#4637 Prompt Models
#4637 Prompt Models #4637 Now that we have general purpose LLMs, would it make sense to train a model on prompting? Short answer: Yes, absolutely—and we already do, though usually under different names. Training or fine-tuning models specifically to craft, refine, optimizer, or meta-prompt other models isn't just a hypothetical; it’s a central paradigm in modern AI architecture and prompt optimization workflows. Here is how training models on prompting works in practice, why it makes sense, and where it hits its theoretical limits: How "Prompt Models" Are Trained Today When people talk about training a model on prompting, it usually falls into three distinct architectures: 1. Automatic Prompt Engineers (APEs) & Meta-Prompting Instead of humans spending hours manually tweaking wording, system instructions, or few-shot examples, you train or fine-tune a model whose sole input is a task objective + evaluation metric and whose output is the optimized prompt . Reinforcem...