AI automation agents for real operations
Orchestrated workflows, shared memory, and operator visibility
The thesis is simple: agents become useful when execution is bounded, memory is durable, and operators can see what is happening in real time. This site focuses on building that stack across orchestration, context systems, and monitoring surfaces.
Operating Contexts
Background, CV, and career context live on the About page.
The Agent Stack
Agent automation is not a single app. It is a system made of three cooperating layers: orchestration, shared context, and operator visibility. Remove one layer and the whole thing becomes fragile.
Execution topology
Issue intake becomes a bounded run with memory, logs, and operator review
Run queue
24 active
Context sync
97.8%
Operator reviews
3 pending
Design rules
Agents should run in bounded workflows, not open-ended chat loops.
Memory must be durable, inspectable, and shared across human and agent access paths.
Monitoring must show what is running, what is blocked, and what requires intervention.
Systems Proving The Stack
These projects show the operating model in pieces: orchestration, shared memory, monitoring, and the industrial reliability habits that keep automation usable outside a demo.
Interactive Demos
Explore working prototypes of systems I've built. These dashboards demonstrate real-world interfaces with realistic data—but they're read-only simulations for demonstration purposes.
Read-only demonstrations. These interfaces showcase the actual design and functionality of production systems. All data is simulated—no backend services are running.
Want to see the implementation details?
View Project Case StudiesGet in Touch
Available for contract work, full-time opportunities, and consulting engagements. I'm based in Zurich, Switzerland and work with clients globally.
Location
Zurich, Switzerland
Available for remote work and on-site engagements in Europe.
Response time is typically within 24 hours. For urgent inquiries, email is preferred.