How to keep LLM spend predictable

Mary, a senior engineer at a mid-size SaaS company, faced a significant unexpected expense when her team inadvertently incurred a $15,000 monthly bill due to a configuration change that routed their SRE agent's operations through a costly API without budget controls. This situation highlights a broader issue where many organizations lack comprehensive visibility over their AI-related costs, leading to surprise invoices when token and cloud computing budgets are exceeded. Barndoor, a tool designed to manage and optimize AI expenditures, could have mitigated this by implementing budget controls, rate limits, and appropriate model access policies. By setting budget ceilings, enforcing rate limits, and choosing cost-effective models, Barndoor allows organizations to manage AI costs proactively, preventing overspending and surprise bills.