RLCR study: agent orgs scale much faster in open-ended environments
rosstaylor90 · x · 2026-10-23
The RLCR team classified training environments as open-ended (many solutions) vs procedural (fixed spec) and plotted scaling exponents for code output: output scales far faster in open-ended environments — agents benefit from exploring and trying more things. The thread context also notes that agent organizations start as a wheel structure (with an imposed CEO agent) but hierarchies with 'Lead x' roles emerge as training progresses, matching organizational-economics predictions about communication costs and information aggregation.
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