{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"Machine Learning Tech Brief By HackerNoon","title":"Your OpenClaw Bill Is Bleeding Tokens. Here’s What We Measured — and How to Fix It.","html":"<iframe width=\"100%\" height=\"180\" frameborder=\"no\" scrolling=\"no\" seamless src=\"https://share.transistor.fm/e/6f212388\"></iframe>","width":"100%","height":180,"duration":848,"description":"\n        This story was originally published on HackerNoon at: https://hackernoon.com/your-openclaw-bill-is-bleeding-tokens-heres-what-we-measured-and-how-to-fix-it.\n             Memory bloat, compaction loss, and a retrieval-first path: ~32% less token spend on the AppWorld dev split — without dumbing the agent down. \n            Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning.\n            You can also check exclusive content about #ai, #openclaw, #agent-memory, #context-engineering, #vector-database, #tokenization, #openclaw-bill, #save-ai-token-costs,  and more.\n            \n            \n            This story was written by: @jinglan0379. Learn more about this writer by checking @jinglan0379's about page,\n            and for more stories, please visit hackernoon.com.\n            \n                \n                \n                Memory bloat, compaction loss, and a retrieval-first path: ~32% less token spend on the AppWorld dev split — without dumbing the agent down.\n        \n        ","thumbnail_url":"https://img.transistorcdn.com/KyA01h2FD2insgk-wX_xzV6vbJnTNl2BvPYVL-XaI9A/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9zaG93/LzQxMjcyLzE2ODM1/ODI0ODgtYXJ0d29y/ay5qcGc.webp","thumbnail_width":300,"thumbnail_height":300}