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[ARTICLE · art-29861] src=cloud.google.com ↗ pub= topic=generative-ai verified=true sentiment=↑ positive

How customer collaboration is shaping the future of GenAI security with Model Armor

Google Cloud enhanced its Model Armor service for generative AI security after a technical sprint with a major telecommunications customer, using direct developer feedback to overhaul documentation and address four critical friction points. The collaboration, which involved Google Cloud's Developer Advocacy team and the customer's developers using Agent Development Kit and Agent Platform, led to improvements in runtime security for GenAI workloads.

read1 min views1 publishedJun 16, 2026

At Google Cloud, we believe that the best products are built in partnership with our customers. Their feedback and real-world experiences are invaluable in helping refine our services and deliver solutions that truly meet our customers’ needs. In January 2026, our Google Cloud Developer Advocacy team participated in a high-velocity technical sprint with a major Google Cloud customer and a leader in the telecommunications industry.

This collaborative engagement provided us with deep insights, leading to significant enhancements in Model Armor information experience, our service for Runtime security for generative and agentic AI.

The objective of this engagement was to support the productionization of a next-generation GenAI customer support platform built using Google Cloud's Agent Development Kit (ADK) and Agent Platform. By sitting directly with the customer's developers and security specialists, we gained a unique opportunity to observe how developers interact with Gemini Enterprise Agent Platform in a live, complex environment.

This experience provided something traditional documentation cycles cannot replicate: radical empathy. By logging friction points, as developers worked, we translated functional blockers into technical insights in real-time, identifying exactly where developers were hindered by ambiguous configuration guidance or a lack of granular detail.

By observing the development workflow firsthand, we identified four critical friction points:

The insights gained from this partnership were immediately channeled into a comprehensive overhaul of Model Armor’s documentation and guidance:

roles/modelarmor.user

) to ensure smooth, error-free deployments.Getting "in the room" with our customers allowed us to bridge the gap between technical accuracy and operational utility. This journey of co-innovation ensures that Model Armor serves as a genuine catalyst for your success. We encourage you to explore the updated documentation and share your feedback as we continue to build the most secure platform for your GenAI workloads.

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