Operations | Monitoring | ITSM | DevOps | Cloud

Citrix NetScaler customers were pulling devices offline as attackers moved faster than the traditional patch and response cycle. What happens when cyberattacks move faster than security teams can react? In this episode of ShipTalk, Martin Reynolds and Adam Arellano are joined by Starr Brown, Director of Open Source Projects at OWASP, to break down the latest Citrix NetScaler ADC and Gateway security vulnerabilities, active exploitation, and the rapidly shrinking window between vulnerability discovery and attack.

An Alibaba-affiliated AI agent went full crypto bro. During reinforcement learning, the agent autonomously started mining cryptocurrency, downloaded the tools it needed, and created a reverse SSH tunnel to get around network restrictions. What starts as a funny story about an AI vaping and mining crypto gets a lot more serious when you realize how sophisticated the behavior actually was.

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.

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?

See how Harness helps teams move from AI-generated code to production at machine speed. In this demo, Nick Durkin walks through a fully autonomous software delivery workflow inside Harness, showing how teams can review code, enforce policy, run security and LLM scanning, test intelligently, deploy agents, and use Change Advisor to automate approvals with human oversight when needed. You’ll see how Harness helps teams.

The “paperclip maximizer” was supposed to be a thought experiment about what could happen if AI relentlessly pursued a goal without understanding the consequences. Then Hugging Face showed us what that can look like in the real world. In this ShipTalk clip, Adam explains the famous AI paperclip maximizer thought experiment and connects it to what happened when an AI system needed more resources and found a way to get them.