I'm Neil Douek. I give keynotes and executive sessions for engineering leaders wrestling with platform engineering, Team Topologies, developer experience, and the agentic-AI shift. The talks are story-led, technically credible, and built to leave a room with a sharper way to act.
Neil speaks from practitioner experience, not borrowed abstraction: regulated financial services, global consulting, product strategy, developer-experience transformation, and current platform work with enterprise engineering teams.
His sessions connect the human and technical sides of engineering: how teams organise, how platforms reduce cognitive load, how governance can move into the flow of work, and what agentic AI changes about the way software organisations make promises.
Now that AI is rewriting the physics of how we build software, what does the next operating model actually look like?
I'm a platform practitioner who turns complex technical ecosystems into practical, scalable developer experiences. I've spent two decades inside regulated, high-stakes environments (Deutsche Börse, ICAP, the London Stock Exchange Group, Publicis, Fujitsu), plus three years at Fujitsu UVANCE leading go-to-market for Application Modernisation and Platform Engineering.
At LSEG I led DX1, a developer experience programme that reached tens of thousands of engineers and delivered measurable lifts in onboarding, telemetry, and self-service. Today I work across two complementary roles: at GitLab Professional Services, helping enterprise customers operationalise the platform; and through OTTRA, on CNI integrations and the capability-discovery signals that surface team maturity and platform health. The seam where governance, observability, and AI-assisted automation meet the systems of intent that modern platforms are increasingly asked to orchestrate.
I'm a Team Topologies Advocate, a certified GitLab Solution Architect, and the author of the forthcoming A Brief History of Engineering… and What Comes Next.
A book about the socio-technical challenges organisations face as AI reshapes how software is built, governed, and experienced. Built on the same arc as the talk: what engineering was, what it is, and the harder question of what comes next.