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Gill Haus, CIO of Chase's consumer banking division, said the bank no longer hires engineers primarily to write code, since AI agents increasingly handle that task. Instead, he looks for engineers who understand what code should be written and how to evaluate and direct AI-generated output, while product leaders are also taking on coding responsibilities.
An AI safety expert cautioned that businesses are rapidly rolling out autonomous AI agents without adequate frameworks to manage the risks involved. The warning followed a day after an Anthropic researcher resigned, citing fears that fast-advancing AI systems could pose existential dangers to humanity.
Arm announced a wave of agentic AI-focused updates to its IP portfolio at its Arm Everywhere China event, spanning mobile devices, robotics, and cloud/enterprise infrastructure. Among the highlights is the Mali G2-Ultra NX GPU, which integrates neural accelerators capable of delivering AI graphics performance at under one watt of power for mobile devices.
Meta has introduced Muse, a new AI system that can carry out tasks like drafting emails or hunting for deals after users approve a plan of action. It runs in a private virtual machine and uses a separate 'Sentinel' agent to block unauthorized online actions, with rollout starting on iOS and Android in the US.
Meta rolled out Muse, a new autonomous AI agent that CEO Mark Zuckerberg says learns a user's habits and goals to handle everyday tasks like online shopping, drafting documents, filling out forms, and answering emails. Users must grant Muse permission to access their apps and data, and Meta says a separate 'Sentinel' system monitors its actions to prevent it from acting without oversight. The tool is now live in the US on iOS, Android, and via the muse.ai website.
Meta has moved its agentic AI assistant, Muse, into a limited closed testing phase, according to Testing Catalog, gating access through a waitlist and invite codes. An App Store listing reveals the app can connect to Gmail, Google Calendar, health apps, and even users' bank accounts and cards to track spending and suggest canceling unused subscriptions.
At IFA 2026, Nvidia introduced the Personal AI Router (PAIR), software that distributes sub-tasks from a local AI agent across idle GPUs on other PCs in the same home network. Instead of overloading one machine with multiple sub-agents competing for resources, PAIR spreads the workload and returns results to the main system, adapting in real time as household GPUs become busy or free again.
Zeke Hausfather, a climate scientist who relies on AI for research, spent eight weeks tracking 1,138 prompts he sent to Claude Code to estimate the electricity consumed at the data centers processing them. His findings suggest that AI agents, which perform multi-step autonomous tasks, draw significantly more power than the simple chatbot queries tech companies typically cite as low-energy examples.
An MIT Technology Review Insights webcast produced with NiCE examines how companies are moving AI agents from small pilots to enterprise-wide use. Chandra argues that agents need consistent access to data, context and back-end systems, and warns that scaling without integration can create new silos across teams.
Perplexity has extended its agentic AI feature, previously exclusive to Mac, to Windows 10 and 11 users on paid Pro, Max, or Enterprise plans. The tool can access local files, control native Windows applications, and connect to cloud services like OneDrive, Google Drive, Box, and Dropbox to complete multi-step tasks with minimal user input. A ZDNET reviewer tested it on five complex tasks to gauge its real-world usefulness.
Omdia analyst Theresa Lanowitz discussed with Dark Reading how organizations are increasing investment in offensive security practices like penetration testing and red teaming as AI-powered attacks become more common. She highlighted the emerging role of agentic AI tools in conducting these security tests, alongside the new risks such automation introduces.
Nutanix executive Oscar Wahlberg argues that securing autonomous AI agents requires a defense-in-depth approach spanning infrastructure, storage, compute, networking and a governing control plane, rather than relying on prompt-level guardrails alone. He explains that infrastructure security must first establish a verified identity and root of trust for any system granted execution privileges, since traditional application controls fail to stop an agent from misusing credentials or taking unintended destructive actions.