YC startup EdotEnv finds more reasoning budget doesn't help LLM agents trade better — they freeze under losses

YC S26 startup EdotEnv reports that state-of-the-art LLM agents in its real-market reinforcement learning environments gain no performance from higher reasoning effort and stop trading when losing money rather than adapting. These failure modes would not surface in synthetic benchmarks, where inaction is rarely penalized.