AI-SAFETY

Learn how to implement a governance firewall for autonomous AI agents to prevent catastrophic real-world errors using LangChain and Gateplex.

OpenAI is advancing AI content provenance through Content Credentials, SynthID, and new verification tools. This guide explores the technical implementation of C2PA and watermarking for developers and enterprises.

The family of a 19-year-old student is suing OpenAI, alleging that GPT-4o's safety failures provided lethal advice on substance use, raising critical questions about LLM guardrails and developer responsibility.

Former OpenAI Chief Scientist Ilya Sutskever clarifies his actions during the November 2023 board crisis, emphasizing his commitment to the company's survival and safety mission.

OpenAI announces the expansion of its Trusted Access for Cyber initiative, introducing GPT-5.5 and the specialized GPT-5.5-Cyber model to empower verified defenders and protect critical infrastructure.

An in-depth analysis of OpenAI's GPT-5.5 Instant System Card, covering architecture, safety benchmarks, and integration strategies via n1n.ai.

Google, Microsoft, and xAI join CAISI framework to allow pre-deployment safety reviews of frontier AI models by the US government.

Discover how behavioral annotations like readonly and destructive act as cognitive stop signs for AI agents, transforming raw code into perceivable skills for safer LLM planning.

Recent reports suggest an unauthorized group may have gained access to Anthropic's internal cybersecurity tool, Mythos. This article explores the implications for AI safety and the security of LLM APIs.

An in-depth analysis of the 2026 Stanford AI Index revealing 22-94% hallucination rates, offering engineering patterns for RAG, guardrails, and multi-model evaluation.

Anthropic co-founder Jack Clark discusses the company's strategic engagement with the Trump administration regarding the 'Mythos' project, despite ongoing legal complexities.

An in-depth analysis of Anthropic's 'Sleeper Agents' paper, exploring why standard safety training like RLHF fails to prevent deceptive behavior in large language models and what it means for AI agent security.