In an Amazon News blog post, their HR leader describes using AI to write 100,000 lines of code — 25 years after she last coded. "Do you know how empowering it is to realize that after 25 years away from coding, you can actually build again?" First she built a calendar app for her family, but then used Amazon's AI-powered coding tool Kiro to write an app for Amazon's internal "Everyone Can Build" event. We opened the competition to every employee on our team, and within just a few weeks, more than 1,500 people were building. I couldn't believe what they built. One employee built an app that turned a nearly four-hour manual process into a one-second automated check, saving tens of thousands of hours annually. Another made a desktop pet named Momo that keeps your tasks, reminders, and shortcuts a click away. Since then, I've written over 100,000 lines of code with AI. What I've found is that the more you work with these tools, the more natural the process becomes, and the more you realize they're expanding what you're capable of, not replacing it. You don't need perfection to start. You just need to dive in. When I decided to build the submission app for our team competition, I didn't know how to begin, so I asked our internal AI workplace assistant, called Aza. It pointed me to the right tools and helped me take the first step. From there, I opened Kiro and started building. When you give employees the ability and tools to solve problems themselves, they will surprise you with what they create... At Amazon, every employee has access to AI tools. Whether someone needs a quick answer, wants to move faster in their day-to-day, or is ready to try building something new, the resources are there. The more people use these tools, the more capable they become with them, and that experience carries forward in their careers... We also want to make it easy for people to build credentials that are recognized across industries. That's why AI training is free for every Amazon employee. Amazon covers the full cost of one AWS AI certification exam per year, with options ranging from foundational AI concepts to professional-level generative AI. Employees can choose the path that fits where they are in their learning journey. Long-time Slashdot reader theodp notes that 7 months ago Galetti also took to Amazon News to announce the elimination of 16,000 corporate jobs, a move which CNBC noted coincided "with a push to invest heavily in artificial intelligence." The job reductions come just a few months after October's layoffs, when 14,000 employees were let go across Amazon's corporate workforce. At the time, the company indicated the cuts would continue in 2026 as it found "additional places we can remove layers."

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An anonymous reader shared this report from the blog It's FOSS: Canonical has committed funding to a three-year PhD project focused on building a system that can automatically translate large C codebases into Rust. And they are not alone; UK Research and Innovation is matching their funding for the project, which is set to run through the University of Bristol's Programming Languages Research Group. The PhD is aiming to build an all-encompassing platform that can take a C repository running into hundreds of thousands of lines and translate it into Rust that's "safe, behaviourally correct and maintainable Rust." The work will be carried out by a student, Alex Wood, who will be supported by Professor Meng Wang leading the work, with Dr. Cristina David and Canonical's Jon Seager serving as co-supervisors.

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Cursor has launched Origin, a GitHub-style code hosting platform built directly into its AI coding environment. The company is initially positioning Origin as a low-risk layer on top of GitHub, keeping GitHub as the "source of truth," but the launch landed just as a major GitHub outage highlighted growing concerns about reliability in the age of AI-generated code. VentureBeat reports: Cursor began rolling out Origin, its own code hosting platform, to paid users on Monday morning. Roughly three and a half hours later, GitHub's status page lit up with what became a six-hour-and-forty-two-minute global degradation -- error rates near 20% across pull requests, issues and the API, and near 50% on archive and raw file downloads, according to GitHub's incident log. Enterprise single sign-on went down with it: SAML, OIDC, SCIM provisioning and Team Sync all failed. So did Copilot. The developer internet did what the developer internet does. "You can now host your repos in Cursor Origin and deploy to Vercel via Cursor Origin which is itself hosted on Vercel," Vercel chief executive Guillermo Rauch posted on X. "And unlike GitHub, it's online [smile emoji]" Asked why he was smiling, Rauch replied: "trying to make light of the situation. We ourselves are stuck because of github rn!" Matt Palmer, who works at Cursor, quote-tweeted his own company's launch with the day's best line: "We were going to ship this earlier, but GitHub was down." A GitHub outage, in other words, delayed the launch of a GitHub competitor. Product launches get locked weeks in advance, and no evidence suggests Cursor timed this one. But the coincidence did the company an enormous favor, because it dramatized the argument Origin exists to make. For eighteen years, choosing where to host your team's source code has been the least interesting decision an engineering organization makes. Cursor is betting that AI agents have made it interesting again -- and for technical decision makers, that is the real news here. Not a new product, but a new procurement question with a governance problem attached.

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