#fine-tuning

News · 2026-05-13

Fine-tuning is not dying. It is just no longer the default answer

Latent Space uses the pullback of part of OpenAI's fine-tuning API as a useful reality check: for most AI products today the first step is not tuning weights but better evaluation, context, retrieval, tool use and workflow. Fine-tuning remains a strong tool, just not a universal fix for a poorly designed system.

Library

Fine-tuning — a scalpel, not a universal hammer

Fine-tuning changes model weights. It is powerful when you have data, evals and a clear reason. It is an expensive mistake when it hides a bad prompt, missing RAG or an unclear process.