SuperAPI AI Directory

duo-experimentation

Data & analytics

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Updated 10-15 22:13

About this skill

Duolingo Experimentation — Map of Content

Duolingo runs hundreds of experiments per week and treats the result as the decision, not as one input. The handbook calls this Show Don't Tell: when people disagree, the experiment is the answer, not the more senior person's intuition. This skill packages that protocol.

This skill is structured as a graph: scan the descriptions below, follow only the [[wikilinks]] you need.

The protocol

  • [[references/show-dont-tell]] — the principle: metrics decide, not titles.
  • [[references/hypothesis-design]] — what makes a testable hypothesis vs. a wish.
  • [[references/ab-test-structure]] — variant/control, randomization unit, exposure rules.
  • [[references/ladder-of-evidence]] — four methods with four blind spots: interviews, controlled experiments, A/B tests, outcome studies.

Metrics

  • [[references/metric-selection]] — picking a primary metric that actually maps to long-term retention, not the easiest-to-move one.
  • [[references/guardrail-metrics]] — the metrics that must not go down, even if the primary does up; includes the cannibalization check.
  • [[references/sample-size]] — how big, how long; the cost of stopping early.
  • [[references/outcome-not-engagement]] — engagement proves a feature was tolerable; only a holdout delta on the targeted failure proves it worked.
  • [[references/invariant-metric-for-redesigns]] — judge a structural redesign on the terminal outcome, not the proxies it was tuned for.

Measurement design

  • [[references/design-the-population]] — who is eligible to enter a comparison decides what it measures.
  • [[references/baseline-at-first-contact]] — capture a self-reported starting level once, or you cannot separate teaching from selection.
  • [[references/probes-inside-the-product]] — embed the measurement in ordinary usage instead of building a separate test surface.
  • [[references/quasi-experiments]] — causal reads without randomization: self-as-control, matched cohorts, within-stratum scoring.

Pitfalls

  • [[references/novelty-effects]] — the lift that decays after week three; how to detect and discount it.
  • [[references/ship-and-iterate]] — when "good enough to ship" beats "perfect to test."
  • [[references/unmeasurable-wins]] — changes you cannot A/B test by construction, and how measurability quietly steers the roadmap.

Discipline

  • [[references/kill-criteria]] — the threshold for stopping an experiment instead of milking it.
  • [[references/experiment-cadence]] — weekly review rhythm that keeps "hundreds per week" survivable.

Sibling skills

  • [[../duo-retention/SKILL]] — every retention claim has an A/B test under it; cite both.
  • [[../duo-product/SKILL]] — Ship It and Show Don't Tell are the same culture seen from two angles.
  • [[../duo-culture/SKILL]] — experimentation only works if disagreement is safe; that's a culture problem too.

Sources

  • Duolingo Handbook (2025), Principle #4: Show Don't Tell
  • blog.duolingo.com — engineering and experimentation posts