Token optimization
3 videos across 3 channels
A practical look at squeezing cost and speed from AI prompts by trimming token use. From a “Caveman” technique that drastically cuts output tokens in Claude code, to strategies for extending Claude’s run time through planning, configuration, and model choices, the coverage also explores converting HTML to markdown in real time to boost context-window efficiency. Together, these videos offer actionable tips for reducing both input and output tokens without sacrificing results.
No way this actually works
The video presents Caveman as a simple method to drastically cut output tokens when using Claude code, arguing it can sa
00:06:58
The Claude Code Limits Problem Is Finally Solved
The video explains why Claude code users hit token limits quickly and outlines practical strategies to make Claude last
00:13:24