Agentic AI Will Scale Only When the Control Plane Scales First
Enterprise agent adoption is accelerating, but reliable value depends on identity, policy, observability, recovery, and workflow ownership outside the model.
Read analysisHands-on guides for agents, RAG, evals, LLMOps, inference, and production AI systems.
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A practical security architecture for AI agents with tools, files, credentials, memory, and network access, from trust boundaries to incident response.
Enterprise agent adoption is accelerating, but reliable value depends on identity, policy, observability, recovery, and workflow ownership outside the model.
Read analysis
Vint Cerf backs a DNS-based identity proposal for AI agents. Production trust still requires scoped permissions, logs, ownership, and a kill switch.

Google's Ironwood optimization work shows how sharding, fused kernels, and memory-aware serving can change the economics of a frontier-scale open-weight model.

PrismML compressed a 27B model to 3.9GB. Its strongest use may be a private assistant that keeps working when connectivity disappears.

Two new attack patterns show how malicious repositories can turn coding agents, approval dialogs, and automated security reviews against developers.