AI-native delivery, industrial discipline

The method

AI in the loop at every stage

Anthropic's Claude Code is the primary development tool — through design, implementation, code review, deployment, and operations. This website is itself built and maintained that way.

A workflow that spans sessions and projects

Parallel workstreams with the AI carrying context across sessions — project maps, knowledge bases, and research journals that let any session pick up where the last one stopped. That is the practical difference between using a chatbot and running an AI-augmented engineering practice.

Proof over promises

The systems on the homepage are not a portfolio of demos — they run in production, operated single-handedly: a multi-tenant analytics platform with a worker-thread ingestion pipeline, a Go-based simulator with a continuous evaluation harness against real observed data, a self-hosted file platform with a deliberate security model, vehicle-telemetry automation feeding business systems, and a private cloud running 15+ services with rehearsed recovery.

Industrial discipline, carried over

Version control for everything including infrastructure, standardised deployment pipelines, layered security, three-tier backups, and monitoring — the same practices used on safety-critical control systems, applied to every AI system we ship.

What this means for a client project

One accountable engineer from brief to running production system: faster iterations, no hand-off losses between roles, and operational ownership after launch — the system is not thrown over a wall when it goes live.