Browse past weeks of engineering reads.
Deploying and managing AI agents at scale in production requires infrastructure for state management, security governance, and complex workflow orchestration that goes beyond demo implementations.
Google Cloud needed to bridge the gap between high-level keynote announcements and practical implementation details that developers could immediately apply.
BASF needed to manage and optimize thousands of interdependent supply chain decisions across 180 global production sites where weather and regulatory changes can cause cascading disruptions in a two-year production pipeline.
Building safe, reliable, and autonomous agents that can act independently across multiple enterprise systems while maintaining security, governance, and reliability guardrails.
How to help developers transition from understanding AI concepts to building and maintaining production agentic systems in cloud environments.
Organizations need to secure their AI systems and infrastructure against emerging AI-era threats while maintaining the ability to leverage AI's potential at scale.
Development teams struggle to safely deploy code to production while managing the risk of releasing features to all users simultaneously, especially as AI accelerates code generation faster than safe deployment practices can keep up.
Enabling seamless connectivity, governance, and security across multi-agent AI systems and core applications distributed globally at planet scale.