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Learn a practical framework to build test cases, choose metrics, set regression tests, and add guardrails to make LLM-powered chatbots reliable, safe, and less prone to hallucinations. This webinar also covers live monitoring strategies to make your chatbot reliable. What you’ll learn: How to build test cases that reveal weak points in LLM behavior Choosing metrics that accurately reflect performance and reliability Setting up regression tests to safely deploy chatbot updates Adding guardrails to minimize hallucinations and harmful outputs Live monitoring and log analysis strategies to continuously improve performance Find a link to the LLM evaluation library here: https://parslabs.org/resources/llm-ev... Meet the speakers: @LenaShakurova is the founder of ParsLabs (https://parslabs.org), a Conversational AI agency, and Chatbotly (https://chatbotly.co), a no-code platform for building AI assistants trained on custom data. At ParsLabs, she leads a team blending AI, user research and conversation science to design and develop high-quality AI Conversations that sound more human. She has a background in NLP and Artificial Intelligence and 7+ years of experience, and 100+ successful projects building production-ready chatbots and voice assistants. Lena focuses on ethical, user-first AI, leveraging her expertise in Linguistics & AI to create responsible, high-quality AI solutions. She shares insights on AI innovation and human-centred design through her blog (https://shakurova.io/blog) and LinkedIn ( / lena-shakurova . Willem Don is one of our seasoned Conversational AI Trainers, with eight years of extensive experience in language model development and evaluation. Throughout his career, he has successfully managed AI implementations for over 40 clients, demonstrating a profound understanding of dialogue system intricacies. As a contributor to the Conversation Design Institute's AI Trainer Course, he has been instrumental in shaping the next generation of AI training methodologies. 00:00 Intro 03:53 Why we shouldn’t launch without evals 06:07 3-stage LLM evals framework 08:45 Setting up experiments for LLM-based AI Assistants 10:39 Making a good test set 17:00 LLM eval metrics 19:01 LLM-as-a-judge 30:02 Specifics of evaluating LLM-based chatbots 31:35 RAG evals 36:00 Response quality evals 37:23 Conversation structure evals 42:09 Conversation simulations 49:30 Outro Watch more webinars here: https://learn.conversationdesigninsti...