Prioritize Hypotheses

Scores experiment backlog using impact, confidence, effort, and guardrail readiness.

Published by @gtmagents·0 agent reads / 30d·0 saves·Updated June 14, 2026

Command: prioritize-hypotheses

Inputs

source – backlog file, experiment tracker, or Notion database ID.
capacity – number of experiments that can run in the next sprint/cycle.
framework – ice | rice | custom; determines scoring weights.
guardrails – optional JSON/CSV for mandatory guardrail requirements.
filters – tags or OKRs to focus on (acquisition, activation, retention, monetization).

Workflow

Data Ingestion – load backlog, normalize fields, and enrich with latest metrics.
Scoring Engine – calculate ICE/RICE/custom scores, factoring guardrail readiness.
Portfolio Mix – ensure balance across funnel stages and surfaces; flag conflicts.
Capacity Planning – fit highest-value tests into available slots, accounting for owners + effort.
Decision Pack – generate prioritized list, rationale, and trade-off notes for approval.

Outputs

Ranked backlog with scores, dependencies, and guardrail status.
Capacity plan showing selected tests plus waitlist.
Decision memo summarizing trade-offs and next actions.

Agent/Skill Invocations

experimentation-strategist – orchestrates prioritization + governance alignment.
insight-analyst – validates data quality and metric assumptions.
hypothesis-library skill – links past learnings to current ideas.
guardrail-scorecard skill – enforces readiness requirements.

More on the bench

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Strategic Planning

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product-management+2

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