LLM token consumption estimation for autonomous research workflows

The user's inquiry about token consumption for overnight autonomous research highlights a critical cost-of-ownership concern for LLM-powered agents. Unpredictable or high token usage directly impacts operational budgets, especially for long-running tasks. For a system like ARIS, which promises "low-cost" and "autonomous ML research," providing clear estimates or cost management features is essential. Lack of transparency here creates a barrier to adoption, as users cannot accurately forecast expenses. This indicates a need for better cost visibility and control mechanisms to align with the product's value proposition.