Memory is Key for Long-Horizon Agents: 15 LLMs Manage a Football Club for 20 Years
dair_ai · x · 2026-08-30
A study tested long-horizon memory and planning by having LLM agents manage a football club for 20 in-game seasons (approx. 340-400 decision stops).
Key Findings:
- All 15 frontier models survived the entire horizon, while most scripted baselines failed.
- Scale, price, vendor, or token spend did not predict rankings; order only settled late in the run.
- Top models exhibited specific managerial behaviors: cutting slow-payoff investments near the end and opening contract renewals well before deadlines.
- Two universal failures were found: no model learned the market's hidden prices from rejected bids, and self-managed memory also failed.
The research highlights that memory/recall is critical for breaking long-horizon agent bottlenecks.
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