Designing AI agents to resist prompt injection
How ChatGPT defends against prompt injection and social engineering by constraining risky actions and protecting sensitive data in agent workflows.
Concept
How ChatGPT defends against prompt injection and social engineering by constraining risky actions and protecting sensitive data in agent workflows.
In a single 48-hour window, Microsoft shipped Agent 365 (the 'control plane' at $15/user/month), NVIDIA announced NemoClaw (an open-source, hardware-agnostic agent orchestration platform), Meta acquired the social network where AI agents already talk to...
OpenAI shipping Codex Security, Anthropic's Claude finding 22 CVEs in Firefox in two weeks, and Microsoft treating AI agents as governed security principals all point to the same inflection: the industry is racing to close the security gap that AI coding...
OpenAI Models Agents Infrastructure Microsoft Anthropic Claude
AI agents are gaining deeper access to enterprise systems and developer environments faster than anyone is securing them. Three stories from a single news cycle show the attack surface widening in real time.
The hardest problem in agentic AI is not building capable agents — it is describing what we want them to do. Polanyi's Paradox, Goodhart's Law, and the limits of language converge to create a specification gap that no amount of engineering can close.
Three separate security disclosures this week exposed a pattern: we are deploying agentic AI infrastructure faster than we can secure it, from MCP servers to coding assistants.
Agentic AI systems degrade through context rot, compounding errors, and model drift — but human oversight erodes in lockstep. The widening gap between actual reliability and perceived reliability is the defining engineering challenge of autonomous systems.
OpenAI and Amazon announce a strategic partnership bringing OpenAI’s Frontier platform to AWS, expanding AI infrastructure, custom models, and enterprise AI agents.
OpenAI and Pacific Northwest National Laboratory introduce DraftNEPABench, a new benchmark evaluating how AI coding agents can accelerate federal permitting—showing potential to reduce NEPA drafting time by up to 15% and modernize infrastructure reviews.