TokenOps: Managing Costs and Value in Agentic Systems

Gareth Bland explains how enterprises can make strategic decisions about token spending in agent-based systems. The discussion connects token costs and context caching with measures of agent efficiency and the value delivered by software features.

- Token cost dynamics: input, output, caching, and the effect of longer agent loops
- Agent efficiency measures: autonomous completion, production adoption, and user value
- Feature investment: using an S-curve to distinguish early development, leverage, and saturation

For enterprise teams building agentic software, this provides a framework for tracking token use and assessing where further investment may create value. It focuses on measurement and strategic decision-making rather than implementation instructions or a specific vendor’s tools.