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The study shows that per-token list price is an unreliable proxy for actual LLM operating cost, with thinking-token variance and run-to-run randomness making true COGS unpredictable — a direct risk for any product built on flat-fee pricing over variable model usage.
The tool directly addresses a concrete bottleneck in agentic coding loops — context budgets consumed by redundant file re-reads — by fitting entire repositories into context that previously only held a fraction of the codebase.
Developers using Gemini 2.5 Flash or Pro must explicitly control the thinking budget to avoid silent truncation; without this knowledge, production endpoints will return incomplete responses with no error message, breaking downstream applications.