[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 vision paper explores the use of 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 the value, feasibility, and applicability of the research problem.

[Conclusion] Although the vision of integrating AI agents into LRI was perceived as promising to support the contextĝ€'aware and practiceĝ€'oriented formulation of research problems, empirical validation is needed to confirm and refine the integration of AI agents into problem formulation.