Improving Intent Detection in AI Interview Coach
Product#rag👥 Community|Analyzed: Apr 17, 2026 16:16•
Published: Apr 17, 2026 14:39
•1 min read
•r/LanguageTechnologyAnalysis
The article discusses challenges and seeks advice on enhancing the accuracy of intent detection for an AI interview coach, focusing on differentiating between resume-specific and performance-specific questions.
Key Takeaways
- •Context Injection vs. Hard Routing debate for complex questions.
- •Alternative methods to Cosine Similarity for better intent detection accuracy.
- •Handling multi-turn conversations where user's intent changes.
Reference / Citation
View Original""Once the intent is detected, I build an Execution Plan that toggles use_rag (Resume data) or use_verdict (Interview report). However, I’m seeing some 'intent bleed' where a user asks something like 'How can I improve my technical answer?' and the system struggles to decide whether to pull from the Resume (technical skills) or the Verdict (how they actually performed).""