SELF IMPROVING AGENT WITH DYNAMIC CONTEXT AND CONTINUOUS LEARNING

Summary from the TLDR AI newsletter

This guide walks readers through how to build a self-improving Text-to-SQL agent using dynamic context and 'poor-man's continuous learning'. The agent answers questions by retrieving data from a knowledge base. It learns from successful runs by adding to the knowledge base, creating a self-improving feedback loop. A video that shows the agent in action is available at the end of the article.