Matteo Villosio

Hi Matteo! You joined Checkmk as a Senior AI Engineer & Tech Lead to build up our AI function from scratch. What did your onboarding look like, and how did you experience your first few weeks in the team?

Joining to help build an AI function from scratch made the onboarding particularly interesting. I was getting to know Checkmk while also helping figure out what we should build and how we should work.

My first priority was understanding the product, the people and the problems worth solving. I brought experience building AI systems, and my colleagues brought a much deeper understanding of monitoring and our users. Bringing those perspectives together was an important starting point.

What appealed to me was the opportunity to take ownership while learning from people with a lot of experience. There was a lot to learn, but I enjoy that stage: asking questions, getting to know people and figuring out how things work.

You are leading the design and rollout of Checkmk’s first AI-powered product features and shape company-wide strategy through the AI Steering Committee. What does a typical project cycle look like for you, from the initial idea to production delivery?

I like to start with someone’s actual workflow. What are they trying to do? Where do they lose time? What would make their job easier? That gives us something concrete to evaluate an idea against.

Then we build a small prototype and test the assumptions with realistic examples. This is where we learn whether the approach is useful, where it fails and what it would take to make it dependable. Quality, response time, cost and security all influence the design.
I stay involved throughout, from architecture and implementation to code reviews and delivery. Along the way, I work with colleagues across the company to make sure we’re focusing on the right problems and sharing what we learn.

After rollout, we need to understand how people actually use the feature. That feedback often changes what we thought the next step should be.

With your strong background in open-source and AI research – such as creating ErisForge – how do you channel experimental tech and GenAI trends into a robust, enterprise-grade monitoring product?

I like trying things out for myself. I experiment with agents in my own projects, including automating parts of my personal knowledge base. Building things helps me understand what works, where it breaks and what might be useful in our work at Checkmk.

That experimentation is valuable at Checkmk because it gives us a better understanding of both possibilities and limitations. Often, the most useful result of an experiment is discovering a limitation early.

For a monitoring product, we need to understand what happens when an answer is wrong, information is missing or an input is unexpected. My interest in model behaviour and adversarial testing feeds directly into that. I want us to be ambitious about what we build and precise about what people can rely on.

Being based between Munich and Aosta, you navigate a flexible, hybrid work environment. How does Checkmk's remote-friendly culture support your daily workflow and personal work-life balance?

Aosta is an important part of my life. I love being close to the mountains, and getting outside for a run or spending time on a trail helps me clear my head. Being able to keep that connection while working with the team in Munich means a lot to me.

I value having a mix of focused work at home and time together in person. Some tasks benefit from a few uninterrupted hours; other problems become much easier when you can sit down with someone and work through them.

Making that balance work also takes effort: writing decisions down, keeping people involved and being clear about what you’re working on. For me, flexibility works best when it comes with trust and a shared sense of responsibility.

Cross-functional teamwork is key at Checkmk (spanning across 250+ employees). How do you collaborate with Development, product, and operations to drive AI enablement across the entire company?

A lot of my work involves understanding how different people approach a problem. Product might start with a customer need and engineering with a technical constraint. Working through those perspectives together helps us decide what to build and how.

For AI enablement, I particularly enjoy working directly with colleagues on their own tasks. We support all our developers through workshops, pairing sessions and shared documentation. Working through a real example together makes the possibilities and limitations much easier to understand.

We also have a round table where we read and discuss AI journals and research papers, as well as a book club. I enjoy that shared learning: hearing how someone else interprets an idea, questioning it together and seeing whether it could be useful in our work. It gives us space to explore beyond our immediate projects and learn from each other.

Looking ahead at the fast-paced world of AI, what makes engineering at Checkmk unique, and what advice would you give to future tech talents looking to apply for your team?

What I find compelling is the chance to work with very new technology in a product with an established purpose and users who depend on it. Monitoring gives you concrete problems to solve, and colleagues with deep knowledge of those problems. That makes it an interesting place to build AI.

My advice would be to build something you care about and take it far enough that someone else can use it. You learn a lot when you have to explain it, handle unexpected inputs, respond to feedback and maintain it over time. A small project can reveal a great deal about how you think.

I’d also encourage people to practise explaining their decisions and being comfortable changing their minds. At Checkmk, we value curiosity, sound engineering judgment and the ability to work through uncertainty together.

Do you remember a particularly interesting, exciting or beautiful experience you had at Checkmk? If so, can you tell us about it?

One of the nicest experiences has been receiving positive feedback from customers and users about the Checkmk MCP. You spend a lot of time working through the details of something, so hearing directly from people who appreciate the result feels really good.
It’s especially rewarding to share that feedback with the team. Getting something out involves a lot of people, and it’s a nice reminder of what we’ve achieved together. That’s one of my favourite parts of building software: seeing how people respond once it’s in their hands.