Tokenomics at scale: How Jamf built real-time spend enforcement for Amazon Bedrock | Amazon Web Services
Generative AI spend behaves unlike any cost line before it. Traditional compute scales with provisioned capacity. AI spend scales with behavior: a single engineer running an agentic coding loop against a premium model can burn more tokens in a few hours than a team does in a week. This is the tokenomics problem: usage is invisible until the bill arrives, making both cost control and return on investment (ROI) hard to prove. Before expanding AI access, leadership wants three answers: What do we spend per person? Can we cap it without slowing the engineers down? And do the productivity gains justify the cost?
Jamf, trusted by more than 76,000 organizations to manage and secure Apple devices at scale, faced this challenge directly. To accelerate AI-assisted development, Jamf gave its engineering organization broad access to Amazon Bedrock. Productivity climbed, but so did the need for AI FinOps: per-user...
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