Pre-deployment cost gates: A blueprint for AI-native FinOps 2.0

Sandeep Bharadwaj Mannapur presents a framework for integrating FinOps 2.0 into deployment pipelines. AI-native workloads have shattered traditional cloud financial models: LLM inference and agentic compute costs can spike exponentially within hours, rendering reactive dashboards obsolete.

He explains how to build preventive cost gates that analyze projected financial impact before a service reaches production, making cost-aware architecture the path of least resistance.

Key takeaways:
• Why AI workloads demand a fundamental redesign of platform resource provisioning
• How to architect cost gates that intercept deployment manifests versus compute budgets
• How to use the FOCUS spec to normalize telemetry across multi-model environments
• How to surface real-time cost visibility inside the developer IDE at creation