When I started the Fediverse integration of the blog, I just made a default handler for the full blog and called it @blog@www.locked.de. Yet, the more I use the blog for the fediverse, the less this made sense to me as it felt too impersonal.
While I could switch the setting to allow profiles for both, users and the blog itself — which would introduce a completely new user … I also could stop overthinking it.
Paste my profile into the search field of your favorite open social app or platform.
Your Profile
Or, if you know your own profile, we can start things that way! Why do I need to enter my profile?
This site is part of the ⁂ open social web, a network of interconnected social platforms (like Mastodon, Pixelfed, Friendica, and others). Unlike centralized social media, your account lives on a platform of your choice, and you can interact with people across different platforms.
By entering your profile, we can send you to your account where you can complete this action.
And if you are not yet on the Fediverse, I would recommend giving it a try. ;-)
GitHub’s new guide, How to write a great agents.md: Lessons from over 2,500 repositories, pulls lessons from over 2,500 repositories to show how to document AI agents effectively. It’s not just about clarity but also about making collaboration, reproducibility, and scalability possible.
The guide breaks down how to structure agents.md files for real-world utility. It highlights common mistakes and explains why solid documentation is the backbone of any successful AI project. Whether you’re a developer, DevOps engineer, or just curious about AI tooling, this is a practical roadmap.
Docker’s recent article “Do You Really Need Microservices?” delivers a good dose of pragmatism with regards to Microservices. The article doesn’t dismiss microservices outright— it acknowledges their value at massive scale — but it also hightlights an uncomfortable truth: most teams simply don’t operate at that scale.
What I particularly like are the warnings about hidden costs, the kind that reveal themselves after committing to the architecture and having to operati it over years and through a lot of releases. Operational overhead, debugging “fun” and the complexity of managing distributed systems aren’t just footnotes — they’re a true burden for teams without the resources to handle them properly.
Backups should be routine not only for folks in the IT. If you’re reading this you probably already have SOME backup process in place. Ideally automatically or with a scheduled reminder.
But doing backups regularly is just half the story …
Paris Buttfield-Addison, a developer and long-time Apple user, recently lost permanent access to his Apple ID. And he didn’t even do anything wrong. The result: 20 years of photos, messages and data? Gone. A true worst case scenario! But let’s have a look, should we learn something from that?
On Mastodon, I just came across “I Went All-In on AI. The MIT Study Is Right.” from Josh Anderson. He spent three months building a product using only AI-generated code. The result? A working product, but also a dangerous realization: He no longer fully understood his own creation. When a small change was needed, he hesitated.
t3n recently wrote that OpenAI’s GPT 5.1 update might come with a surprise to desktop users: previously reliable prompts no longer behave as expected. While this may be just a minor annoyance in day-to-day chat interactions, think about what that means in production environments.
Retrieval-Augmented Generation (RAG) is frequently marketed as a simple solution for grounding AI responses in real-world data. It sounds straightforward & easy: connect a vector database to a language model, pipe in your data, DONE! But maybe it might be just a little harder than that …
Mistral AI has published Mistral 3, the latest version of their open-weight language model. The models are available under the Apache 2.0 license and, according to their benchmarks, outperform DeepSeek’s recent models in several key areas … well, let’s see.