I build robotics, AI agents, and memory systems for physical intelligence.
Co-founder at Orangewood, where I work on making industrial robots easier to deploy, adapt, and use in real factory environments.
This GitHub is my public lab for experiments around robots that remember, agents that reason, and AI systems that can act reliably in the physical world.
- 🤖 Physical AGI & embodied intelligence
- 🧠 Memory agents for robotics
- 🔁 Attention, memory, cognition, behavior loops
- 🧩 Neuro-symbolic reasoning systems
- 🧪 Evaluation and introspection for agents
- 🏭 AI workflow automation for industrial teams
- 🎛️ Human-machine interaction for robotics
I use GitHub as a working surface for research-practice projects, technical demos, and system design experiments.
Some active directions:
- 🦾 Memory-enabled industrial robotics
- 🧠 Agent architectures with persistent memory
- 🔍 Reasoning systems that expose their steps
- 🧰 Evaluation tools for failure, recovery, and self-correction
- 🌍 Embodied world models for physical systems
- 🏭 Robotics demos that connect AI behavior to real-world action
Intelligence becomes useful when it can remember, adapt, recover, explain, and act reliably in the physical world.
The next wave of AI will not just be about better answers.
It will be about systems that can hold context, build memory, learn from failure, coordinate with humans, and operate inside messy real-world environments.
Robotics · AI Agents · Memory Systems · Physical AI · Cognitive Architectures · Reasoning Systems · Industrial Automation · Human-Machine Interaction
This is where I publish experiments, notes, demos, and technical direction as I explore one central question:
How do we build intelligent systems that do not just think, but remember, adapt, and act?
Still early. Shipping in public. Making the robots slightly less confused every week. ⚙️✨