Agent context, which involves using Claude to generate text based on previous conversations or outputs, can create a feedback loop that increases the input size with each iteration. By round 5, the input can be 5 times larger than the initial prompt, leading to a significant increase in costs.
For example, a small SaaS team (case-002) using Claude for customer support auto-replies saw their costs drop from $1840 to $287 after optimizing their usage with AIUsage.ai. Similarly, an agency (case-004) using Claude for agentic workflows saw their costs decrease from $2490 to $498. These cases demonstrate the potential for significant cost savings when optimizing Claude usage.
To understand the impact of agent context on your own budget, try pasting your last 30 days of Claude usage into aiusage.ai to see the potential savings. You may be surprised at the opportunities for cost reduction, as seen in cases like case-003, where a solo freelancer saved 81% on their Claude bill. By auditing your usage and optimizing your workflows, you can minimize the budget blowout caused by agent context and make the most of Claude's capabilities.