Swapping large language models (LLMs) is supposed to be easy, isn’t it? After all, if they all speak “natural language,” switching from GPT-4o to Claude or Gemini should be as simple as changing an ...

Enterprise teams who treat model switching as a “plug-and-play” operation often grapple with unexpected regressions: broken outputs, ballooning token costs or shifts in reasoning quality.