The IT Blog

Category: Blog

IT, Data, Work

  • Recommended Read: The Boring Internet

    The internet we know isn’t gone — it is being hidden under platform noise. And it seems like big platforms want to make us forget that this internet still exists. But while platforms rise and fall, the real internet is built on simple, open protocols like email, chat, and feeds — and they remain.

    Terry Godier’s essay “The Boring Internet” is a reminder: the web’s heart beats in the quiet, reliable tools. No algorithms, no ads, no need for growth, no monetization, no corporations, but freedom to create, explore and connect.

    Check out the Essay: “The Boring Internet“

    And follow him on Mastodon as well: @tg@indieweb.social

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  • It’s All About Adoption (Or: We Just Don’t Want to Change)

    One thing I’ve seen a lot is how we love to debate whether Tool A is better than Tool B — especially when we already have Tool B in place. Or we ask if Tool A, which might be 5% better, is worth the switch. Yet, the problem we often like to ignore? We forget the most important but inconvenient part: the users and whether they’ll actually use it.

    Even if a new tool is slightly better or cheaper, I always point to the adoption rate. Sure, replacing a tool with one that’s 5% better sounds great. But have you checked how many people are actually using the current tool? If only 10% of your team is on board, a 5% improvement for that 10% won’t improve your situation lot. On the other hand, increasing adoption from 10% to 50% means 5x the people are leveraging more efficiency — just by getting more people to use what’s already there.

    Of course, if you can improve the tool and the adoption rate, that’s ideal! But in reality, you usually have to choose — time and budget don’t stretch forever. And even if you switch tools, don’t expect miracles if you haven’t thought about adoption as well.

    But even if you do get users on board, there’s another problem we rarely talk about: the learning curve. Introducing a new tool —especially something like AI — comes with a cost.

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  • GPT-Live … And the Engineering Behind It

    Finally I took the time to read OpenAI’s post about their GPT-Live Realtime system.

    If you’re interested in how to build such low-latency systems, I definitely recommend to check it out. But what I also had in mind while reading the article was the “no one needs programmers anymore in the age of AI” … Oh really? Well I don’t know how many people were involved in the whole project – and I’m pretty sure they used AI in the coding parts. But the whole process to get there, knowing how / where to measure latencies, how to circumvent them, enhancing the WebRTC protocol and designing a new, faster standard, checking geo-location impact, shadow testing, etc … Oh boy, do I see people talking and engineering tasks there.

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  • My code vanishes from the web

    As a lot of people, I had most of my code published on GitHub. During my (reduce the amount of US services), I decided that I want to move my code somewhere else. Codeberg came totally handy and was recommended a lot.

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  • (why) I do not like Excel / Spreadsheets

    It seems like I’ve earned a reputation at work for hating Excel.

    We recently had a workshop with different stations and flipboards about how to improve some processes etc. And well – I added a lot of “less spreadsheets” sticky notes. After a while someone approached me and asked what my problem with Excel was – if I maybe just don’t know how to use it.

    But no, my reluctance to spreadsheets comes from the very bad experience together with automation. Let me explain: Very often, Excel (or any spreadsheet) is used as a not-very-well structured database in some process. And whenever you try to add more automation to this process or want to re-use the data, we come to one of two scenarios:

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  • Against Information Hoarding

    I am an information hoarder. I am somehow unhappy if I don’t get new information, new insights, new aspects. That’s not limited to technology but to literally everything.

    And since I do more and more self-hosting, I have two services on my candidates list: Readeck and Linkwarden. Then, with the rise of AI, the whole topic of AI managed second brain “LLM Wiki” came up, allowing to hoard even more information.

    And yet … I still do not use either of them.

    And even though it would be cool to play around with the technology, my main questions before setting up one ofthe tools are:

    • Did I ever miss something?
    • Does it solve an actual problem?

    And currently .. both are no for me.

    I just stumbled across Joan Westenberg’s article “5 Rules for a Second Brain You’ll Actually Use” with the more than accurate subtitle: “Tend a Garden, Don’t Fill a Warehouse”.

