Why Most AI Teams Are Flying Blind on LLM Costs

Standard AI monitoring—logging responses—misses the real cost drivers: hidden reasoning tokens, tool selections, and infrastructure expenses that silently drain budgets in five-figure monthly increments. True AI observability requires instrumenting four critical dimensions: logs, prompts, tool calls, and costs, but most teams track only one or two, leaving them unable to optimize spending or debug agent behavior. As AI operational expenses become material to the bottom line, this observability gap is quickly becoming a business liability rather than a technical nice-to-have.