It’s easy to send a single prompt to an LLM and check if the output meets your expectations. But once you start shipping real products, from RAG assistants to autonomous agents, you quickly run into a harder question: how do you know it’s actually working?
To get clear on this, join us on August 6 for a free webinar hosted by Nebius Academy, the AI-centric cloud platform behind Y-DATA and other educational projects for tech-minded learners.
When you’re building with LLMs, you’re constantly changing prompts, tweaking logic, and updating components. That means you need to reevaluate outputs all the time. But manually checking everything doesn’t scale.
There are automated evaluation techniques we can borrow from traditional ML. But most LLM systems behave differently from standard predictive models — they generate open-ended text, reason step by step, and interact with external tools. That calls for a new approach to evaluation and observability.
In this webinar, our speakers Emeli Dral and Elena Samuylova, co-founders of Evidently AI, will break down practical strategies for evaluating and monitoring LLM-powered systems. Drawing from real-world experience and their in-depth long read on evaluation, they’ll walk you through how to:
✔️ Frame meaningful evaluation goals for generative and agentic workflows
✔️ Combine automatic and human-in-the-loop methods
✔️ Design regression tests and define observability signals that scale
✔️ Avoid the most common pitfalls when shipping LLMs in production
If you’re building or maintaining LLM-powered systems, this session will help you go beyond benchmarks and focus on creating trustworthy, reliable products.
Save the date!
📆 August 6
⏰ 8 PM Israeli time
📹 Zoom
👉 Join the webinar
See you there!
