Workflow · workflow
Duolingo's multi-prompt LLM roleplay system enables personalized language learning conversations
Asking a generic LLM to practice a language with you produces generic, non-personalized exchanges — the model cannot adapt to a learner's proficiency level, maintain a character's personality, or keep a conversation on a specific learning goal without a sophisticated multi-prompt system.
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 · User starts roleplay session
The user begins a roleplay session by conversing with a familiar Duolingo character.
Tools used
LLM
Outcome
Duolingo's multi-prompt roleplay system delivers targeted, fun, and effective language learning by continuously adapting vocabulary difficulty to the learner's CEFR level and maintaining engaging character-driven scenarios.
Grounding & classification
Source type: technical build writeup
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content generationconversational aipersonalizationchat transcriptbuilder submittednamed customerproduction runtime claimedtools describededucationtechnical build writeupagentic task execution