[Background] Poorly formulated research problems can compromise the practical relevance of Software Engineering (SE) studies by not reflecting the complexities of industrial practice. [Aims] This paper explores the vision of integrating artificial intelligence (AI) agents to support SE researchers during the early stage of a research project: the formulation of the research problem. [Method] Based on the Lean Research Inception (LRI) framework and using a published study on code maintainability in machine learning as a reference, we developed a descriptive evaluation of a scenario illustrating how AI agents, integrated into LRI, can support SE researchers by pre-filling problem attributes, aligning stakeholder perspectives, refining research questions, simulating multiperspective assessments, and supporting decision-making. [Results] The descriptive evaluation of the scenario suggests that AI agent support can enrich collaborative discussions and enhance critical reflection on value, feasibility, and applicability of the research problem. [Conclusion] Although the vision of integrating AI agents into LRI is promising for a more context‑aware and practice‑oriented formulation of research problems, empirical validation is needed to confirm and refine this AI-enabled methodology.