If you’ve ever wondered how to take control of your digital life without immediately diving into the deep end of server racks and command-line chaos, I want to recommend Laura Hargreaves’ latest post, “Self-Hosting for Everyone”.
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Feeling Trapped by Big Tech? Just Take the First Step
Do you feel that you are too dependent on Big Tech and overwhelmed by the number of services you use?
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Recommended read: Frictionless – About Eliminating Development Friction
I just read Martin Fowler’s blogpost and foreword to Frictionless by Andrew Harmel-Law. The book’s core idea is simple but powerful: How do we make developers truly efficient? Not by adding more processes, tools, or meetings, but by removing the friction that slows teams down and using smart metrics.
I put it on my reading list and I’m curious about it!
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I break things … Google Veo
Recently I had the opportunity to test the new Google AI-Video generator powered by Veo 3(.1). The demo was truley impressive and scary at the same time! And then we were able to test it ourselves …
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A sentence about Data Quality that I missed for over a decade
In Data Analytics, there’s one phrase I hear over and over—so often it’s become a reflex: “We need clean data before we can do anything.”
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o365 “control plane” for AI Agents coming
I just read an article on InfoWorld, that Microsoft rolls out Agent 365 ‘control plane’ for AI agents. The description sounds quite well what an enterprise needs in terms of compliance and security:
Microsoft said that Agent 365 unlocks five capabilities intended to make enterprise-scale AI possible:
- Registry, to view all agents in an organization, including agents with agent ID, agents registered by the user, and shadow agents.
- Access control, to bring agents under management and limit access only to needed resources.
- Visualization, to explore connections between agents, people, and data, and monitor agent performance.
- Interoperability, by equipping agents with applications and data to simplify human-agent workflows. They would be connected to Work IQ to provide context of work to onboard into business processes.
- Security, to protect agents from threats and vulnerabilities and remediate attacks that target agents.
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AWS, Azure, Cloudflare – who’s next?
On October 20th, quite some parts of AWS went down (AWS Outage Analysis: October 20, 2025, What caused the AWS outage – and why did it make the internet fall apart?).
I don’t follow thouse outages very intensly, but the last such outage I remember(!) was end of February 2017 with the big S3 outage (The great Amazon S3 outage of 2017, Amazon And The $150 Million Typo).
Then not even 10 days later, Microsoft Azure‘s Frontdoor had a wide spread service disruption on October 29th, that affected a lot of Azure clients (Microsoft Azure Front Door Outage Analysis: October 29, 2025)
And today, on November 18th, Cloudflare experienced an outage that affects large parts of the internet (Cloudflare apologises for outage which took down X and ChatGPT, Cloudflare outage: Services globally disrupted)
As if we wouldn’t be talking about digital sovereignty enough … These incidents just show the dependency of large parts of the internet to just a small amount of companies. Not exactly what was intended when the internet was built.
Can we just count days until GCP follows? For Google, I hope that they won’t have an outage in the christmas shopping period.
Update Oct. 19th: heise online nailed it pretty well:
After a series of comments about why we find it stupid to rely on the cloud, we’ve now reached the point where we find it stupid to have to write a comment about it every week.
Nach dem Cloudflare-Ausfall: Digital völlig unsouverän | heise onlineFediverse reactions
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What I am Missing in Most GenAI Conversations
When people talk about Generative AI, the focus is usually on:
- Prompting
- LLMs
- Chatbots
- Proofs of Concept (POCs)
But what I am missing a lot in those conversations are:
- Try classic automation first
- Process integration: Can I add it into a process so that it fixes a problem?
- Data privacy
- Security
- Works council/employee representation (if applicable)
- Observability (not just the usual observability but also prompts and responses)
- Robust data pipelines (a.k.a ETL)
- Model Selection
- Model decay & re-evaluation (How often will you need to update? Currently about ~1x / year)
- Regulatory Compliance AI Act (EU)
- Costs (Tokens, maintenance, scaling — over years, not demo days)
- Scalability
- Latency & Performance:
- Testing (“it works in demo” ≠ “it works in production with real users”)
- Human-in-the-Loop (HITL):
- The other 95% of the app (The “boring” software stack around the AI)
- APIs (If it’s meant to automate, it needs to talk to other systems)
If there’s a user interface:
- Interface design & UX (no one uses what they can’t understand)
And the elephant in the room:
- How do you address the fear—justified or not—that you might be innovating people out of their jobs?
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The Architect I Never Knew I Was
For years, whenever someone asked me what I do, I described my projects and activities, like “I worked on a cloud migration, reduced technical debt, refactored systems to be cloud-native, designed environments for scalability, cost effectiveness and security, …”. But I could never express in a TL;DR what I really did. My official title “Senior Process Manager” wasn’t very helpfull as well.
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Why Your Favorite AI Tool Might Be Isolating You
AI chat tools are a remarkable invention. Their rapid adoption speaks for itself: instant access to information, tailored feedback, and the ability to explore ideas or discuss one own thoughts or questions without friction – never before did we have such opportunities. But this power can come with a risk.
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