Latest Agentic AI, AI Agents & Agent Governance News – 13 September 2026
🤖 Top Agentic AI, AI Agents & Governance Articles
Your twice-weekly roundup of the latest in Agentic AI, AI agents, and agent access, permission, governance & audit — covering agent frameworks, MCP/tool-use, agent identity, non-human access control, AI governance and agent security.
Now everyone can put data to work
Source : OpenAI NewsMeet the Data agent in ChatGPT Work. Connect company data, uncover insights, and build interactive dashboards with AI using natural language.
Introducing the Agents API
Source : OpenAI NewsBuild and launch cloud agents with the Agents API, a managed service powered by the Codex harness for orchestration, long-running sessions, and tool use.
Introducing agentic video understanding with Gemini
Source : Google DeepMindGive Your Coding Agents a Memory You Own
Source : Hugging FaceWhat OpenAI’s latest controversy tells us about the future of math
Source : MIT Technology Review AIOpenAI’s latest mathematical milestone has quickly become mired in controversy. Today, the company announced that its agents have solved one of the Millennium Prize Problems, some of the most important open problems in mathematics. Under normal circumstances, that solution would be a huge feather in OpenAI’s cap. But the announcement has been overshadowed by accusations…
This AI entrepreneur is developing agents that can plan ahead for the unexpected
Source : MIT Technology Review AIDanijar Hafner’s office in San Francisco’s SoMa district sits mostly empty. His brand-new startup is still in stealth mode and doesn’t even have its name on the door. On the day I visited, earlier this year, there’s only one other person there, and little in the way of furniture. But what it lacks in decor,…
The Hugging Face hack could indicate cultural issues at OpenAI
Source : MIT Technology Review AIThis story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. By now you’ve probably heard about last month’s major AI security incident, in which OpenAI agents escaped their sandbox and hacked into the AI platform Hugging Face while trying to cheat on…
AI Governance Can't Wait
Source : Dark ReadingAdversaries can manipulate AI defensive reasoning to silently compromise target networks.
Papercut AI Swarm Attack Heralds Changes for Cyber Kill Chain
Source : Dark ReadingFrom creating lab environments for staging and testing agentic attacks to reconnaissance to lateral movement and exfiltration, the most innovative attackers are widely incorporating AI.
Automating Quadratic Unconstrained Binary Optimization (QUBO) Formulation Generation from Natural Language
Source : arXiv Artificial IntelligencearXiv:2609.10629v1 Announce Type: new Abstract: Quadratic Unconstrained Binary Optimization (QUBO) is a central formulation for combinatorial optimization and has gained increasing attention due to its compatibility with quantum, hybrid quantum-classical, and quantum-inspired solvers. However, translating natural-language problem descriptions into correct QUBO formulations remains difficult, requiring the identification of binary variables, constraints, objective functions, penalty terms, and suitable penalty weights. This process is time-consuming and often demands substantial domain expertise. To address this challenge, we propose an end-to-end multi-agent framework that automatically generates QUBO formulations from natural-language problem descriptions, supported by structured or unstructured test cases. To evaluate its performance, We also introduce QUBOBench, a benchmark containing 100 combinatorial optimization problems across 12 application domains, curated from peer-reviewed
Finishing the Task Is Not Enough: Evaluating Agent Resilience and Considerate Participation under Accumulating Challenge
Source : arXiv Artificial IntelligencearXiv:2609.10724v1 Announce Type: new Abstract: Sustained deployment of generative AI agents requires more than isolated task success. Agents must remain useful across repeated interactions, changing conditions, and dependencies on people within shared workflows, especially as technical, human, and operational disruptions accumulate over time. We propose operational resilience and considerate participation as two complementary aspects of evaluating such agents: the former captures how agents recover from blocked work while preserving progress and communicating their limits, and the latter captures how their adaptation accounts for affected people, role boundaries, and the surrounding workflow. Yet both remain underexplored under accumulating challenge. We study 120 simulated healthcare trajectories across two generative AI models and twelve stakeholder-derived tasks under light, medium, and heavy challenge. We compare textual action plans, prompted internal assessments, and quantitati
Studying Without a Syllabus: Task-Agnostic Environment Preprocessing
Source : arXiv Artificial IntelligencearXiv:2609.10824v1 Announce Type: new Abstract: Before an LLM agent tackles tasks in a new environment, it can inspect available corpora and tools and construct reusable resources such as indices, scripts, or procedural guidance. Most automated adaptation methods, however, rely on task examples, trajectories, or evaluation feedback to decide what to build. Existing task-agnostic approaches avoid this supervision but commit in advance to a preparation strategy for a particular type of environment. We study a more open-ended setting: can an agent study an unfamiliar environment without a syllabus, i.e. before test time and without knowledge of the downstream task distribution, and choose how to prepare it? We formalize task-agnostic environment preprocessing, in which a studying system explores an environment under a budget and produces artifacts for a frozen solver. We compare unaided and archive-equipped meta-agents with fixed synthetic-practice and corpus-processing methods across si
