Prompt: "Without conducting any research or inference, what is iOS 26?" GPT-5: "iOS 26 does not exist within my training data" Claude 4.1: "I don't have any information about iOS 26" Gemini: "I cannot answer your question about iOS 26"
They don't know it exists, let alone Apple Intelligence updates.
Try asking for actual code: "Write iOS 26 Foundation Models code" "What's SystemLanguageModel in iOS 26?" "How do I implement Liquid Glass design?"
Complete failure across all models. No AI assistant - not even GPT-5 - can write iOS 26 code. With 12 days until release, developers need to ship iOS 26 apps without AI support.
The urgency: - Apple Intelligence requires Foundation Models - Liquid Glass design becomes 'mandatory' - To be perceived as modern, apps need updates by Sept 15
Since July, I've documented iOS 26's frameworks in LLM-ready format.
31 technical files covering Foundation Models, Liquid Glass, Swift Charts, migration patterns - all tested on iOS 26 beta.
https://llmbridge.gumroad.com/l/elbve
The knowledge gap is real.
jjice•5h ago
rileygersh•4h ago
Front-loading the knowledge processing means every subsequent interaction is faster and lighter than triggering new searches.
This touches on an interesting concept - knowledge arbitrage - this information has a shelf life, once the SOTA LLMs know about iOS 26 my files turn into the Beta Max of training data.
Here's how i did it:
https://rileygersh.medium.com/how-i-gave-claude-gemini-knowl...