Design Problems, Decisions, and Evidence in Agentic Software Engineering: A Systematic Mapping Study

Agentic Software Engineering (ASE) systems depend on decisions about context, reasoning, coordination, tool use, execution, and verification. This systematic mapping study maps problems, design decisions, operationalizations, and evidence in peer-reviewed studies of LLM- or foundation-model-based agentic systems in Software Engineering from 1 January 2024 to 13 July 2026. ACM Digital Library, IEEE Xplore, Scopus, and Springer Nature Link were searched on 13 July 2026 using the same Boolean string. From 1069 records, 94 studies were included. A frozen, single-paper-isolated extraction protocol identified 1018 design decisions, followed by deterministic multi-label synthesis; no formal study-level risk-of-bias assessment was performed. Of these decisions, 633 were linked to 656 problems or objectives, and 913 (89.7%) had empirical or comparative evaluation records. Only 19.8% of evaluation records attributed evidence to an individual decision, whereas 52.3% assessed complete systems; multi-agent configurations represented 68.7% of problem-linked decisions. Heterogeneous metrics and system-level evaluation limit inference about effectiveness. The findings expose a gap between evaluation coverage and decision-level attribution and motivate ablations and human-centered evaluations. The review received no external funding and was not registered.