As autonomous agents become primary API consumers, a subtle cost problem emerges. Traditional JSON serialization, optimized for human readability and broad compatibility, incurs significant token overhead when feeding data to language models. Every structural character (braces, quotes, colons, commas) gets tokenized and charged separately.
The issue compounds at scale. When agents query APIs hundreds of thousands of times daily, JSON’s verbosity translates directly to infrastructure costs. Organizations running agent-heavy workloads are discovering that a substantial portion of their LLM token consumption is due to serialization overhead, not actual data transfer.