OpenSpender Spend Cap Ladder
The OpenSpender Spend Cap Ladder is a framework for agencies to structure client AI agent deployments by layering financial controls. Start with a per-request cap, which is the smallest unit of control and prevents a single runaway call from exceeding the client's budget. Next, set a daily cap to smooth out usage spikes across the day, and finally a total cap to bound the entire engagement. Each rung of the ladder corresponds to a specific allowance token configuration in OpenSpender, and agencies can revoke access instantly if a cap is breached. For example, an agency deploying a scheduling agent for a local clinic might set a $0.50 per-request cap, a $20 daily cap, and a $500 total cap, ensuring the client's USDC on Base is never exposed beyond agreed limits. This framework turns OpenSpender's granular controls into a repeatable delivery process, making cost governance a selling point for retainer clients.
By InnovaAI ResearchPublished
“Per-request cap → daily cap → total cap → revoke”
The OpenSpender Spend Cap Ladder is a framework for agencies to structure client AI agent deployments by layering financial controls. Start with a per-request cap, which is the smallest unit of control and prevents a single runaway call from exceeding the client's budget. Next, set a daily cap to smooth out usage spikes across the day, and finally a total cap to bound the entire engagement. Each rung of the ladder corresponds to a specific allowance token configuration in OpenSpender, and agencies can revoke access instantly if a cap is breached. For example, an agency deploying a scheduling agent for a local clinic might set a $0.50 per-request cap, a $20 daily cap, and a $500 total cap, ensuring the client's USDC on Base is never exposed beyond agreed limits. This framework turns OpenSpender's granular controls into a repeatable delivery process, making cost governance a selling point for retainer clients.