News and Tech Update

In today’s enterprise software delivery environment, AI has moved from a distant possibility to an active area of experimentation across the CI/CD pipeline. The conversation around AI in software delivery often runs ahead of the underlying reality, and most organizations are still working through what it takes to operationalize AI inside delivery architectures that were built long before AI was a practical consideration. Techstrong polled its community of DevOps, platform engineering and software delivery professionals to understand where AI adoption in CI/CD really stands, where it is being applied today, and what is standing in the way of broader operationalization. Our findings reveal that active interest is running ahead of operational readiness, with most organizations either experimenting in isolated areas or beginning to expand AI use in selected parts of the pipeline, while fragmented toolchains, governance concerns and integration complexity remain the primary barriers to sca...

The tech landscape constantly evolves, making it tempting to chase every new trend. Ironically, in today’s business world, the word “innovation” has become almost synonymous with technology adoption. Yet after years of leading digital transformations, I’ve learned that sustainable innovation isn’t about having the latest technology—it’s about solving business problems and delivering measurable impact. In 2025, the hype was “we’re building an AI strategy.” In 2026, it’s becoming clearer that many of those strategies were more aspirational than actionable—some even serving more as positioning than practical guidance. The latest wave of generative AI has carried a magic-wand promise: that simply generating outputs would unlock transformation overnight. But enterprises are quickly realizing that generating output was never the hard part. The real challenge—and the real differentiator—is governing it responsibly, securing it end-to-end, controlling its b...

DevOps.com is now providing a weekly DevOps jobs report through which opportunities for DevOps professionals will be highlighted as part of an effort to better serve our audience. Our goal in these challenging economic times is to make it just that much easier for DevOps professionals to advance their careers. Of course, the pool of available DevOps talent is still relatively constrained, so when one DevOps professional takes on a new role, it tends to create opportunities for others. The ten job postings shared this week are selected based on the company looking to hire, the vertical industry segment and naturally, the pay scale being offered. We’re also committed to providing additional insights into the state of the DevOps job market. In the meantime, for your consideration. Greenhouse Ripple Chicago, IL Site Reliability Engineer, Observability $160,000 to $200,000 EarnIn Mountain View, CA Staff Site Reliability Engineer $252,000 to $308,000 Ashby Element 84 Ale...

GitHub has moved Copilot cloud agent’s integration with Linear out of preview and into general availability, and the update brings more than a stability label. Along with GA status, GitHub added a set of controls that let teams shape exactly how the agent behaves on a per-issue or per-team basis, without leaving Linear. The core workflow stays the same as it was in preview: Assign a Linear issue to Copilot cloud agent, and it analyzes the issue contents, opens a draft pull request, and works independently inside its own ephemeral development environment powered by GitHub Actions. Progress streams back to the Linear activity timeline, and the agent requests a pull request review once the work is done. What’s new at GA is the control layer sitting on top of that workflow. Teams can now pick which model Copilot uses for a given task, point the agent at a custom agent defined in their repository so it follows team-specific conventions, and set the base and working branch to co...

GitHub and the Python Package Index (PyPI) just added a new layer of defense against supply chain attacks, and it doesn’t involve scanning code or blocking uploads outright. It involves waiting. GitHub’s Dependabot now applies a default three-day cooldown before opening a pull request for a routine version update. PyPI, meanwhile, will no longer accept new files uploaded to a release once it’s more than 14 days old. Neither change stops a bad actor from publishing malicious code in the first place. Both are designed to shrink the window during which that code can quietly work its way into production systems before anyone notices. The reasoning behind both moves is simple. A newly published package version often gets pulled into build pipelines within minutes of going live, well before a person or a scanner has had time to review it. Security tools are usually fast at flagging something suspicious. But flagging isn’t the same as fixing. A maintainer still has to...

CodePen has spent 14 years as the place where front-end developers show off CSS tricks and JavaScript experiments. That reputation is about to change. The company just shipped CodePen 2.0, a full rebuild that turns individual “Pens” into deployable, file-based, version-controlled projects. For a platform best known for demos, that’s a meaningful shift toward production use. One Editor to Replace Three Until now, CodePen ran three separate editors: the Classic Pen editor, a Projects editor, and a Vue-specific editor. CodePen 2.0 merges all three into a single tool, and co-founder Chris Coyier says it was built to do everything the old editors could do, plus a long list of new capabilities. The company also says it kept backward compatibility with existing Classic Pens as a priority during the rebuild. The most notable addition is one-click deployment. Every Pen built in 2.0 can now be pushed to a live *.codepen.app subdomain, updated on save, or pointed at a custom ...