Cutting Token Consumption Without Losing Output Quality

The problem

Running AI workflows at any real scale - agentic loops, long context, repeated calls - can hit token limits really fast, and it’s rarely obvious where the waste is actually coming from.

The solution

A deep dive into a skill provided by Microsoft that converts data sources into .MD files, resulting in more efficient token consumption.

What you'll walk away with

• A discussion of where token waste typically hides
• A live before/after token comparison through a Chrome extension
• Instructions on how to install the skill on any AI Assistant