Building applied AI systems, multi-agent workflows, and federated learning infrastructure.
Founder-operator with a background in protocol design, cryptoeconomics, and complex technical systems.
For a long time, I could think in systems faster than I could build them. Codex and Claude Code changed that. Now I use a workflow that lets me turn architecture into working systems at the speed I design.
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Working on: multi-agent orchestration with
clawdbot-the-endgame, privacy-aware AI through SoraChain AI, and practical workflows built with Codex and Claude Code.
Excited by: context engineering, reinforcement learning, memory systems for agents, and turning research ideas into durable tools.
- Building and refining multi-agent orchestration systems such as
clawdbot-the-endgame - Exploring federated learning, federated RAG, and privacy-aware AI through SoraChain AI
- Pushing high-skill AI coding workflows with Codex, Claude Code, and practical automation
- Going deeper on the technical foundations behind reliable agent behavior
- 8+ years across AI, distributed systems, solution architecture, and stakeholder-heavy technical delivery
- Founder of
Build Superagency(AI Upskilling Workshops, The Netherlands) andSoraChain AI - Former roles across Binance, ZetaChain, and ICTU (Dutch Government)
- Supported 200+ ecosystem teams on architecture, integration, and launch
- Speaker at NVIDIA, the Global Open-Source AI Conference, and OpenAI community events
- Background in protocol design and cryptoeconomics spanning roughly a decade
| Project | What it is |
|---|---|
clawdbot-the-endgame |
Local-first multi-agent operating system for research, hiring, and structured execution |
healthcare_ortho |
Federated learning healthcare proof of concept built around SoraChain AI |
FL |
Federated learning experiments and implementation work |
Pomodoro-Cube |
A smaller build on the side, written in Swift, for focused work sessions |
- Multi-agent orchestration and OpenClaw-style systems
- Getting strong output from AI coding tools without lowering standards
- Federated learning and privacy-aware AI architecture
- Protocol design, cryptoeconomics, and technical strategy
- Context engineering
- Reinforcement learning
- Memory management for agents
- Agent reliability, evaluation, and system design under real constraints


