Methods and Techniques of Agentic Software Engineering: A Systematic Literature Review

The development of agentic software engineering (ASE) is shifting the software development process, specifically by adopting autonomous agents into the fundamental software development process, where autonomous agents using large language models (LLMs) and artificial intelligence (AI) make decisions, write code, and collaborate across the entire software development lifecycle. The systematic review is a summary of literature on the agentic software engineering methodologies, frameworks, and techniques published in 2022-2025. We identify and compare methods based on autonomous coding, multi-agent systems, iterative refinement, and human-agent collaboration, drawing on 61 high-quality studies. We find that LLM-based agents show substantial potential in automated software engineering and that recent work is exploring new trends in agent cooperation, reasoning systems, and tool integration. We recognize such key challenges as the coordination procedures, reliability, explainability, and the ethical issues. This review characterizes the emerging role of agentic software engineering in improving the productivity of developers, the quality of their code, and the automation of their processes, and it offers a structured roadmap for future research. With the rapid evolution of the field, agentic approaches will tend to transform the conception, creation, and maintenance of software and provide more autonomous, adaptive, and intelligent systems.