Building a News Fact-Checker AI Agent

Building AI agents that can fact-check news articles is a powerful way to combat misinformation and provide users with reliable information. Combining large language models (LLMs), Retrieval-Augmented Generation (RAG), and API integrations allows AI engineers to create robust applications that validate news content against credible sources. Mastering these techniques equips you with the skills to build intelligent, trustworthy AI systems.

In this hands-on code-along session, Jon Bennion, Manager of Applied Machine Learning at The Objective AI, will guide you through building a news fact-checker AI agent from scratch. You’ll learn how to create a simple AI agent, combine LLMs with RAG and API calls, and test and evaluate your application’s performance. The session will also cover best practices for ensuring the quality and accuracy of your AI agent, providing you with practical experience and valuable insights. This webinar is perfect for AI engineers looking to build impactful AI tools with real-world applications.

To code along live, please follow the set-up instructions below:

1. You need the below api keys for your own individual use, copy them when you have them so you can paste them in the next step:
2. An OpenAI API key
3. A Serper API key
4. In datalab, start a new workbook and add these api keys to the environment (Environment > Environmental Variables > Add > Done), you can use these names, respectively: OPENAI_API_KEY and SERPER_API_KEY
5. Confirm you have Python 3.10 selected in datalab (Environment > Language)