Agentic engineering significantly influences agile software development, maintaining agile’s relevance while necessitating evolution in practices. As AI agents manage tasks autonomously, the role of humans transforms to primarily guiding these agents, leading teams to adjust their traditional structures and workflows.
Specifically, agile teams must redefine roles, adapting to the shift where humans focus on specifying tasks for AI agents rather than coding. Additionally, the scope of agile stories changes, allowing for more extensive objectives due to increased efficiency. Managing concurrency and emphasizing end-to-end testing become crucial in an era where AI operates faster than human developers, necessitating rigorous examination practices to ensure user needs are met effectively.
Moreover, robust software development metrics gain importance as teams seek to quantify efficiencies and identify potential risks introduced by AI agents. While agentic engineering presents new challenges, the foundational elements of agile methodology remain vital for the successful management of software projects in this evolving landscape.
👉 Pročitaj original: CIO Magazine
