Software development
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21 hours agoClaude Code Can Now Run Your Desktop - DevOps.com
Claude can now control your desktop, performing tasks while you are away, enhancing productivity through AI.
Every iOS app I've shipped over the last nine years started the same way: a Rails developer with a great web app, users who want it in the App Store, and weeks spent on Xcode, signing certificates, and Swift boilerplate that has nothing to do with the actual product.
In order to use agents or in order to use AI in IT operations, all of your systems need to be interconnected and what interconnects all of your systems is an automation platform. Interconnecting systems is only a piece of the puzzle though. There is also some well-founded concern about the autonomous AI systems we are moving towards. AI agents may make decisions and inferences, but enterprises remain hesitant to allow direct execution on production systems.
A few months ago, I decided to breathe new life into a 2019 Dell XPS 15 that had been collecting dust for a couple of years. Despite its (at the time) high-end Core i7 CPU and 32GB of RAM, Windows was frustratingly slow on it. The fan was constantly at full throttle even when the machine was idle, and it regularly failed to install updates.
Sudo, for those not familiar with Unix systems, is a command-line utility that allows authorized users to run specific commands as another user, typically the superuser, under tightly controlled policy rules. It is a foundational component of Unix and Linux systems: without tools like sudo, administrators would be forced to rely more heavily on direct root logins or broader privilege escalation mechanisms, increasing both operational risk and attack surface.
I've had several incarnations of the self-hosted home lab for decades. At one point, I had a small server farm of various machines that were either too old to serve as desktops or that people simply no longer wanted. I'd grab those machines, install Linux on them, and use them for various server purposes. Here are two questions you should ask yourself:
I recently wrote about my migration away from VirtualBox to KVM/Virt-Machine for my virtual machine needs. I've found those tools to be far superior (albeit with a bit more of a learning curve) than VirtualBox. Since then, however, I've found another method of working with KVM (the Linux kernel virtual machine technology), one that not only allows me to create and manage virtual machines on my local computer, but also from any machine on my LAN. That tool is Cockpit, which makes managing your Linux machines considerably easier.
The software industry is collectively hallucinating a familiar fantasy. We visited versions of it in the 2000s with offshoring and again in the 2010s with microservices. Each time, the dream was identical: a silver bullet for developer productivity, a lever managers can pull to make delivery faster, cheaper, and better. Today, that lever is generative AI, and the pitch is seductively simple: If shipping is bottlenecked by writing code, and large language models can write code instantly, then using an LLM means velocity should explode.
Dependabot sounded the alarm on a large scale. Thousands of repositories automatically received pull requests and warnings, including a high vulnerability score and signals about possible compatibility issues. According to Valsorda, this shows that the tool mainly checks whether a dependency is present, without analyzing whether the vulnerable code is actually accessible within a project.
Bash scripts are a great way to automate all sorts of repetitive tasks -- you can run backups, clear temporary files/logs, rename or batch-rename files, install or update software, and much more. Although writing such scripts isn't nearly as hard as you might think, it does take some time to learn the ins and outs of bash scripting. Also: 6 hidden Android features that are seriously useful (and how they made my life easier) Good news: If you have an Android device, you can enable the Linux terminal, which means you can create or practice your bash scripting on the go.
For the longest time, Linux was considered to be geared specifically for developers and computer scientists. Modern distributions are far more general purpose now -- but that doesn't mean there aren't certain distros that are also ideal platforms for developers. What makes a distribution right for developers? Although I consider app compatibility, stability, and flexibility to be essential attributes for most any Linux distribution, developers also need the right tools
But what happens when you need more granularity? How do you grant write access to a file to just one specific user who isn't the owner and isn't in the owning group? How do you allow two different groups read access, but only one of them write access? How do you ensure files created in a shared directory automatically get specific permissions for a certain team?
Ring the bells, sound the trumpet, the Linux 6.19 kernel has arrived. Linus Torvalds announced that "6.19 is out as expected -- just as the US prepares to come to a complete standstill later today, watching the latest batch of televised commercials." Because while the big news in Linux circles might be a new Linux release, Torvalds recognizes that for many people, the "big news [was] some random sporting event." American football, what can you do?
The reason for this is Snap - a Linux application packaging format - creates a local Trash folder for each VS Code version, one that's separate from the system-managed Trash, according to a VS Code bug report dating back to November 11, 2024. Not only that, but Snap keeps older versions of VS Code after updates, potentially multiplying the number of local Trash folders and the trashed-but-not-deleted files therein. Emptying the system Trash folder doesn't affect the local instances.
Industry professionals are realizing what's coming next, and it's well captured in a recent LinkedIn thread that says AI is moving on from being just a helper to a full-fledged co-developer - generating code, automating testing, managing whole workflows and even taking charge of every part of the CI/CD pipeline. Put simply, AI is transforming DevOps into a living ecosystem, one driven by close collaboration between human judgment and machine intelligence.