LLM integration in edtech: Separate safety scores from rubric data

This article discusses best practices for integrating LLMs into educational technology products, specifically for chatbot-based interview practice. It argues for separating safety verdicts from rubric scores in the output JSON, even when using a single LLM call. The author emphasizes that stored data, unlike chat logs, requires careful handling due to retention policies and potential future review. The proposed solution involves two distinct JSON schema outputs: one for safety and one for rubric scores, ensuring that each piece of data is validated independently. AI

IMPACT Recommends architectural patterns for LLM integration in edtech to improve safety and data integrity.

RANK_REASON The article provides an opinion and technical recommendation on LLM integration rather than announcing a new product or research.

Read on dev.to — LLM tag →

• application programming interface
• candidate
• chatbot
• JSON Schema
• LLM
• OpenAI
• rubric

• product
• other

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