The primary use case for AI lab APIs is software engineering, which is by far the most token-hungry application. This observation is a current point in time, alongside discussions on token budgeting, Meta's compute strategy, and Anthropic's profit margins.
Coding workloads are the binding variable for AI API revenue and token consumption, directly influencing compute strategy and profitability for frontier labs.