence hardware requirements without triggering Game Mode? If not, is there another way to restrict installation to devices meeting Apple Intelligence requirements? Is there a way to prevent Game Mode from appearing for my app while still using this capability restriction? Thanks in advance for your help.

My phone no longer shows the waitlist for Siri and has the option to "Try New Siri." I select it, continue, continue and the settings change to "Siri (Beta)" and the waitlist option is no longer there, but when using Siri it's the old pre-Apple Intelligence Siri that activates (little bubble at the bottom) and it does not work. Going to Safari and typing "Siri://" opens the New Siri App, but it says "Siri Update in Progress; Adding support for Siri hasn't completed. Open Settings to check the status." The app does not show up in Spotlight. My phone is done Indexing and all signs point to my phone being enrolled to use the New Siri, but it isn't working at all and still has not shown up. I've tried restarting a few times. Anyone experiencing this too?

I want to share a Siri / Apple Intelligence issue I have been troubleshooting since the iOS 27 beta cycle, together with the configuration that finally resolved it. The issue started during iOS 27 beta, continued across multiple beta builds, and was still present after I updated to the official iOS 27 release. Updating iOS alone never fixed it. The main problem was that Siri / Apple Intelligence repeatedly failed to complete activation. Settings would remain stuck on: “Adding support for Siri is in progress” The Siri app would sometimes show: “Siri is not available” Siri also frequently fell back to the older floating-sphere interface instead of using the newer glowing-edge interface. Sometimes the new Siri interface would suddenly appear and work normally, but later it would fall back again. The most repeatable symptom involved charging. When the iPhone was connected to power, Siri sometimes appeared to finish downloading and would temporarily work normally. After disconnecting the charger, Siri could become unavailable again or the system would behave as though Siri resources still needed to be downloaded. Connected to power → Siri sometimes worked normally Disconnected from power → Siri could return to downloading / unavailable There was also a difference between Wi-Fi and cellular data. On cellular data, iOS sometimes said Wi-Fi was required to continue downloading Siri resources. After connecting to Wi-Fi, it would return to “Adding support for Siri is in progress” and still fail to finish. Apple Intelligence storage also behaved abnormally. At one point, iPhone Storage showed approximately 7.37 GB in use. Later, the Apple Intelligence entry disappeared and storage usage decreased, then reappeared after changing language settings. Before finding the working configuration, I had already tried restarting, Reset All Settings, Recovery Mode update, multiple iOS 27 beta builds, the official iOS 27 release, different Wi-Fi networks, cellular data, disabling VPN/proxy, changing languages, removing additional languages, switching between old and new Siri, and leaving the phone on Wi-Fi and power for long periods. None provided a permanent fix. After repeated testing, the issue appeared to involve network transport, routing consistency, Siri language / voice configuration, Siri AI authorization, and local asset refresh. My final working setup was: System language: English (United States) Region: United States Siri language: English (United States) Siri voice: American Apple Intelligence enabled Proxy environment: Shadowrocket Proxy transport My proxy node uses an AnyTLS-based configuration. Previously, UDP traffic was enabled. During troubleshooting, some Apple / iCloud requests appeared unreliable when using UDP / QUIC through this node, with timeouts, resets, or repeated retries. I changed the node transport to TCP only while keeping TLS enabled: TCP + TLS After this