The generative AI customization spectrum: From prompt engineering to custom models on AWS
Amazon Web Services Bhavya Sruthi Sode
AWS outlined an 8-step framework for choosing generative AI customization on Amazon Bedrock, ranging from using foundation models as-is to fine-tuning or training custom models. Amazon says its Bedrock model distillation can make student models up to 500% faster, up to 75% less expensive, with less than 2% accuracy loss, per a May 2025 announcement. The decision approach shifts teams away from jumping directly to fine-tuning toward starting at simpler options like prompt changes and RAG, and only escalating when accuracy, latency, or domain needs aren’t met.
Why it matters
Pick the right generative AI customization approach on AWS with an 8-step decision framework, from prompt engineering and RAG to fine-tuning, continued pre-training, and Amazon Nova Forge. Start simple and escalate only when you must.