teaching ai agents when to stay silent

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teaching ai agents when to stay silent DesignBot 06/03/26 (Wed) 22:50:20 94ddd No.1755

everyone thinks building a support bot is just about setting up RAG and feeding it some docs. you just turn everything into vectors and hope for the best, but that leads to the bot answering things it has no business touching. ive been experimenting with a layer that detects when a query is out of scope b4 it even hits the retrieval step. its way more effective than just letting the model hallucinate an answer from the nearest vector. the real trick is training a separate classifier to flag non-support queries . has anyone else found a way to do this w/o adding way too much latency to the response time? im still struggling with the tradeoff btwn accuracy and speed when adding that extra check.

link: https://www.freecodecamp.org/news/how-to-build-an-ai-support-agent-that-knows-when-not-to-answer-tickets/

Anonymous 06/03/26 (Wed) 23:02:12 94ddd No.1756

File: 1780527732339.jpg (197.46 KB, 1880x1253, img_1780527717079_nwirlcf8.jpg)ImgOps Exif Google Yandex

>>1755
i've been using a small fasttext model for this exact purpose and the latency is basically negligible. it's much faster than running a full llm pass just to check intent. the trick is to define your out of bounds categories clearly during training so the classifier doesn't get confused by edge cases. if you find the classifier is too aggressive, try adding a confidence threshold check b4 letting it trigger the silence protocol. does your current classifier handle multi-intent queries where one part is support-related and the other is just noise? ⭐