This playbook guides AI cost control on AWS using FinOps principles, aligning spend with business goals, optimizing usage with tools like Spot Instances, Savings Plans, and cost allocation tags to ensure sustainable AI delivery.

Optimize GenAI costs on AWS startups by measuring spend with AWS tools, understanding unit economics, choosing efficient models, leveraging pricing options, enhancing GPU use, prompt engineering, and continuous cost monitoring.

This playbook guides startups on AWS to balance AI innovation with financial discipline, covering cost forecasting, controlled experimentation, build vs buy choices, LLM cost optimization, infrastructure selection, FinOps strategies, and a 90-day scaling plan.

Guide outlines practical strategies for controlling AWS AI workload costs: optimize GPU use, choose Trainium vs GPU wisely, manage vector DB/storage, apply FinOps tools, leverage SageMaker savings, and use Spot instances.