Why your AI pipeline costs 10x more after the demo

TL;DR

AI applications can incur unexpectedly high costs due to inefficient token usage, not just flawed models. Optimizing token consumption is crucial for reducing operational expenses.

Key Takeaways

• Analyze token usage patterns to identify inefficiencies.
• Implement prompt caching to reduce repeated token costs.
• Use semantic caching to handle paraphrased queries efficiently.
• Route simple tasks to lightweight models to cut expenses.