The IT Blog

Tag: GenerativeAI

  • Reproducible Vibe Coding | It’s all About Context

    Actually I wanted to try a bit GithubCopilot with Agents.md. Yet .. I think during the project I totally forgot to test the influence of the Agents file but tried “vibeCoding” in a reproducible way.

    I had a very little project in mind that authenticates to Mastodon, fetches some data, saves into a database and displays some metrics on a web page in basic charts. Nothing overly fancy, but also some stuff that would simply take some time when coding “alone”. Like proper OAUTH flow, paging through mastodon apis, rate limiting, database writing, database setup script and cleanup. Some Javascript for the chart, etc.

    But I thought it might be nice to try with GithubCopilot (GHC). But I’m also a big fan of reproducible results. So … step by step, what did I do.

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  • The Cost of Going All-In on AI

    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.

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  • LLM Update in Production: When Prompts Fail — and What It Means for Your Applications

    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.

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  • Mistral – the European ChatGPT

    OK, I admit that I’m sometimes too focused on technology to realise that not everyone is aware of all the different AI services out there. — This week, I mentioned Mistral.ai to a colleague and was surprised that he hadn’t heard of it. But, as I said, you can’t know everything.

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  • AI vs. the Legacy Black Box Codebase

    If you want to see a cool example of how Generative AI can be used to tackle one of the nastiest problems in enterprise IT, you might want to invest some minutes in reading “From Black Box to Blueprint.”

    What it’s about: Large organizations often have to rely on systems that are both business-critical and poorly understood due to lots of legacy. The article describes how Thoughtworks approached such a case: combining a multi-lens strategy (UI reconstruction, logic inference, change data capture, etc.) with AI-assisted “binary archaeology.”

    I really like the idea as it’s not about replacing humans, not hype but solving a real problem: complex — legacy — codebases. Something no one of us likes to lay their hands on.

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  • The Double-Edged Sword of Generative AI in Linux Troubleshooting

    I’ve recently been experimenting with how generative AI can support Linux debugging. The experience was both impressive and frustrating — depending on whether I was diagnosing or actually fixing a problem.

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