The IT Blog

  • 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 ro play around with the technology, my main questions before setting up one ofthe tools are:

    • Did I ever miss something?
    • Does it solfe 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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  • How to fix: VLC long startup time

    Since a while I noticed that when I double clicked an MP4 file, VLC took really long (like several seconds) to open and show the file. Actually really annoingly long. But as I don’t watch a lot of movies, I never really bothered debugging it.

    BUT recently I came across on itsfoss.com and a tweet on X from VideoLan themselfes that explained the problem and solution:

    The Problem:

    This is because of a « bug » from Microsoft Defender in one update of Windows 11, who magically made VLC plugins cache quarantined by Windows.
    Reinstalling VLC or regeneration of the plugin cache will fix this.

    VLC Team on X

    The solution(s)

    Clearing the cache by one of the following steps:

    • Regenerate the plugin cache: launch with vlc.exe --reset-plugins-cache
    • Clear VLC’s cache under the user profile at %APPDATA%/VLC
    • Reinstall VLC from the official build (download here)

    But this won’t prevent Defender to possibly kick in again.

    Therefore, excluding vlc.exe (exclude the process, not just the file) in Microsoft Defender should be a sustainable solution!

    The exact clickpath might change. But it should be under (german):

    Einstellungen >
    Viren und Bedrohungsschutz >
    Einstellungen für Viren & Bedrohungsschutz - Einstellungen verwalten >
    (ganz unten) Ausschlüße hinzufügen oder entfernen

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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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  • Should IT Departments Embrace being Hosting Providers?

    Over the past few months, I’ve spoken to people across a variety of companies, and one thing has become quite obvious: with today’s tooling, employees are eager and able(!) to build their own applications. Whether it’s a small script to automate a tedious task or a full-fledged web application to solve a very specific problem, they’re motivated to create solutions – both in their personal time (and often even on their own personal expense) and, increasingly, in a business context.

    But there’s also a pattern that I recognized: There usually is no process and environment where people can simply deploy their applications in a business context. Those applications are built with great enthusiasm – an enthusiasm that you wouldn’t even create with cool company events – only to hit a wall when it comes to deployment. Employees either lack the infrastructure to run their applications, face weeks of approvals, or hit unexpected cost barriers – all of which kill innovation and drive shadow IT. The result? Wasted potential, security risks, and frustrated teams that could be building solutions for your business.

    What if they also take the role of a hosting provider

    This got me thinking: What if IT departments expanded their role? Instead of acting purely as a service provider for infrastructure and/or implementation, what if they also take the role of a hosting provider? What if they channeled this energy and provided a platform where employees could safely deploy their applications, turning shadow IT into visible, manageable, and secure IT?

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  • The Myth of the 2-Day Workweek: What History Tells us about AI and Labor

    I’ve heard this claim now really often: at conferences, in keynotes, even in casual conversations: “With AI, we’ll soon only need to work two or three days a week.” The narrative is seductive, I admit: technology will finally liberate us from the grind, freeing up time for creativity, family, leisure, hobbies – who would not want that? Who would not want to believe that? It sounds like StarTrek! Silicon Valley CEOs, futurists and tech optimists repeat this vision again and again, as if it were just a matter of time AI renders the 40-hour workweek obsolete.

    But at some point, I got suspicious. Not because I doubt the power of AI or so – it’s clearly heavily impacting industries. From manufacturing to customer service, IT itself, everything that has to do with digital imaging … GenAI is transforming several processes. — No, I got suspicios because I started to notice that every time someone made this claim, it was framed as a natural consequence of technological progress. As if history had a built-in mechanism to ensure that efficiency gains would automatically translate into more free time for workers. And that’s when I wondered:

    Why should a company just pay me the same amount even though I’m working significantly fewer hours? Did that ever happen before?

    Did the major technological revolutions – from the Industrial Revolution to the rise of computers (or the internet) – just simply lead to a work time reduction? I never heard or read about that. And in fact … usually productivity surged, but working conditions only improved when workers, unions, and governments forced the change to happen. Everything else would have been surprising! Businesses are profit-driven and not charitable organizations. Let’s look at historical examples to show how technological progress has not automatically reduced working hours.

    The Industrial Revolution

    The Industrial Revolution (late 18th to mid-19th century) introduced mechanized production, steam power, and factories. These innovations dramatically increased output, making goods cheaper and more abundant than ever before.

    Working Conditions

    Despite the productivity gains , working conditions weren’t so great (see for example Life in Great Britain during the Industrial Revolution). Working hours (12+ hours per day, often only with Sunday off) didn’t decrease and even child labor continued to exist.

    Working Hours Decrease

    The 8-hour workday didn’t emerge naturally from technological progress. It was mainly the result of decades of labor struggles, Unions, Strikes and Labor Movements, reformers and politicians (Eight-hour day movement). Fun Fact from the Wikipedia page:

    “A 12-hour day was reintroduced [in Germany] by a right-wing government during the occupation of the Ruhr and subsequent hyperinflation crisis in 1923″ (Link)

    The Computer Age

    The late 20th century brought the rise of computers, automation, and digital technology. The innovations transformed industries, from manufacturing to office work, making production faster and more efficient. – That sounds like GenAI-light, doesn’t it?

    But the whole efficiency gain did not materialize in a quick, massive drop in working time (Charts from ourworldindata.org). The increased productivity was great, no doupt! But the impact to working time, … Between 1970 and 2020, U.S. productivity rose quite a bit, but the average workweek barely changed, hovering around 40 hours (Our World in Data, OECD).

    Conclusion

    Working times HAVE reduced massively in the last 150 years (see here). There’s no doubt about that. But this was rarely down to the goodwill of the companies that have benefited from technological progress.

    This raises the question: Why is the narrative of the 2-3 day workweek still being promoted so repeatedly when it’s historically untenable? Is it naivety, tech optimism, or deliberate intent? Maybe all of them. – Undoubtedly, it fuels and legitimizes the agenda of the major tech companies (well, the investments have to pay off sooner or later!). And at the same time, it diminishes the discussion about government regulation of the impact of AI.

    The next time you hear someone claim that AI will soon reduce our workweeks to 2-3 days, ask yourself: Who benefits from this story? And more importantly: Who’s really fighting for our time?

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