I've been working with iOS 26 and Apple's new Foundation Models Framework. I realized every major LLM (GPT-4, Claude, Gemini) currently knows nothing about it—because training cutoffs predate its release.

So I created a structured training dataset specifically for LLM ingestion. It covers: - Core API usage (SystemLanguageModel, LanguageModelSession, Tool protocol) - Advanced implementation (@Generable/@Guide macros, constrained decoding, tool chaining) - Strategic features (adapter training, multi-step workflows, Apple’s AI vision)

All written in Markdown, with production-tested Swift code from actual iOS 26 beta usage. Tokenized structure, progressive complexity, no fluff—just what a model needs to learn this framework from scratch.

Details + preview here: https://rileyhealth.gumroad.com/l/bwoqe

Happy to answer questions or provide a sample if helpful.