KP Murphy-Sawhney

Google’s Agent Scaling Problem Is Quota, Observability, and Evaluation

KP Sawhney and Ian Ballantyne describe Google DeepMind’s agent work as an infrastructure problem rather than a single-agent breakthrough. Their account centers on the constraints that appear when thousands of heavy users and agent workflows run at once: quota management, scarce compute, traceability, skills governance, evaluation, and review. Sawhney argues the next step for Deep Research is to move away from passing giant context blobs through a pipeline toward shared workspaces where components can collaborate more like human researchers.