Ask HN：基於代幣的定價是否讓 AI 難以投入生產？

I’ve noticed a recurring theme in many threads here: AI is powerful, but once you move past demos, token-based pricing becomes expensive and hard to reason about.

We ran into this problem ourselves while building AI-powered systems. Predicting costs, budgeting usage, and experimenting safely all got harder as workloads grew. So we built a small AI inference platform focused on lower and more predictable costs, optimizing for affordability rather than chasing the latest model.

This is still early, and I’m mainly posting to learn from others here. For people running AI in production, what’s been the hardest part to manage so far? Cost, predictability, performance, or something else?

I’d really appreciate any insights or experiences.