Unleashing Investigative Reporter AI Agents across a Data Platform: A Prototype

In this post, I’ll walk you through the development of an AI-powered agent designed to analyze social conversations about climate change. This agent acts like an investigative reporter — digging into discussions, collecting relevant data, and ultimately producing a summary that provides key insights into the conversation’s core narrative.

The image above outlines the agent’s design. It starts by assessing the conversation, then loops through a series of research tasks, continually updating its internal “notepad” with new discoveries. Once enough information is gathered, the agent synthesizes everything into a story.

In this video walkthrough, I provide an in-depth look at the prototype and discuss its functionality. Some key highlights covered in the video include:

• The introduction of an investigative agent tasked with analyzing social conversations on climate change events.
• How the agent moves through different stages: assessing conversations, conducting external research, and generating a concise summary.
• The modular design includes nodes for assessment, research, and writing, all linked by key workflows that ensure the agent makes informed decisions.
• Currently, the agent relies on DuckDuckGo for research, but future iterations will introduce additional tools to expand its capabilities.

This prototype demonstrates how AI agents can be leveraged across a data platform to perform a variety of tasks, such as gathering additional context and information from external tools to generate rich, insightful summaries. In this case, the investigative agent goes beyond merely collecting data; it dynamically assesses conversations and conducts targeted research to enrich the narrative. This showcases the versatility of AI agents in automating complex investigative tasks, making them invaluable in extracting deeper insights from raw data.