Text chunking and context overlap for product managers

Understanding text chunking is essential when your search product gives inaccurate answers. If your assistant acts dumb, you need to know why the model forgets things so you can fix the product. When you feed a massive document into a large language model without breaking it down, the system gets confused and forgets key facts. This lesson uses a simple index card analogy to explain how tech teams slice large texts into bite-sized pieces at logical breaks like chapters or headings. However, cutting text creates a context bleeding problem where the system loses the thread across chunks. You will learn how to talk to your engineers about chunk size and edge overlap to fix this issue. Overlap repeats a few words across cards, turning a messy data dump into a smart filing system that actually helps your users. In this lesson: - Why large documents overwhelm language models - The index card analogy for text slicing - How context bleeding breaks search - Discussing chunk size and overlap with engineers U2xAI Academy - AI skills for product managers.