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Bitbucket Pipelines has always been an engine for automating more than just CI/CD, but today, Pipelines takes a first step towards a full agentic automation platform for all the manual, tedious, repetitive work that happens before and after code creation. You’ve probably seen the stat: Development teams spend 84% of their day doing things other than building features. A lot of this work is: This work matters, but it’s not very fun.

Stranded capacity might be costing you more than you realize. It’s time to explore what this means for your data center and how it impacts your bottom line.

This post by an engineer explains how his team uses the.claude folder in Claude Code. The folder is the hidden directory where you store context files, behavioral rules, and automated workflows so Claude understands how to operate in a specific project. He’d set up coding conventions, tool configs, CI integrations. Very engineering-brained. The tool is called Claude Code, so fair enough. I run a web and content team. We write blog posts, tutorials, and technical guides for a living.

Most engineering career advice treats the leadership track as a ladder where each step is a slightly bigger version of the one before it. That metaphor is the reason so many career transitions go sideways. IC, manager, director, and VP are four different jobs. Each has its own failure modes, its own definition of what counts as your work, and its own relationship to the code. The skills that earn a promotion to one level are rarely the skills that make someone effective at the next.

Last week, the cybersecurity industry received a signal it cannot afford to ignore. Anthropic announced Claude Mythos Preview: a general-purpose frontier AI model that, without any explicit training for the task, autonomously discovered and fully exploited zero-day vulnerabilities across every major operating system and web browser. Not theoretical capabilities.

Welcome to April’s Cloud Economics Pulse, CloudZero’s monthly look at cloud spend as AI moves from cost problem to strategic commitment. March’s Pulse called 4.01% a record. It lasted all of 31 days. Why? February’s billing data came in at 4.84% aggregate AI/ML share. That’s another high, another acceleration. You’ve heard it before and it’s getting a bit boring now, but the story isn’t in the numbers; it’s now in the behavior.