Reinforcement learning RL for large language model LLM agents looks attractive on paper, but in practice it breaks on cost, infrastructure and reward noise. Training an agent that clicks through web pages or completes multi step tool use can easily need tens of thousands of real interactions, each slow, brittle and hard to reset. Meta’s
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