Abstract
Tan et al. report that longer, parallel, and communicating searches “all … eventually plateau as the agents accumulate history” and that “the key to scaling discovery further is to forget”: discard every agent’s session and the candidate history, and restart from the best candidate. They never test resetting sessions while keeping candidates; we introduce a shared verified archive that does. It bounds conversations and keeps every evaluator-verified attempt with its source and cited tools, so different agents’ improvements compose. On Anthropic’s performance take-home, where their forgetting team reaches 1,077 cycles and CORAL 1,103 with other models, four Claude Opus 5.5 agents on the archive reach a median of 914 [913, 916] cycles over 3 seeds in 8 hours, against 948 for a CORAL-faithful team and 946 for the best of four isolated agents on matched machines. Both baselines’ medians stall at 946–956 cycles after 3 hours, where several CORAL-faithful agents concluded about 951 was near the floor and 7 of 12 fell into a no-op resume loop, which we name the false floor; from 2.75 hours the archive’s worst seed stays ahead of both baselines’ best seeds. On open problems, a team built 60 of its first 98 new bests on another agent’s attempt or tool and, in one run per arm, led every arm at 8 hours on Erdős’s minimum overlap problem, the first autocorrelation inequality, and AHC026.
Code and data
Per-seed anytime curves
evidence/analyst_budget_curve.csvTake-home best-so-far cycles per attempt for every seed of the main comparison, the original run, the added seed and the c2d-highcpu-56 rerun70 KBfigures/hero_data.csvFigure 1 data: the nine main-comparison take-home runs and the open-problem arms, every best-so-far step66 KBevidence/curves_matched.csvOpen-problem best-so-far for every arm and problem on a 0.25-hour grid of matched working hours435 KBkx/results/curves-completed.csvTake-home best-so-far curves for the model-change, mixed-family, seeded, open-weight and single-agent runs, with the agent and model of each new best18 KBkx/results/analysis-completed.txtBest-so-far cycles at 15 to 480 minutes for each take-home run in curves-completed.csv, including the mixed-family, seeded, open-weight and model-change runs2.2 KB
The take-home task prompt
kx/harness/task_prompt.mdTake-home task prompt every agent received1.6 KB
C₁ and Erdős constructions with their exact verifiers
anc/ac1-SX-A43.txt.xzon the new-constructions pageC1 construction at 3.97 working hours, 262,144 heights, bound 1.50274043592276697641…1.3 MBanc/erdos-SX-A51.txton the new-constructions pageErdős minimum-overlap construction A51, 3,584 cells, bound 0.38085673888331742055…56 KBanc/verifier/audits_crossfamily/exact.pyon the new-constructions pageIndependent exact checker for C1 and Erdős (GMP carry-free packed convolution, exact fractions)8.2 KBanc/verifier/verify_all.pyon the new-constructions pageRuns every checker on the construction files and compares with the papers' values6.1 KBanc/SHA256SUMSon the new-constructions pagesha256 of every construction and checker file40 KBanc/README.txton the new-constructions pageFile formats, exact values and how to run the checkers6.1 KB
Cite
@misc{cumes2026scaling,
title = {{Scaling Discovery Does Not Require Forgetting: Verified Shared Archives Break the Multi-Agent Plateau on Anthropic's Performance Take-Home}},
author = {Cumes, Lindell S.},
year = {2026},
url = {https://durableintel.com/paper-societies-horizon}
}