back_office_ops · workflow
How Duolingo uses AI and human expertise across four stages to build personalized language learning courses
Creating accurate, engaging language course content at scale requires more than human expertise alone; Duolingo concluded that combining human curriculum knowledge with AI-driven efficiency was the best path to high-quality, individualized learning experiences.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Curriculum design by experts
Experienced curriculum designers carefully plan what to teach and when for each course, sequencing learning objectives according to CEFR standards and the learner's native language.
Tools used
버드브레인 모델
Outcome
The four-stage human-AI pipeline delivers personalized Duolingo lessons that teach carefully sequenced concepts through varied content and adapt exercise selection and timing to each learner's individual needs, with the content team working faster, more accurately, and more efficiently.
Results
Volume더 신속하게, 더 정확하게, 더 효율적으로
Grounding & classification
Source type: technical build writeup
17 fields verified against source quotes.
content generationpersonalizationrecommendation systemspeech to textknowledge basehuman review describedmetric backednamed customerproduction runtime claimedtools describedvendor confirmedworkflow describededucationemployee productivitytechnical build writeupback office opsai draft human approval