• CALM from WeChat groups tokens into a single continuous vector. Fewer steps, less compute, fewer errors. The model on page 1 of the paper shows how it collapses 4 tokens into 1 vector while keeping 99.9% reconstruction accuracy. • Anthropic’s “Effective Harnesses” shows why long-running agents break down. Their fix: an initializer agent, a coding agent that makes one clean change per run, and progress logs so nothing resets. • Cognizant’s “Million-Step” work tackles error snowballing. Break ta

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