Building Responsible Large Language Model Applications
Webinar on making LLM applications safer and more reliable with transparency, guardrails, and production-ready practices.
This webinar explores what “responsible LLM applications” really means in practice, from transparency and explainability to production reliability and safety. You’ll see why large language models can be manipulated through prompt injection, why “black box” outputs need traceability, and how guardrails can enforce structure, validation, and corrective actions for real applications. The session also covers how LLMs are changing everyday software delivery, helping junior developers become productive faster while shifting senior work toward planning, evaluation, and communication.
You will learn how to:
- Improve trust with transparency and backtracking of AI outputs
- Add guardrails and validation to reduce hallucinations and unreliable responses
- Apply LLMs in production while considering privacy and responsible use
As speakers we have Harri Ketamo from Headai, Shreya Rajpal from Guardrails AI, and Sergei Häyrynen from Veracell.
👉Watch the webinar below
