AI Token Cost Optimization: From Pilot to Production Without Sticker Shock

Token costs scale with use; cost discipline is operational hygiene, not premature optimization, once production volumes are non-trivial.

What AI does well here

• Implement prompt caching (where supported) — repeated context becomes nearly free
• Route by complexity — small/cheap models for routine, big models for hard cases
• Monitor cost-per-use case so growing use cases get attention before they become budget surprises
• Optimize prompt length — long system prompts add cost on every call

What AI cannot do

• Eliminate token costs — they're real and scale with usage
• Substitute optimization for use-case prioritization — sometimes the right answer is to kill an expensive use case
• Predict 12-month costs accurately when usage patterns are still emerging