7 docs tagged with "components"

As an activity evolves, its traits shift dramatically. In the early stages it is uncertain, rare, and poorly understood. Over time it becomes commonplace, predictable, and focused on efficiency.

Elements of a system don't evolve in isolation. Practices often change alongside the activities they support. For example, new engineering techniques may arise when a related technology matures.

All parts of a value chain move from novel beginnings toward well defined commodities. Competition and user demand push activities, practices, and even mental models from experimentation to standardisation. Early on you might custom build an entire stack yourself, but over time those same capabilities become utilities that you simply plug into.

Change rarely happens in one smooth curve. Adoption tends to surge then stall as it crosses different chasms before the next wave picks up.

When competitors adopt a more evolved component, others feel pressure to follow. The gains in efficiency and capability create a pull that is hard to resist. This "Red Queen" effect means standing still rarely remains an option: as some players move forward, the rest must keep pace simply to survive.

A system is built from components that sit at different stages of evolution. Experimental parts require freedom to change, while industrialised parts demand stability and efficiency. Because of this mix, a single management or delivery method cannot suit every component.

Markets don't all move at the same speed. Consumer-facing systems often change much faster than long-lived industrial platforms. Understanding the ecosystem helps you gauge how quickly components will evolve.