[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"cheat-sheet---en":3,"domain-info---en":3,"topic-info----en":3,"lesson-aws-certified-ai-practitioner-foundation-model-applications-fm-training-and-fine-tuning-how-foundation-models-are-trained-en":3,"prev-aws-certified-ai-practitioner-foundation-model-applications-fm-training-and-fine-tuning-how-foundation-models-are-trained-en":4,"next-aws-certified-ai-practitioner-foundation-model-applications-fm-training-and-fine-tuning-how-foundation-models-are-trained-en":3},null,{"locked":5,"reason":6,"meta":7,"item":3},true,"paywall",{"title":8,"description":9,"isFree":10,"estimatedMinutes":11,"difficulty":12,"learningObjectives":13},"Prompt Versioning and Management","Treating prompts like code: Amazon Bedrock Prompt Management, the difference between a mutable draft and an immutable version, and how versioning gives you safe rollout and rollback.",false,15,"intermediate",[14,15,16,17],"Explain what Amazon Bedrock Prompt Management does and why prompts need lifecycle tooling","Distinguish a mutable draft from an immutable prompt version","Describe how versioning enables safe rollout and rollback in production","Explain the role of variables in a managed, reusable prompt"]