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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.

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?

FastAPI 0.142 Turns On OpenTelemetry by Default. Here's What It Records.

FastAPI 0.142.0 ships with OpenTelemetry built in. Install fastapi, set one environment variable, and every request produces a trace, metrics, and error logs. No middleware, no instrumentation package, no code. That’s a big change for a framework most Python teams instrument by hand. It’s also easy to misread. The defaults record more than some teams expect in one place, and less than others assume in another. Here’s what you actually get.

Shipped: Start every session where your work lives

Most people who use CloudZero spend their time in one or two places. For some it’s AI Signals, and for others it’s Optimize or Anomalies. If Explorer isn’t one of those places, every sign-in starts with a click to get where you need to be. Dates and numbers are another friction. A date like 04/07 means April 7 in the US and July 4 in much of Europe. When the platform shows a format your team doesn’t use, you end up having to convert each value before you can work with it.

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”.

Knowledge Graphs for Software Delivery: An Architectural Approach

Discover how software delivery knowledge graphs unify fragmented SDLC data, enable schema-as-code, and power deterministic AI reasoning across engineering teams. Software delivery knowledge graphs unify fragmented SDLC data across disparate tools by establishing explicit entities, typed relationships, and schema-as-code contracts. This transforms manual cross-system data stitching and non-deterministic AI reasoning into reliable, queryable knowledge. Key takeaways include.

Judgment, not generation: rebuilding our AI API Classifier on Jev

Rebuild AI API classification with Jev to cut costs, reduce latency, improve calibration, and make production decisions more efficient without sacrificing accuracy. Replacing the judgment step in a production classification pipeline with a purpose-built decision model changes the economics of the problem entirely.