01
The Challenge
A large global enterprise — under NDA — had bought into AI, but adoption was uneven. The licences were in place and the tools were available; what was missing was a way of working that actually changed how teams shipped. They didn’t want a vendor to build it for them, and they didn’t want a permanent team on the payroll. They wanted the capability to live inside their own people — and they wanted it fast.
02
How We Worked
Drawing on the Team Topologies framework, we embedded as an enabling team alongside the client’s stream-aligned teams — on their real backlog, and deliberately temporary. We opened with a short, collaborative discovery: where their capability actually sat, and which tooling and guard-rails fit the organisation’s risk and compliance posture.
From there we worked shoulder to shoulder, helping the teams reshape their SDLC around AI-native workflows built to fit how they already shipped — not a process imposed from outside. We ran live production work through agentic tooling together, and grew the internal champions who would own the practice once we left. By design, our intensity tapered as the teams became self-sufficient — and we handed over every workflow, prompt, and playbook for them to keep.
03
The Outcome
The teams came out shipping AI-native by default — with internal champions ready to bring the next team up to speed, and a way of working they own outright. We made ourselves redundant, on schedule. The measure that matters here isn’t our hours or a short-lived velocity spike; it’s capability transferred and cognitive load reduced — and it stays with their people now that we’ve stepped out.