Naive Prompt Optimization: Rethinking the Need for Complex Prompt Search
Challenges prevailing assumptions about prompt optimization complexity and offers more efficient approaches for AI researchers.
AI Summary
Researchers propose Naive Optimization, a lightweight method that achieves comparable performance to complex prompt optimizers using iterative revisions with teacher model feedback.
Excerpt
Efficiently improving autonomous agents across diverse tasks is central to accelerating recursive self-improvement (RSI) in agentic AI, with prompt optimization emerging as a promising approach capable of delivering performance gains comparable to those achieved by fine-tuning model weights, while reducing computational costs in both optimization and serving. However, recent developments increasingly favor unnecessarily complex prompt optimizers. We introduce Naive Prompt Optimization (NPO), a l