The aim of this report is to help software engineering leaders assess the maturity of agentic AI technologies and identify where to prioritise investment. It provides a data-driven overview of the current state of agentic AI adoption and implementation amongst professional developers. We begin by examining how widely agentic AI architectures are being implemented and the contexts in which they are used. We then explore the key use cases that AI agents are designed to handle, analysing their relative maturity by comparing popularity in prototyping versus production environments. This is followed by an assessment of developer familiarity and engagement with Model Context Protocol (MCP) servers. Finally, we take a look at the usage and awareness of the leading frameworks/platforms that are used to deploy agentic AI systems.