change, Apple-related authentication and asset requests appeared much more stable. Routing rules This was one of the most important changes. I use split tunneling so that Chinese apps can remain DIRECT while selected traffic uses the proxy. However, some Apple traffic was being matched by broader fallback rules such as: apple.com,DIRECT GEOIP,CN,DIRECT This meant some Siri / iCloud / Apple Intelligence requests could use the proxy while related requests went directly through the local connection. I added these high-priority rules and moved them above broader Apple / DIRECT / GEOIP rules: DOMAIN-KEYWORD,gateway,PROXY DOMAIN-KEYWORD,probe,PROXY DOMAIN-KEYWORD,gdmf,PROXY DOMAIN-KEYWORD,guzzoni,PROXY DOMAIN-SUFFIX,iphone-ld.apple.com,PROXY Rule priority was important. If broader DIRECT rules were above these entries, the specific traffic could still bypass the proxy. After moving these rules to the top, the relevant Apple traffic consistently followed the same network path. Split tunneling still worked normally, and apps such as WeChat, Alipay, Meituan, and Xiaohongshu could remain DIRECT. Language and Siri configuration I standardized the Siri environment: System Language: English (United States) Region: United States Siri Language: English (United States) Siri Voice: American I selected an American Siri voice, such as Voice 4. After changing everything to the same English (US) environment, asset loading became more consistent. Enable Siri AI I manually selected: Try Siri AI (Beta) and completed the authorization process. I also temporarily disabled “Require Face ID” for the standalone Siri app while troubleshooting. I cannot confirm that this directly affected the download, but it removed an extra authentication layer while testing. Refresh local language assets I opened Apple’s built-in Translate app, deleted the downloaded English (US) language package, and downloaded it again. My goal was to refresh the local language / MobileAsset download state. I cannot confirm that Translate directly controls Siri’s generative models, but this appeared to help clear the remaining stuck asset state. Final installation step After making all of the above changes, I connected the iPhone to Wi-Fi and power, locked the screen, and left the device idle for approximately 10–15 minutes. After this, the Siri / Apple Intelligence state finally changed and remained stable. Current result: Siri consistently uses the full-screen glowing-edge interface Type to Siri works correctly Siri no longer falls back to the legacy floating-sphere interface “Siri is not available” no longer appears “Adding support for Siri is in progress” is no longer permanently stuck Apple Intelligence remains active Siri continues working after disconnecting the charger Split tunneling still works normally Most importantly, the previous charging-related behavior is gone. Before: Connected to power → Siri temporarily worked Disconnected from power → Siri failed again Now: Siri continues to work normally whether or not the device is connected to power. I am not claiming that Apple has officially documented every domain or internal process above as the root cause. These findings are based on repeated troubleshooting and network behavior observed on my own device. However, this issue persisted from the iOS 27 beta cycle through the official iOS 27 release, and standard system updates alone did not resolve it. In my case, the successful fix only came after correcting the combination of: TCP transport + consistent Apple routing + English (US) system / Siri configuration + Siri AI authorization + local asset refresh. If anyone else is experiencing “Adding support for Siri is in progress,” “Siri is not available,” repeated fallback to the legacy Siri UI, Apple Intelligence storage disappearing / reappearing, or Siri working while charging but failing after unplugging, I would be interested to know whether the same configuration also resolves the issue on other devices.

