Lock-in before the first experiment narrows down where the strategy can be coming from. Nothing has been run, so nothing has been measured, and the only available inputs are the prompt and the model's prior. The sharpest evidence for that reading is the split between harnesses: Claude Code trajectories converge on full-parameter supervised fine-tuning, Codex CLI trajectories converge on parameter-efficient fine-tuning [6]. Two agents on the same task diverge systematically, which the authors take as the prior talking rather than the task [7].
This is an analysis of someone else's runs, so it is worth naming what has to hold for the pattern to appear in yours. The trajectories come from PostTrainBench, which formalised end-to-end post-training as an agent task and reported that frontier agents can complete it and lift downstream performance [13]. Transfer needs three conditions: your agent has comparable latitude over strategy, the budget is long enough that revision was actually available, and the labelling scheme would have registered a revision if one had happened. The released text describes the pattern and not the labelling procedure. It also carries the scaffold's GSM8K and HumanEval gains as bare point deltas with the numeric values absent [9], so the size of that improvement cannot be checked against what has been published.
The escalation is the useful part of the design. Three interventions were tried, and the strategy dimension moved exactly once, at the beginning, when a human moved it [10]. Interventions that produced a revision mid-run: zero [15]. The authors' conclusion is that the gap is a missing mechanism for spontaneously reevaluating strategy during execution, not a shortage of experience, guidance or reasoning compute [12].
If revision does not happen inside a run, then the run is the unit of exploration, and strategy search becomes a scheduling problem the operator owns. Anchoring on a default before looking at the data is a habit humans share; we usually call it taste.
The cheap diagnostic is a diff. Pull the strategy line out of the agent's first plan file and its last one, across tasks that differ in dataset size and label quality. If that line never changes, the opening choice was a default and the rest of the budget was tuning [4].
