Concept
Agents
The security bill is coming due for AI's agent era - Mitchell Bryson
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.
Topics: Agents
Entities: Agents
The Specification Gap: Why We Can't Tell AI Agents What We Actually Want - Mitchell Bryson
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.
Topics: Agents
Entities: Agents
The agent security reckoning nobody is ready for - Mitchell Bryson
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.
Topics: AgentsInfrastructure
Entities: AgentsInfrastructure
The Decay Paradox: Why AI Agents Get Worse as We Trust Them More - Mitchell Bryson
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.
Topics: Agents
Entities: Agents
OpenAI and Amazon announce strategic partnership
OpenAI and Amazon announce a strategic partnership bringing OpenAI’s Frontier platform to AWS, expanding AI infrastructure, custom models, and enterprise AI agents.
Topics: ModelsAgentsInfrastructure
Entities: OpenAIModelsAgentsInfrastructure
Pacific Northwest National Laboratory and OpenAI partner to accelerate federal permitting
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.
Topics: ModelsAgentsInfrastructure
Entities: OpenAIModelsAgentsInfrastructure
The Multi-Agent Paradox: Why More AI Agents Don't Mean Better Results - Mitchell Bryson
Google's latest research shows multi-agent coordination can actually reduce performance, challenging the industry's $52 billion bet on orchestrated AI systems and revealing why coordination complexity may be the wrong path forward.
Topics: Agents
IBM and UC Berkeley Diagnose Why Enterprise Agents Fail Using IT-Bench and MAST
A Blog post by IBM Research on Hugging Face
Topics: Agents
Entities: Agents
OpenEnv in Practice: Evaluating Tool-Using Agents in Real-World Environments
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
Topics: Agents
Entities: Agents