State capacity is a constraint upon effective service delivery at the local government level. Efforts to identify and scale solutions for capacity constraints are of limited effect, partly due to the variety of contexts in which different local governments operate, and partly because the capacity constraint itself limits the ability of local governments to adopt such solutions. The concept of administrative load and premature load-bearing illustrates why scaling solutions will not reliably build – and may even harm – local government capacity. In this paper, we argue for an alternative approach: distributing the capacity to solve by leveraging open-source software platforms, sometimes known as Digital Public Goods (DPGs). A platform-based approach to service delivery is inherently well-suited to working in low-capacity environments, as it sequences capacity creation and reforms intelligently, ensuring that the load on local government employees is minimised. It fits naturally with the problem-driven iterative adaptation (PDIA) approach to local innovation, learning, problem-solving, and capacity-building.