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Un mes en el bucle de retroalimentación

Qué cambió cuando obligamos a cada tarea aceptada a llevar una nota de rúbrica de vuelta al experto. Spoiler: la tasa de disputas disminuyó, la progresión de niveles se aceleró.

Escrito por

Lukas Brennan

Principal Researcher

5 min de lecturaMarzo 2026

A month ago we made one change: every accepted task carries a one-paragraph rubric note back to the expert who produced it. Not as an option. Not as a 'reviewer comments' field that sits empty on the good ones. As a required field, on every accepted submission, written by the reviewer in plain language.

The results in a single month surprised us, including the parts that did not change.

What dropped

Dispute rate fell 38% across the network and 51% in the cohort of experts in their first ninety days. Most disputes were never really about the rejection — they were about the silence around the rejection. Once experts could see what specifically was being noted on accepted work, the rejections stopped feeling arbitrary.

  • Dispute rate: −38% network-wide, −51% for experts in onboarding.
  • Median time-to-tier-up: 11 weeks → 7 weeks.
  • Reviewer time per item: +90 seconds. Worth it.
  • Expert NPS: +14, with the largest gains in the Practitioner tier.
The reviewer note on accepted work was doing more onboarding than our onboarding was.

What did not change

First-pass acceptance rate did not move. We had quietly hoped it would, because better feedback should mean better next-batch submissions. It is possible we will see it in month two or three. It is also possible that acceptance rate is set by rubric design, not by individual feedback — and that is a different lever to pull.

What we are doing next

We are A/B testing structured notes (a short rubric-aligned tag plus the free-text paragraph) against pure free-text. We are also opening the notes corpus to a small group of senior arbiters, who are using it to find rubric clauses that produce inconsistent commentary — a leading indicator that the clause itself is ambiguous and due for a rewrite.

We will share the three-month read in due course. For now: the cheapest improvement we made all year was a required text field.

Principal Researcher

Lukas Brennan

Lukas studies how expert disagreement gets surfaced, calibrated, and turned into training signal.

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