Building applied AI systems, multi-agent workflows, and privacy-aware infrastructure.
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- Multi-agent orchestration (
clawdbot-the-endgame) - Privacy-aware AI (SoraChain AI)
- Production-grade AI systems (research -> deployment)
- OpenClaw execution workflows
Learning
- Context engineering
- Reinforcement learning
- Memory systems for agents
- Turning research ideas into durable tools
| Project | What it is | Status |
|---|---|---|
clawdbot-the-endgame |
Local-first multi-agent operating system for research, hiring, and structured execution | 🟢 Active |
openclaw_mirofish_outreach |
OpenClaw outreach workflow system for autonomous, context-aware execution | 🟢 Active |
parameter-golf |
Foundational AI research track (parameter-constrained model optimization) | 🟢 Active |
healthcare_ortho |
Federated learning healthcare PoC around SoraChain AI | 🔵 Stable |
Pomodoro-Cube |
Swift app for focused work sessions | 🔵 Stable |
- System-design-first approach: architecture, constraints, and failure modes before implementation.
- AI-assisted build loop: Codex + Claude Code + Antigravity as force multipliers for speed and breadth.
- Foundational AI research through parameter-constrained modeling and efficient architectures.
- Agent reliability: context engineering, memory design, evaluation, and long-horizon orchestration.
- Federated and privacy-aware AI systems that translate research into deployable products.
- 10+ years in distributed architecture, solutioning and technical strategy.
- Founder of Build Superagency and SoraChain AI.
- Speaker at NVIDIA, Global Open Source AI Conference (GLOSAIC), and OpenAI community events.
- Collaborating on foundational AI research (model efficiency, agent reliability, evaluation systems)
- Building multi-agent systems from the ground up with strong architecture and execution discipline
- Working with teams translating AI research into production-grade tools and workflows
- Technical talks, advisory, and hands-on AI upskilling workshops