I am currently on Apple's Dev Beta V4 for iOS 27. The first version I installed was the Dev Beta V2, I am desperate to try out the new Siri AI Beta, but it's just not installing for me. I have the ability to "turn siri off" then "on again" and find I get the 2024 Apple Intelligence version fine. But if I choose to try out the new AI Beta, I'm left with "Adding support for Siri is in progress. Siri will be unavailable until the update is complete." It's been in that state for over 48 hours in Beta 4 and I'm left with the OLD OLD Siri globe from pre-Apple intelligence. Am I being too keen and just not leaving it long enough? Or is there a genuine issue at Apple's end, in regard to getting the new Siri to actually fully install?

(I don't follow the AI stuff here, so sorry if this is a stupid question. Or the wrong category.) There is a new fangled AI mode called JEV. Can the current Apple Intelligence libraries do something like it, or is this a WWDC27 thing?

Hello, We are seeing what appears to be a regression in the Core ML multifunction ML Program loading path on macOS 27.0. A compiled multifunction ML Program is correctly recognized by MLModelAsset and MLModelStructure, but loading either named function through MLModel fails with an error claiming that the model is not an ML Program. Environment macOS 27.0 Build: 26A428 Apple silicon Mac BABANE 1.0.4, build 16 Application built with the macOS 26.5 SDK Reproduces both inside and outside App Sandbox Approximately 98 GiB of disk space is available Public reproduction BABANE is available from the Mac App Store: BABANE on the App Store Apple engineers can reproduce the issue without receiving a separate model archive: Install BABANE from the App Store on macOS 27.0. Download either available translation model in the app. The model is delivered using Apple-Hosted Background Assets. Trigger model loading by starting a translation. Core ML fails while loading the first named function. The downloadable models are approximately 1.9 GB, so the App Store build is the most practical complete reproduction environment. Model structure The model is a specification-version-9 ML Program containing two functions: infer prefill Core ML correctly recognizes both functions: let asset = try MLModelAsset(url: compiledModelURL) let functionNames = try await asset.functionNames print(functionNames) Output: ["infer", "prefill"] MLModelStructure also returns a .program structure containing both functions. Loading code import CoreML func loadModel( at url: URL, functionName: String? ) throws -> MLModel { let configuration = MLModelConfiguration() configuration.computeUnits = .cpuAndNeuralEngine configuration.functionName = functionName return try MLModel( contentsOf: url, configuration: configuration ) } Loading either function: try loadModel(at: compiledModelURL, functionName: "infer") or: try loadModel(at: compiledModelURL, functionName: "prefill") fails with: `MLModelConfiguration`'s `.functionName` property must be `nil` unless the model type is ML Program. This contradicts the results returned by MLModelAsset and MLModelStructure. Setting functionName to nil is not a workaround. It fails with: This MLModel doesn't support the multi-function description syntax. Unified logging Immediately before the public Core ML error, unified logging reports: E5RT encountered an STL exception. E5RT: <private> (11) Core ML then returns the misleading functionName error. Tests performed We tested: functionName = "infer" functionName = "prefill" functionName = nil .cpuOnly .cpuAndGPU .cpuAndNeuralEngine .all App Sandbox application Non-sandboxed command-line executable Existing .mlmodelc A newly compiled .mlmodelc produced on macOS 27 All named-function combinations fail in the same way. The failure is independent of compute-unit selection and App Sandbox. The source package recompiles successfully on macOS 27, but the newly compiled model still fails to load. As an additional control: A system-provided multifunction ML Program exhibits the same loading failure on this installation. A single-function Core ML model loads successfully. This appears specific to the multifunction model loading path. Documentation The current Core ML documentation still describes MLModelAsset.functionNames as the way to discover functions and MLModelConfiguration.functionName as the way to select one: MLModelConfiguration.functionName MLModelAsset.functionNames We could not find any macOS 27 documentation or release-note entry stating that this behavior changed, that named functions now require a different loading API, or that a new entitlement is required. We found some potentially related reports: Core ML loading crash on macOS 27.0 build 26A428 Historical multifunction model loading crash Core ML/E5RT AOT loading regression with an Apple DTS response None of these reports documents the exact functionName failure described here. Expected behavior A model recognized as a multifunction ML Program should load when MLModelConfiguration.functionName is set to one of the names returned by MLModelAsset.functionNames. Actual behavior MLModel rejects the named function and incorrectly reports that the model is not an ML Program. Questions Is this a known macOS 27.0 regression in the Core ML multifunction loading path? Does MLModelConfiguration.functionName still accept names returned by MLModelAsset.functionNames on macOS 27? Is there a new required loading API, deployment target, SDK, entitlement, or model-packaging rule? Is there a supported workaround other than exporting each function as a separate model? Which diagnostics should we attach to a Feedback Assistant report besides the reproducer, unified logs, sysdiagnose, and exact OS/Xcode builds? Thank you.

