The Token Economy

AI usage is expanding from simple assistants to heavier agentic workflows, coding assistants, personal coworkers, and workflow automation, which is impacting both the price of frontier models and the number of tokens used per output. Each retrieval, tool call, intermediate step, and reasoning loop adds up.

While many attribute rising token costs to the price of the models themselves, the underlying enterprise AI architecture also affects these costs. 

Watch this webinar for a walkthrough of how context, routing, continual learning, and harness design all impact the usage of tokens and what you can do about it. 

What you’ll learn

• Why token efficiency is an architecture problem, not only a model pricing problem.
• How higher-quality context and indexed retrieval reduce unnecessary reasoning and improve results.
• How to design routing, continual learning, and harnesses if you want AI systems to scale sustainably.