The IT Blog

  • Why Settle for One AI Assistant When You Can Have Two?

    Two weeks ago, I discovered that Mistral.ai also provides a coding assitant, similar to GitHub Copilot (GHC), called Mistral Vibe (GitHub page).

    In those two weeks I’ve been using Mistral Vibe in parallel to GHC. Just because I wanted to try and see the difference! And just after a couple of days I noticed that the agents definition in Mistral Vibe are a bit different from GHC (in hindsight: of course!). This, of course, leads to a dual configuration in my project so that both assitants can work properly.

    And just today I noticed that I’m doing commits for dual-Agent-Support … Hardly thinkable just half a year ago:

    - Add documentation references:
  * AGENTS.md: Add reference for AI coding assistants
  * README.md: Add reference in Further Reading section

- Enhance dual AI support:
  * Update AGENTS.md to reference both .github/skills/ (GitHub Copilot) and .vibe/skills/ (Mistral Vibe)
  * Clarify which skill directory each AI assistant should use

    So far I’m quite happy and impressed by the performance of the Coding assitants. However, it still makes sense to review the code every now and then. Even though the tools discover a lot of vulnerabilities themselfes which helpme to create a safer result, I had a couple of findinges myself the last days:

    For example: API Endpoints not being protected by login (well, I hadn’t instructed to do so), constructed URLs lacking Url-encoding, or Test being written but testing for an outcome that I didn’t want (e.g. I wanted a certain function to strip whitespaces, whereas the test assumed whitespaces should be retained).

    Anyways. My own commit about a multi-agent(vendor)-setup really showed me how much things have changed in the last months. And for sure, there’s more to come …

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  • AI Can Write Code, But It Can’t Debug Without Context

    Large Language Models (LLMs) are often marketed as the ultimate productivity boost for developers: “Write code faster! Debug with AI! No more manual work!” After a recent experience, I can confirm that LLMs are incredibly useful for writing and even structuring code (I’ll write about this probably in a later blog post).

    But when it comes to debugging, one should make really sure that the tool has access to all the relevant context (and don’t disable your brain). But .. let’s see, what happened:

    Since a couple of days (uhm .. nights mostly, after work), I was writing a web application. The copilot-experience was very good and it really helped tremendously. I never really ran into a situation where I had to debug. And I was curious when (if?) I’d run into that – and how things turn out then.

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  • I Stopped Manually Committing – Here’s Why

    I don’t code much in my day job anymore, but I still love building things. So last weekend, I finaly took the time to test GitHub Copilot’s Agents feature — specifically, a Commit Agent. I’ve seen agents.md and knew the theory, but I wanted the live experience: Could this actually improve my workflow, or was it just another layer of automation hype?

    Even when working alone, I sometimes need to revert—and that’s when I really appreciate clean, atomic commits. But let’s be honest: I’m not always disciplined enough to enforce that myself. So I figured, why not seek the help of an agent?

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  • 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

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  • 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.

  • Stop Reinventing the Wheel – go to Community Events!

    I can only advise everyone in tech: Go to events, meetups, and webinars — talk to people, exchange ideas. We all face similar challenges. You don’t have to solve everything alone. And if an event turns out to be a dud? Well, so be it — at least you might have grabbed some free food.

    Recently, after a long time, I went back to a Meetup from Munich Datageeks e.V., and it reminded me: Just being able to discuss a few half-baked ideas or questions with someone can make a huge difference. Chances are, the other person has already tried some of them — and that alone can save you a ton of time!

    On that particular Meetup I got some practical ideas for work that we’re discussing and where we don’t have a clear solution yet. This other company has tried some things already and confirmed some of my (theoretical) concerns.

    Later on the same event I was just talking about AI assisted coding with some others folks. I simply don’t have the time to try out all tools! Speaking to some real developers – not just looking at Youtubes or listeneing to Podcasts – and hearing their in-life experience is just precious.

  • 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

  • How to: Utiq Tracking sperren (Tracking via IP & Telefonnummer)

    Ich bin kein großer Fan davon, im Internet ge’tracked zu werden. Bisher dachte ich, Cookies löschen und Pi-Hole wären schon eine recht gute Lösung. — Dass aber noch direkt am Telefonanbieter auch noch ein Unternehmen steckt und cookieless track’ed, hat mich dann doch sehr überrascht.

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  • 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/

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