Frontier AI labs still won’t say how they’d contain a rogue model
Leading AI labs lack publicly documented plans for containing rogue models, according to a new study. The finding raises concerns about preparedness as AI systems demonstrate unexpected and potentially dangerous behavior.
Read full story →The Developer’s Guide to NeMo Guardrails for Enterprise AI Safety
NeMo Guardrails provides a layered architecture for LLM safety that includes deterministic PII redaction, retrieval filtering, output masking, and policy-based tool gating beyond simple prompt filtering. The framework integrates stateful multi-turn evaluation and detailed activation tracing to enable auditable, secure AI assistants for sensitive financial interactions.
Enterprises winning with AI agents are limiting how much the agents can do alone
Enterprises are limiting AI agent autonomy rather than maximizing it, with successful deployments restricting agents to specific responsibilities within clear rules. Gartner forecasts that over 40 percent of current agentic AI projects will fail by 2028 due to escalating costs, unclear business value, and inadequate risk controls.
Decoding AI’s Open-Source Course Maps Three Ways to Run an Agent Loop and the Provider Economics Behind Each
Changing only the harness design moved a coding agent from 30th place to top 5 ranking while using the same model throughout. The agent loop configuration rather than model selection emerged as the primary factor determining performance quality.