{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"AI News Today | Julian Goldie Podcast","title":"Claude: Save 82% Tokens with RTK!","html":"","width":"100%","height":180,"duration":567,"description":"RTK Token Savings: Cut LLM Token Usage by ~80% (Plus Ponytail, Headroom & Caveman)\nThe script explains testing RTK, an open-source filter that sits between an AI agent and the shell to remove padding and duplicate output from common commands, reducing token usage while keeping results the same. The presenter reports 82.9% average token savings in their tests, cites RTK’s README claim of 60–90% savings, and notes minimal added latency (~14 ms). An example shows swapping git diff to an RTK version that strips repeated headers and unchanged lines, cutting output from 373,000 to 29,000 characters (92% less) while saving full unshortened output to a file if needed. RTK is described as easy to install on Linux/macOS, small (6.6 MB), and capable of shortening outputs for about 100 everyday commands. The script also covers stacking RTK with other open-source tools—Ponytail, Headroom, and Caveman—to further minimize tokens, and promotes the Agent OS setup and AI Profit Bot community.\n00:00 RTK Token Savings Intro\n00:55 How RTK Works\n01:47 Real Test Results\n02:28 Step by Step Example\n04:42 Testing Method\n05:07 Install and Command Support\n05:38 Does It Lose Info\n05:51 Token Minimizer Stack\n06:36 Caveman Mode Demo\n07:39 Fable 5 Efficiency Wins\n08:23 Agent OS and Community\n09:25 Wrap Up","thumbnail_url":"https://img.transistorcdn.com/Tp0JSUlyiAe2ran44b13cjk4ImQYS1QEMKCAa9Q7go0/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9lNTYz/NGQxMTU2ZTM1MzU5/MDNiYjcwZjJmYTY5/ODJmOS5qcGc.webp","thumbnail_width":300,"thumbnail_height":300}