Commentary

When Kubernetes first came onto the scene, it was a major turning point, a revision of the infrastructure and operations space that transformed the way developers and ops personnel build, deploy, and maintain applications in the cloud. It has since become the clear standard for how modern applications are built and operated. As the CNCF […]

When Kubernetes first came onto the scene, it was a major turning point, a revision of the infrastructure and operations space that transformed the way developers and ops personnel build, deploy, and maintain applications in the cloud. It has since become the clear standard for how modern applications are built and operated. As the CNCF

You know the meeting. The board wants an AI agent strategy by end of quarter. Someone on the leadership team has read a McKinsey report. You’ve been voluntold to build the platform. The slide deck says “AI-native.” The acceptance criteria are vague. Somebody mentions LangGraph, and somebody else says, “We’ll just wrap it ourselves.” You

You know the meeting. The board wants an AI agent strategy by end of quarter. Someone on the leadership team has read a McKinsey report. You’ve been voluntold to build the platform. The slide deck says “AI-native.” The acceptance criteria are vague. Somebody mentions LangGraph, and somebody else says, “We’ll just wrap it ourselves.” You

Many AI agent systems become economically unsustainable long before they become technically impressive. Teams usually focus on model choice, prompt design, tool calling, and orchestration. Those things matter, but they are only part of the system setup. The deeper issue is that coding agents, such as Claude Code, Codex, and Jules, make agent workflows easier

The following article originally appeared on Sena Evren’s Legal Layer newsletter and is being reposted here with the author’s permission. TL; DRAgentic coding tools like Claude Code, Cursor, and Codex generate code that may be uncopyrightable, owned by your employer, or contaminated by open source licenses you cannot see. Some of this is settled law,

This week Miguel Fierro, a former Microsoft principal researcher who recently founded his own company, RecoMind, joined data and AI evangelist Christina Stathopoulos to talk about the state of recommendation systems. Christina also ran through the latest AI news she’s been watching, from Anthropic’s continued rise to responsible AI, announcements from Google’s I/O 2026 conference,

This is the eighth article in a series on agentic engineering and AI-driven development. Read part one here, part two here, part three here, part four here, part five here, part six here, and part seven here. “640K ought to be enough for anybody.”—Bill Gates (allegedly) If you’re building AI agents that do complex, multistep work, you’re going to run into context

The demo to Production Death Valley If you’ve worked on an AI feature, you know the feeling. You start building something that you are excited about, set launch timelines. The model spits out a perfect response, the prototype works magically, and everybody in the room is mentally calculating how big this product will be when

On June 1, GitHub Copilot’s usage-based billing became active for all Copilot plans, and developers reacted quickly and loudly. A Pro plan still costs $10, but it now comes with a monthly pool of AI credits. Those credits are priced at a penny each, and they’re consumed according to the model used and the tokens