Securing the future of AI agents

Rohin Shah and Four Flynn lay out Google DeepMind's roadmap for securing their own internal systems against AI agents that are capable enough to be genuinely useful but not reliably aligned: access control, anomaly detection on agent trajectories, and human escalation for suspicious behavior, treated as security engineering problems rather than alignment philosophy. What struck me is that this isn't speculative; they describe an internal prototype already monitoring coding-agent trajectories in production. A useful, concrete counterpoint to AI safety discussions that stay abstract, this is what "securing an agent deployment" looks like as actual infrastructure.

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