Circling back on the LocalLM Lab arc. With v0.7, we've moved from prompt experimentation into real app development on Apple's Foundation Models local AI. The LocalLM Lab SDK lets you build that same on-device model and MCP client this thread has covered directly into your own app, with real tool and data access (Slack, Todoist, GitHub, Notion, Linear, plus Calendar, Reminders, Contacts and Location). And you can ship your app including through the Mac App Store. This is a big improvement over version 0.6, where the localai-cli toolkit needed LocalLM Lab installed and running. On the other hand, the SDK (LocalLMLabSDKCore) doesn't relay through anything; it links FoundationModels and a real MCP client directly into your own binary and is totally self-contained. The example included in the SDK, Plate Today, has actually been built into a sandboxed test app and verified working, with a signed path to a Mac App Store .pkg (Apple Distribution signing + provisioning profile pipeline). That's "verified signable and sandbox-compatible," to be precise. Entitlements (from personal experience: always a complicated topic): com.apple.security.app-sandbox + com.apple.security.network.client for the app itself, plus the standard personal-information entitlements per connector used (com.apple.security.personal-information.calendars, .addressbook, .location) and matching NS*UsageDescription strings in Info.plist. The one worth flagging specifically: the network entitlement is easy to miss and fails silently rather than throwing. Without it, MCP connections and Weather calls just hang with no error surfaced. OAuth handling requires the app delegate callback (application(_:open:)), not SwiftUI's .onOpenURL. Worth knowing before wiring it up if you're SwiftUI-only. Full entitlements list + SDK guide: https://github.com/ancientcomputing/locallm/blob/main/docs/sdk-guide.md Feature page: thisbrain.ai/locallm/sdk.html I hope the availability of the SDK (free, Apache 2.0 license) will give folks further incentive to explore local AI-enabled applications on the Mac. What else would you want to do that the SDK doesn't currently support? File picker? Calendar/Reminders/Contacts edits & writes?

Transcript.CustomSegment and the .custom case on Transcript.Segment were in the Xcode-beta 27 builds. WWDC26 session 339 covers them as the way a model package extends the protocol for new modalities and server side tool output. In the Xcode 27 GM they are gone along with the matching action on the executor generation channel. Is there any additional information as to what happened to custom segments, a replacement, etc? I don't see any mentions of this change in any release notes, though perhaps I'm looking in the wrong place.

Open Letter to Apple Leadership To: John Ternus, Chief Executive Officer Craig Federighi, Senior Vice President of Software Engineering Greg “Joz” Joswiak, Senior Vice President of Worldwide Marketing Apple Developer Relations & App Store Small Business Review Teams Subject: PCC & Developer Continuity: Implementing a Paid Tier for Private Cloud Compute (PCC) Dear John, Craig, Greg, and the Apple Developer Relations Team, I write to you as a new developer community member. While developing several Apple applications, I was glad to find deeply integrated applications through Apple Intelligence and the Private Cloud Compute (PCC) architecture that can be used to add features and capabilities to these applications. By eliminating early-stage cloud API friction, you gave indie developers the exact "on-ramp" needed to build incredible, localized AI tools. However, the current off-ramp mechanism built into the App Store Small Business Program enrollment is actively penalizing developer success. Your documentation outlines a rigid, unyielding pipeline for growing applications: "If any app subsequently exceeds the 2 million first-time downloads threshold, or the developer is no longer enrolled in the App Store Small Business Program, the developer will be notified and must migrate to an alternative solution within 6 months." While I know that it is highly unlikely that my downloads will exceed 2 million (shoot for the moon though, one never knows), since Apple does not distribute its frontier-tier server model weights, developers who reach this milestone will be forced to migrate their core features onto third-party infrastructure like AWS, OpenAI, or Microsoft Azure. This policy introduces a severe, counterproductive paradox into the Apple ecosystem: This will force successful devs to move to third party AI providers and away from Apple's tools. I am sure this is not a desired result at Apple. Or, it will have a chilling effect: developers will not use PCC if this a potential hurdle they might have to jump in the future. Why bother at all to begin with if this might be the end result. *Forced Migration Breaks Developer Continuity: Forcing growing apps off PCC means developers must completely swap out backend configurations. Instead of focusing on enhancing their apps for your new hardware, developers must waste critical engineering cycles rebuilding infrastructure on third-party clouds. Abandoning the Privacy Promise: Apple built its reputation on an uncompromising commitment to user privacy. PCC extends the secure enclave to the cloud. Forcing a developer to move their traffic to a third-party server means forcing users to trust external corporate entities with data that could have stayed inside Apple’s secure ecosystem. The "Success Tax": For mid-sized developers, the transition is a massive financial cliff. A commercial AWS instance capable of running an open-weight equivalent model introduces steep fixed baseline costs. My Proposal: A Predictable, Commercial Pay-As-You-Go PCC Tier after the limit, rather than an off-ramp to Apple's competitors: Instead of forcing growing developers onto AWS, Google Cloud, or OpenAI, Apple should allow developers to transition to a paid PCC commercial plan upon crossing the 2 million download or small business revenue thresholds. Whether structured as a metered developer API cost or an explicit tier integrated into Xcode and App Store Connect, developers want the option to pay Apple directly to stay on your hardware. This achieves your goal of preventing data centers from becoming a subsidized utility while ensuring our apps don't break when they go viral. Apple has always championed the idea that the best experiences happen when hardware, software, and services are vertically integrated. Forcing your most successful developers to sever that integration and hand their infrastructure over to external cloud providers at the exact moment they achieve scale undermines the ecosystem you’ve worked so hard to build. Please give us a path to grow with Apple, not away from it. Sincerely, The Apple Developer Community

