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How Agentic AI Could Change Global Network Deployment

From the Alibaba Cloud Apsara Conference stage, here's a look at how Agentic AI, APIs, and NaaS could simplify network deployment and automate routing decisions. At this year’s Alibaba Cloud Apsara Conference in China, I was honored to represent Megaport on stage to present our live demo session “Alibaba Cloud × Megaport: Making Agentic Networks Simpler”.

The Next AI Breakthrough? Teaching AI to Shut Up and Decide

Jev is a new AI model from Type Safe built around a very different idea: instead of generating long answers, it makes fast, simple decisions. The team reportedly even demoed it playing Doom using nothing but split-second choices. After years of teaching AI models to talk, could the next breakthrough be teaching them to simply decide?

Watch an AI Agent Fix a Failed CI Build | Harness Worker Agents

What happens when an AI agent can do more than suggest a fix — and actually take action inside your CI pipeline? See Harness Worker Agents in action as an AI agent identifies a failed CI build, determines what went wrong, creates the fix, and gets the pipeline moving toward production again. Worker Agents bring AI-powered reasoning directly into your software delivery pipelines while maintaining the controls enterprises need, including sandboxed execution, scoped credentials, policies, and RBAC.

Get your agents off laptops and onto shared infrastructure

There's a specific, recognizable point where a team's use of AI agents changes shape. Not when they adopt agents; most teams already have. It's when agents stop running on someone's laptop and start running on infrastructure that the whole team can see. This is a real technical shift, not a policy change or a maturity score. Here's specifically what's different on each side of it.

9 Best AI Penetration Testing Companies for Enterprise Security Teams

Enterprise security teams know the value of penetration testing. The problem is the schedule. A large organization may run hundreds of web applications, thousands of API endpoints, mobile apps, AI features, and a sprawling external attack surface, and much of it changes every week. An annual or quarterly pentest examines a snapshot of that environment, produces a report weeks later, and leaves most of the year untested.

Stripe aims to power the next generation of AI-driven payments

Stripe has not only become a leader in modern online payment systems in just a few years, but has also set itself an even more ambitious goal: moving from e-commerce to AI commerce. Stripe wants to become the leading payment infrastructure for AI agents, and it has made that ambition clear with the acquisition of OpenRouter, a platform that routes requests from users and developers to more than 400 AI models from over 80 providers.

Steer, Block and Audit Agent Behavior from One Place | SAO Agent Control Demo Cisco Agent Control

Most teams keep an agent from regressing by hardcoding checks into its logic, an if-statement here, a regex there. Every new rule then becomes a code change, a review, and a deploy, and the person who spots the problem in production is rarely the person who can ship the fix. Agent Control moves those rules out of the code and into one hub. Steer, block, and validate agent behavior in real time, with rules any team member can update without touching the codebase.

Block AI Agent Regressions Before They Ship | SAO Pre-Push Eval Gate Demo

Every engineering team has unit tests. They tell you the code still works. They tell you nothing about what the model started saying. This demo wires a single eval gate script into a git pre-push hook, so Splunk Agent Observability scores every agent's output before the push is allowed through. Luna, an on-premise small language model, runs as a synchronous judge against fixed thresholds. Fail one, and the push is blocked.