A knowledge worker is explaining how to use feedback to improve Claude-supported work over time.
Which description is most accurate?
A.
Capture specific feedback after each run, translate it into targeted prompt or workflow changes, and observe whether subsequent runs improve.
B.
Capture feedback only after several runs so patterns emerge from the volume of observations, then apply changes based on the patterns rather than any single run.
C.
Capture feedback as an aggregate quality score per run, since aggregate scores show whether quality is improving without requiring detail on individual issues.
D.
Capture general impressions after each run and apply them as broad prompt rewrites, since broad rewrites cover more potential issues than targeted changes.
Under the objective Adjust approach based on feedback and results, iterative refinement requires tight, closed feedback loops characterized by concrete observation, targeted modification, and empirical evaluation.
Option A details the gold-standard iteration cycle: capturing specific, granular defects immediately following an execution run (e.g., tone misalignment, omitted edge cases, formatting errors), translating those observations into targeted, discrete adjustments in prompt instructions or workflow logic, and validating whether subsequent outputs resolve the issue without regressions. In contrast, deferring feedback collection across multiple unmonitored cycles (Option B) delays error detection. Relying solely on high-level aggregate numerical ratings (Option C) lacks the actionable diagnostic detail needed to locate root causes. Applying sweeping, unfocused prompt overhauls (Option D) obscures cause-and-effect relationships and frequently introduces new failure modes.
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