    And that just nails it so well for me: I do have my note taking (currently in Joplin) for all kinds of intersting stuff, plus the articles that I share here in the “Recommended Read” category. And .. I do not NEED more.

    I achieved to live a simple enough life so that I have no projects or so that are so complex that I need more organization than that. And I’m happy with it :-)

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  • Eight Myths on Software Engineering and GenAI – acm

    Actually, I just posted this on Mastodon, but I so agree to all those points that I want to reference them here on the blog as recommended reads as well.

    Generative AI is reshaping software engineering—but the narrative has gotten ahead of the evidence. Marketing claims, anecdotal wins, and misread studies have given rise to a set of persistent myths that are quietly driving poor decisions about AI adoption, tooling, and how to measure success.

    This article examines eight of the most common misconceptions.

    https://queue.acm.org/detail.cfm?id=3807963
    • Developers Spend Most of Their Time Writing Code
    • Writing Code Is the Bottleneck
    • Lines of Code Written by AI Is the Best Measure of Impact
    • AI Helps All Tasks and Engineers Equally
    • AI Will Turn Individual Developers into 10x Developers
    • It’s Up to Each Developer to Make AI Workgg
    • High-Performing AI Tools Will Be Adopted Automatically
    • With GenAI, Enterprises Can Innovate at Startup Speed

    See the full article here: https://queue.acm.org/detail.cfm?id=3807963

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  • Backup your Crontab …

    Yesterday evening I just quickly wanted to change something in my crontab .. I was tired, I was distracted, I just SSH’ed into my machine and typed crontab -r.

    Ahh typo! I obviously wanted to crontab -e which is just ONE key away from -r. But … no error, no “unknown option”? This left me in a “eh what is -r and why is crontab -l empty?” – and I sensed a little disaster …

    A quick check with man crontab confirmed my discovery:

           -r     Removes the current crontab.

    Oh man. I never thought about backing up my crontab! Until yesterday. Now I have a fresh crontab and new line in in it, too:

    crontab -l > crontab.bak && git commit -am "auto commit" && git push

    Luckily there wasn’t TOO much in my crontab, but still, this was an anoying experience. Maybe there are smarter ways to backup scripts in my home directory – but it’s okay for now.

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  • Debugging with Mistral: Learning, Not Just Fixing

    Depending on which social bubble one is into, people are drawn to letting LLMs do everything. Latest tools promise to fully configure or even manage entire server setups. While that sounds amazing (and I want to try it out some time) that approach has some downsides:

    1. Loss of control: I don’t really know what’s happening under the hood. If something breaks, I’m left in the dark.
    2. Loss of Learning: I want to know / learn how and why things (don’t) work.
    3. Digital Sovereignty: Relying on an external connection is creating a hard dependency that I want to avoid. And hosting my own LLM isn’t an option as my mini PC doesn’t have the RAM or power for that.

    So, while these tools are impressive, they’re not for me — at least not now or not in my private useacse of maintaining my main home-server.

    But, that’s no reason to not leverage it at all!

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  • Local Models for Coding

    Coding agents are becomming more and more popular (well – I guess). Yet the dependece to LLM providers is pretty obvious: Starting in June, GithubCopilot changed to usage-based billing. In April and June Anthropic’s Fable 5 and Mythos 5 being available, then not, then limited, … And since then I read more and more about locally hosting models.

    To be honest: I was quite sceptical and surprised at the same time.

    Sceptical because the larger models were always told to perform ways better and surprised to see those extremes: The outcry of Fable 5 (large frontier model) not being available – combined with “let’s self host models” (meaning a fall back to WAAYS smaller models – so why this outcry of Fable not being available …).

    But then also reading articles about “Best open-weight models for coding” (09 July, 2026) … So … do we really NEED the big models? Is it just hype? And how much (V)RAM and GPU do I need?

    Luckily, Birgitta Böckeler did a comparison in two articles where she’s testing different models:

    Overall though, the agentic coding capabilities are definitely very far away from what I’ve now become used to with bigger models.

    Check out her articles. I would say they are worth reading to get an impression of what you could expect.

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