The IT Blog

Category: Recommended Read

All kinds of posts mainly to Arctiles or other blog posts that I find worth reading

  • 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 :-)

    Fediverse Reactions

  • 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

    Fediverse Reactions

  • 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.

    Fediverse Reactions

  • BuzzFeed’s AI Gamble Backfired – The pivot to AI isn’t going so great

    I just came across the article BuzzKill – BuzzFeed Nearing Bankruptcy After Disastrous Turn Toward AI and thought it might be worth sharing. Not because of schadenfreude but as a reminder that going all-in on a technology that you haven’t fully mastered is a gamble that risks the company’s existence.

    The article starts with …

    In January 2023, BuzzFeed CEO Jonah Peretti announced in a memo to staff […] a hard pivot to AI […]. two months after OpenAI unveiled […] ChatGPT

    “What could possibly go wrong” is literally the only thing that comes to my mind.

    It’s so insane because they didn’t just bet on AI. They bet against their own strengths: human creativity, editorial judgment, and the hard-won trust of an audience.

    They had a Pulitzer-winning investigative unit (!) and content machine that understood what people wanted. The issue might have been that Facebook changed the rules and BuzzFeed’s response wasn’t adaptation — it was surrender. Instead of doubling down on what made them unique (award winning journalism), they doubled down on what made them cheap. A desparate race to the bottom that you simply can’t win against a behemoth like Facebook.

    BuzzFeed’s story isn’t about AI failure. To me, it’s a testament about

    • mistaking hype for strategy
    • automation for innovation, and
    • desperation for disruption.

    The next time someone declares a ‘hard pivot’ to the latest flavor-of-the-month tech (keep in mind WHEN this pivot was decided!), let’s remember BuzzKill: Are they innovating — or just paying Silicon Valley to automate themselves into obsolescence.

    Read the article on futurism.com: https://futurism.com/artificial-intelligence/buzzfeed-disastrous-earnings-ai

    Fediverse Reactions

  • Are we now coding / writing for other agents?

    I just wanted to tick off another article that I had marked for “read later”. In Claude Code is blowing me away, Nick Hodges writes about his surprise how well Claude Code wrote a website plus payment connection for him.

    The story itself is impressive, no doubt. But a key sentence (to me) comes later when he writes:

    The lesson here is that much of what we are doing now is not coding for humans—we are now coding for other agents.

    Nick Hodges

    … and, well, I pretty much agree. Whenever I see any LLM-chat sytem like perplexity or chatgpt in my access logs, I see what he means as well. And – I don’t complain about it. This might be confusing, but the fediverse changed my mind.

    Wait … the Fediverse?

    Yes, the Fediverse!

    I was (and am) happy and proud when people find their way to my website and — hopefully — find something that they find useful! And when i enabled the WordPress-fediverse plugin on my website, I was happy to open the content up to the fediverse.

    And when I don’t just publish a teaser, the whole post can be read completely in the respective fediverse client – well the same holds for RSS, but with the fediverse, it became really apparent to me. And in both scenarios (RSS or Fedi), I don’t get the reader via Browser to my website. They might just stay in their RSS reader or Fedi-client.

    And now? Agents come along as another “client”?

    Should I care? Well yes! Maybe I should keep in mind to make the website agent-friendly (just text only, no CSS, ….)? As long as my content generates value to a visitor, I might just feel fine. No mater which client is used.

    Of course, this attitude doesn’t hold for anyone who needs to make money from the website visit (like showing ads) or aims for a branding effect! But in my case … I could post my How-Tos also on StackOverflow and don’t get branding effects or credit for it …

    Maybe it’s naive. Maybe not. Maybe it’s just the future. I don’t know. But for this website, I don’t want to care too much.

  • One of the most potentially dangerous failure modes of LLM-based coding assistants …

    I really like having Jason Gorman’s blog posts in my RSS reader. Especially when he’s highlighting some critical issues with AI assisted coding.

    This paragraph for example really made me smile:

    For example, a common strategy they use when they’re not able to fix a problem they created is to delete failing tests, or remove testing from the build completely,

    What Makes AI Agents Particularly Dangerous Is “Silent Failure”

    I just had to smile because I probably would have been quite surprised to see that happening.

