How I Save 80% of Neural Network Context When Working with Logs

The Problem I actively use AI to debug issues in my project development. I ran into an annoying problem: logs typically contain massive amounts of repetitive information. This eats up a huge chunk of input context without adding any real value. Here's a typical scenario: I notice a bug, copy 1000 lines of logs, and paste them into the chat. The neural network starts parsing the text, but out of those 1000 lines, only about 300 are actually unique.