Anthropic’s Cheap Token Math Breaks When Your Feature Ships

1. 1Analyze your feature's token usage to identify potential areas of cost escalation
2. 2Implement prompt-caching rules to minimize token waste
3. 3Monitor your feature's performance and adjust your token math accordingly
4. 4Consider using alternative pricing models to mitigate the risks of carryover context and tool loops
5. 5Optimize your feature's architecture to reduce token usage and minimize costs

This article is relevant to machine learning engineers, product managers, and entrepreneurs who use Anthropic's API for their SaaS products, as it highlights the potential pitfalls of relying on cheap token math

💡 Carryover context and tool loops can significantly increase token usage and costs, even with cheap token math

💡 Anthropic's cheap token math can break when your feature ships! 🚨 Carryover context and tool loops can erase SaaS margin fast 📉