Glyn Darkin has spent two decades at the intersection of engineering leadership and technology transformation. His career began with a mechanical engineering degree and has spanned startups, global systems integrators, and enterprise technology before arriving at AI-native software delivery.

With experience as a lead engineer, chief architect, and CTO, Glyn brings a broad aptitude that moves fluidly between boardroom strategy and hands-on engineering. His track record includes building award-winning digital services for some of the UK and Ireland’s most loved brands.

Today, as global head of delivery at ClearRoute, a global platform engineering consultancy serving major banks, energy companies, and digital platforms, Glyn has made a deliberate choice to return to hands-on work by writing code, building personal projects, and working directly with AI tooling. His conviction is simple: organizations cannot meaningfully guide enterprise customers through AI transformation unless they have experienced the friction themselves.

This hands-on approach has led him deep into one of the most underexplored problems in modern software delivery: how to evaluate nondeterministic systems. Traditional quality engineering assumes predictable outputs. Agentic workflows do not. As AI agents take on increasingly autonomous roles across the software development life cycle, the absence of rigorous evaluation frameworks is not just a technical gap, but a risk.

Glyn has been building in this space directly, including LLM-as-judge test harnesses, OpenTelemetry-based agent tracing, and evaluation infrastructure designed for the unpredictability of production agentic systems.