Our inboxes contain dozens (if not hundreds) of newsletters we subscribed to during moments of curiosity, but we seldom read most of them. Manually unsubscribing is tedious: open each email, scroll to the bottom, click unsubscribe, confirm … repeat 50+ times.

This post covers a personal project developing an AI agent using the ReAct pattern to analyse newsletters I have subscribed to and recommend the ones to unsubscribe based on my reading behaviour.

Developing custom Named Entity Recognition (NER) models for specific use cases depend on the availability of high-quality annotated datasets, which can be expensive. As someone who has worked on several real-world use cases, I know the challenges all too well. This post describes a few real-world challenges, a solution which reduces human effort whilst maintaining high quality, and code snippets for the solution.