Building deployable AI agent systems and platforms.
PhD in Economics · MSc in AI (UZH)
Luxembourg / Zurich
I design and build AI agent runtime and platform systems focused on:
- Deployable AI agents (OpenClaw-based)
- Kubernetes (K3s) orchestration
- Tooling & skill ecosystems
- Self-hosted and scalable AI infrastructure
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🔧 Patched OpenClaw Runtime
- Extended capabilities (browser, scraping, CLI tools, data processing)
- Production-ready container environment
-
⚙️ AI Agent Deployment (K3s / Kubernetes)
- Multi-instance orchestration
- Isolated runtime environments
- Scalable deployment patterns
-
🧩 Skills & Tool Ecosystem
- Web scraping & content extraction
- Data processing pipelines
- System-level tool integrations
-
🧪 Towards an AI Agent Platform
- One-click agent provisioning
- Runtime + tools + orchestration
- Platform layer (API-driven deployment)
User / API
↓
Platform Layer (in progress)
↓
Kubernetes (K3s)
↓
OpenClaw Runtime (patched)
↓
Skills / Tools / Extensions
Enhanced runtime with extended capabilities for real-world usage
→ container environment + system tools + execution layer
Reusable tool modules for AI agents
→ scraping · parsing · data workflows · system utilities
K3s-based multi-instance deployment
→ isolated agents · reproducible environments · scaling
API-driven agent provisioning system
→ create / manage / scale agents programmatically
I am working towards:
→ A deployable AI agent platform
→ Supporting multi-instance, multi-user environments
→ Bridging AI systems with real-world infrastructure
- Kubernetes (K3s)
- Docker / Container systems
- Python
- Linux systems & CLI tooling
- AI agent frameworks (OpenClaw ecosystem)
- GitHub: https://github.com/ernestyu
AI is not just models —
it is systems, runtime, and deployment.