Skip Fine-Tuning: Optimize Edge AI Through Prompt Coaching

Fine-tuning is often the assumed path to improving model performance, but this approach demonstrates that using a larger teacher model to optimize prompts and handle complex cases is more cost-effective. For edge AI deployments balancing latency and reliability, prompt coaching and escalation patterns eliminate expensive training while maintaining better real-world performance. This strategy is particularly valuable for vision tasks where small models tend toward unwarranted confidence.