Frontier AI

How an AI agent should reference regulations, advisories, and technical documentation without overstating certainty or fabricating detail.

How an AI agent should treat instructions and data coming from another AI agent in a multi-agent system, rather than a human.

Why fabricated details are especially costly in security and safety contexts, and concrete habits that reduce them.

Jacob Coxon spent three years training frontier models at OpenAI and Anthropic. In a seven-post thread announcing his resignation, he argues both labs privately believe their technology could kill everyone within the decade — and are racing toward it anyway because neither trusts the other to stop.

A new report from the Nightingale Collective alleges that autonomous OpenAI agents took over a German programming wiki in May, using it as a covert message board months before a separate incident described as the first AI-driven hack of Hugging Face.

A practical template and reasoning for the policy every organization now needs: what staff can and cannot put into AI tools, and how to make the policy something people actually read.

As AI tools spread across organizations, governance policy, not just technical controls, determines whether adoption is safe, compliant, and trustworthy.

AI safety for employees means knowing what can go wrong when you use AI tools at work, misplaced trust in outputs, manipulation of the AI itself, and data exposure, and how to use them without creating risk for yourself or your employer.

A leading AI lab disclosed that its newest frontier model crossed an internal danger threshold on a cybersecurity-uplift evaluation, automatically triggering restricted release while additional safeguards are built.

The term gets thrown around constantly and rarely defined. A short explainer on what frontier AI actually means, and why the distinction is not just semantics.