Why don't CH/A devices have Apple Intelligence, and when will it arrive? It’s a major issue because the demographic that uses those devices—and the demographic capable of buying an iPhone—is massive, yet the lack of artificial intelligence is what prevents them from making the purchase.

I had a complete voice-only experience working with AppIntents and AppShortcuts on iOS 27.0 prior to enabling Siri AI. Once I enabled Siri AI, Siri refused to recognize any of the donated phrases in one particular AppShortcut. It still worked for several others. For the AppShortcut that no longer works, Siri responds to some of the phrases claiming the app doesn't support that action through Siri, and Siri responds to some of the phrases telling me I need to open the app to do that. FB24854409 includes a Sysdiagnose file. Note that I'm aware of App Schemas, but none apply well to my app.

I'm trying to add Private Cloud Compute support to a macOS app and can't get session.respond to succeed. Every call — even a trivial one-line prompt — hangs for one to several minutes ("Thinking" in my UI) and then fails. My setup: macOS 27.2 beta on an M2 MBP Xcode 27.2 The Private Cloud Compute capability is added in Signing & Capabilities, and com.apple.developer.private-cloud-compute is present in the built app's entitlements Removing the entitlement produces the expected error at construction ("Missing entitlement: com.appledeveloper.private-cloud-compute"), confirming it's genuinely being read PrivateCloudComputeLanguageModel().availability reports .available Apple Intelligence is enabled, I'm signed into iCloud with an eligible account/region, and system language is English The failure reproduces with zero tools registered on the session, and with a single isolated request. Relevant code: swift let model = PrivateCloudComputeLanguageModel() let session = LanguageModelSession(model: model, instructions: "You are a helpful assistant.") let result = try await session.respond(to: "What is 17+10?") The error, in full, after several minutes: Error Domain=FoundationModels.LanguageModelError Code=-1 "The operation couldn't be completed. (FoundationModels.LanguageModelError error -1.)" UserInfo={NSLocalizedDescription=The operation couldn't be completed. (FoundationModels.LanguageModelError error -1.), NSMultipleUnderlyingErrorsKey=( "Error Domain=FoundationModels.LanguageModelError Code=-1 "(null)" UserInfo={NSMultipleUnderlyingErrorsKey=(\n "Error Domain=com.apple.GenerativeFunctionsFoundation.GenerativeError Code=5040000 \"(null)\" UserInfo={NSMultipleUnderlyingErrorsKey=(\n)}"\n)}" )} Questions: Is this a known issue with Private Cloud Compute for macOS apps at this point in the beta? Does GenerativeFunctionsFoundation.GenerativeError code 5040000 mean anything specific — a connectivity failure, a capacity/availability issue, something else? Is there a way to get more diagnostic detail than this generic top-level error — a specific log subsystem to check in Console, for instance? Any guidance appreciated — happy to provide a full sysdiagnose or additional repro detail if useful.

I am exploring different approaches for integrating AI capabilities into modern iOS applications and would like to learn from developers who have built AI-powered experiences. Some areas I am interested in: Best architecture patterns for AI-powered iOS apps Handling API communication securely Managing latency and offline scenarios Protecting user data when working with AI services Designing a reliable user experience around AI-generated responses For developers who have implemented AI features in production apps: What frameworks, architectures, or patterns have worked well for you? Are there any common mistakes you would recommend avoiding when building AI-powered applications on Apple platforms?