I am a design-led Product Manager and agentic builder in Berlin, with 15+ years in tech.
I own, design, prototype and build products end to end.
SaaS, MarTech, marketplaces, logistics, lately construction and typography.
How I work
Breaking large projects into buildable steps has been part of my work since I started out storyboarding 3D animation.
I prototype fast with agentic AI to learn, iterate and improve.
Security and privacy go in from the start.
I like a team around me. At Movinga, touching the booking flow meant touching every department in the company — that is the kind of problem I find interesting.
Product strategy & vision, roadmapping, prioritisation, continuous discovery, backlog ownership, user stories & acceptance criteria, lifecycle management, A/B testing, product analytics, pricing & monetisation, stakeholder management, cross-functional leadership, go-to-market
Rapid prototyping and shipping with agentic AI tooling; connecting APIs and normalising their formats
(Claude Code, Figma, TypeScript, Next.js, Tailwind, Supabase, Vercel, WebGL, ...)
Design systems, UI/UX, editorial, storyboarding
Agile, Scrum, Kanban, rapid prototyping, workshop design & facilitation, design sprints
Claude Code, Figma, Adobe Suite, Jira, Miro, Google Workspace
German (native)
English (C1)
Prototype Thinking
These days I build digital things faster than I could have planned them.
Planning a digital product first used to be the recommended order. It was a lot cheaper than building.
From waterfall to agile, we planned as granular as we could — or were allowed to. We often prototyped, but built last.
AI changes that equation. A first working version is now often faster to build and share than to plan.
The outlook I see
Most likely Prototype Thinking is the new way of working. At least it is how I work now: start from a vision for context, strip it to the core, build a proof of concept, then an MVP. Test it, watch where it breaks, and turn what breaks into SKILL.md files and guardrails so it does not break twice. Because requirements don't go away.
Design Thinking wanted us to understand before we build. We still need to. The understanding just arrives in increments. Design sprints were great for aggregating perspectives, but they tied up a lot of team capacity, and a measurable ROI stayed beyond the horizon.
In AI-driven companies this is already becoming team practice: skills, plug-ins, harnesses and guardrails as shared assets, building blocks as a common library. Prototypes land inside the existing architecture instead of beside it, which can be tricky as LLM semantics are not deterministic, and results vary a lot across models and individuals.
That also opens a window to blend disciplines, and to let more people take part. Prototype Thinking comes with new breaking points and pitfalls. How it evolves from here is the interesting part — happy to discuss.
What can Iget out ofyour way?
Reach out