Glyn Darkin has spent two decades at the intersection of engineering leadership and technology transformation — a career that began with a mechanical engineering degree and wound through startups, global SIs, and enterprise tech before arriving at the cutting edge of AI-native software delivery.

With a background spanning lead engineer, chief architect, and CTO, Glyn brings a jack-of-all-trades aptitude that moves fluidly between boardroom strategy and hands-on engineering. His track record includes building an award-winning digital services for some of the UK and Irelands most loved brands.

Today, as Global Head of Delivery at ClearRoute — a global platform engineering consultancy serving major banks, energy companies, and digital platforms — Unusually for someone at his level, he's made a deliberate choice to go back to basics: writing code, building personal projects, and getting his hands dirty with AI tooling from the ground up. His conviction is simple — you can't meaningfully guide enterprise customers through AI transformation unless you've felt the friction yourself.

His hands-on approach has led him deep into one of the most under-explored problems in modern software delivery: how do you evaluate non-deterministic systems? Traditional quality engineering assumes predictable outputs. Agentic workflows don't. As AI agents take on increasingly autonomous roles across the SDLC, the absence of rigorous evaluation frameworks isn't just a technical gap — it's a risk. Glyn has been building in this space directly: LLM-as-judge test harnesses, OpenTelemetry-based agent tracing, and evaluation infrastructure designed for the unpredictability of production agentic systems.