research-refine

To turn a vague research direction into a concrete plan, define an initial problem anchor, provide relevant literature, and set a clear success criterion to drive iterative GPT-5.4 reviews and refinement.

Problem anchoring in research refinement establishes a core problem statement that persists across multiple iterative rounds, ensuring proposals and reviews remain aligned with the original research goal throughout the workflow.

Start a phase-driven refinement workflow by defining a clear problem anchor and invoking the session, which then progresses through explicit checkpoints: anchor, proposal, review, refine, and done.

You can resume an interrupted research refinement session using state persistence and checkpoint recovery, which saves progress to refinement logs and carries the problem anchor across rounds continuously.

Before starting research plan refinement, you need an initial problem anchor, relevant literature or materials placed in a papers directory, and a clear success criterion to drive the evaluation process.

When the research refinement workflow reaches the done phase, it provides a clean handoff for downstream execution planning or experiment design, delivering a frontier-aware plan ready for implementation.