@a1zhang: Good harness designs can get around extreme token costs when information is structured. There's really no need to feed …
Summary
A discussion on how harness designs can reduce token costs by structuring information instead of feeding everything into a language model's context, citing an example of an RLM agent processing many lines of logs with few active tokens.
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Cached at: 06/15/26, 11:08 PM
Good harness designs can get around extreme token costs when information is structured. There’s really no need to feed everything into a language model’s context all the time.
We’ve conflated naively throwing everything into context with bitter-lesson pilled scaling for too long. A good harness goes a long way!
diego 🧞♂️ (@diblacksmith): My RLM agent can effortlessly process ~80k lines of service logs from CloudWatch
in a single go. that’s worth like 8 million tokens.
The cool part is, after 53 steps, it had spent only 32k “active” tokens* (not through the full 8MM yet atp, more like half).
That’s nothing for
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