    But okay. It’s another thing I put onto my mental list to care about when doing AI assisted coding.

    Check out his post: https://codemanship.wordpress.com/2026/02/27/what-makes-ai-agents-particularly-dangerous-is-silent-failure/

    Fediverse Reactions

  • Agent finops

    The start of this article made me laugh:

    The first time my team shipped an agent into a real SaaS workflow, the product demo looked perfect. The production bill did not.

    FinOps for agents: Loop limits, tool-call caps and the new unit economics of agentic SaaS

    I wasn’t laughing out of malicious joy, but as it’s something that quite a lot of people don’t think about when they start AI / Agentic coding: Whenver you give the program flow the opportunity / ability to make queries on it’s own judgement, think about the case that the thing (I don’t want to call it AI) could run into an infinite loop. And every query to the LLM generates real costs.

    And with “costs” I don’t just mean “a busy CPU” like in traditional infinite loops. More like “costs” in terms of Lambda Horror Stories: Suddenly, every loop querying your LLM provider hit’s your budget.

    And that might get even more interesting in case of vibe coding, where such an infinte loop is burried in thousands of lines of auto-generated code. Oh we have interesting times ahead!

    Check out the article: https://www.infoworld.com/article/4138748/finops-for-agents-loop-limits-tool-call-caps-and-the-new-unit-economics-of-agentic-saas.html

  • AI amplifies DevOps

    DevOps is the backbone of modern software delivery. The latest insights from Developer Tech on Perforce’s AI-driven tools highlight why — again.

    70 percent of the organisations report their DevOps maturity materially affects their success with AI. Rather than replacing established delivery practices, proper foundational workflows serve as the prerequisite for scaling these capabilities.

    Perforce Software: How AI is amplifying DevOps | developer-tech.com

    What’s remarkable out isn’t just the AI integration. It’s how it amplifies DevOps’ core strengths: bridging team gaps, automating repetitive tasks, and ensuring reliability at scale.

    Collaboration, Speed, and Resilience

    DevOps thrives on collaboration, speed, and resilience. AI doesn’t replace these principles — it supercharges them. Perforce’s tools streamline code reviews, predict deployment risks, and optimize workflows. They’re not just upgrades. They’re force multipliers for teams drowning in complexity.

    It’s not an “either or”

    The article also points out that DevOps without AI risks obsolescence. Manual processes become bottlenecks – but AI-driven insights — whether in testing, monitoring, or incident response —turn the huge amount of data into actionable insights.

    That’s not hype. It’s a competitive edge. The future isn’t about choosing between DevOps and AI. It’s about how well you integrate them.

    Check out the article: https://www.developer-tech.com/news/perforce-software-how-ai-is-amplifying-devops/

    Fediverse Reactions

  • Rules don’t always work on AI agents

    A recent Mastodon post from @solomonneas highlights an annoying issue: an AI agent pushed to the main branch 12x, despite clear instructions not to.

    […] My agent pushed to main 12 times despite explicit instructions.

    Fix: git pre-push hooks on 39 repos. Agent can’t push code to main because git rejects it. No willpower needed. […]

    Mechanical enforcement > written instructions.

    @solomonneas@infosec.exchange

    The post really speaks for itself:

    • Agent rules are not 100% reliable
    • KISS: Keep it Simple, Stupid. Don’t make it more complex than necessary. (= don’t start fiddling around with additional AI)

  • How an Identy Check is distributing your Biometric Data

    I just came across “I Verified My LinkedIn Identity. Here’s What I Actually Handed Over.” and thought it might be worth sharing

    It’s a story of someone just wanting the “verified checkmark” on LinkedIn. Quite legit, right? Just that – afterwards – he started to check which companies his biometric data are now shared with.

    17 companies with Anthropic, OpenAI, and Groqcloud on the list. And just as I wanted to mention “Usually — as a company — you have enterprise contracts that the data must not be used for training purposes”, the next surprise comes up. Because by using the system you consent to exactly that – well okay, not consent but “Legitimate interest”.

    In the end I agree: the checkmark might not be worth the invest.

    Check out the article: https://thelocalstack.eu/posts/linkedin-identity-verification-privacy/

    Fediverse Reactions