I build AI agents that survive contact with the real world.

Most "AI agents" are a wrapper, a prompt, and a prayer. They look unstoppable in a demo and fold the second they touch real, messy production data. I build the other kind. Hooked on AI since ninth grade and never shook it.

High bandwidth is the actual edge: I run several builds/projects in parallel without dropping them, which my ADHD insists is a feature, not a bug. I work from 0 → 1, usually on a few zeros at once.

Co-founder and CTO of AgentyLab , building agentic AI for vertical industries, recruitment first. The agents live where the work already happens (Gmail, Slack, LinkedIn, ATS tools) instead of begging anyone to learn another dashboard.

Co-founder of AIxHuman , building AI-human collaboration. The long game: how people and machines actually think better together.

Agentic systems and multi-agent orchestration. LLM infrastructure, post-training, and evals. Knowledge graphs as the memory layer that makes an agent reliable instead of confidently wrong. Mostly: killing the gap between "works in the notebook" and "works in front of a customer."

• ARIA (UK Advanced Research and Invention Agency): sole architect of the knowledge graph infrastructure behind their agentic AI capability.
• Scintilink: founded an AI Scientist platform built for research workflows.
• XQTechnical: Lead AI Engineer across Formula One Recruitment.
• MSc AI & ML, Distinction (Queen Mary University of London) · Perplexity AI Business Fellow · 2 peer-reviewed papers (Springer Nature, IEEE Xplore).

Contribution history carried over from a previous work account.

• limitless : keeps a Claude Code session alive across usage-limit windows. Wraps the TUI, auto-continues at reset, runs headless.
• claudecodetts : gives Claude Code a voice using the built-in macOS Siri TTS.