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Lesson 01 of 05

Feedback to a better local model

Quality can rise from real use. The default path is signals, then synthetic rows, then a baked Core AI file. It is not a live cloud fine-tune.

Agent brief (llms.md)

Users show you where the feature fails. That signal can improve the next model you ship. It must not become a silent upload of their chat to a public trainer.

UseProduct signal
UseProduct signal
DataSynthetic rows
UseProduct signal
DataSynthetic rows
TrainLoRA on a Mac
UseProduct signal
DataSynthetic rows
TrainLoRA on a Mac
ShipCore AI .aimodel

Two Apple products sit in this story. Foundation Models is the system language-model API, including Dynamic Profiles and Evaluations. Core AI is how you ship a model file you trained or adapted. Core AI vs Core ML vs MLX keeps the names apart. You do not fine-tune Apple's system model in this course.

Core AI has no documented hot-swap LoRA. A better adapter is a new bake and a new app release, the same rule as LLM LoRA for your writing style.

Rule. Feedback improves the next baked file. It does not patch the live system model.

Next, collect signals that are safe by default.

Key concepts

  • Users show where the feature fails. That signal can improve the next shipped model.
  • The path is signal, synthetic data, LoRA, merge, coreai.llm.export, .aimodel.
  • There is no documented hot-swap LoRA on Core AI.
  • Feedback improves the next baked file, not the live system model.

Takeaways

  • Do not fine-tune Apple's system model in this course.
  • A better adapter is a new bake plus a new app release.
  • Keep Foundation Models and Core AI as separate products in your design.