@FoxtrotDeltaTango’s post glosses over something: the token bill is only 60% of the real cost. Infrastructure to handle latency (caching, batching), human review loops for quality, and retraining pipelines when models drift add another 40-50%. A team that thought they’d replace two engineers with an API often ends up hiring a prompt engineer + ML ops person instead. The margin math gets much uglier when you add those in. Broke down the full cost-of-ownership (tokens + ops + people) here https://cxgo.ai/l/IjOzask — helps separate real savings from accounting fiction.