Muse dodged every trap in this billing ticket
A billing ticket resolution task was used to benchmark agentic AI performance, and Muse excelled by successfully navigating multiple challenges including account linking errors, duplicate refund issues, and prompt injection attempts. The agent demonstrated superior performance by investigating thoroughly, fixing the account link, issuing the correct refund, updating the plan, and marking the ticket as resolved.
Summary
The speaker describes a benchmarking task designed to evaluate agentic AI capabilities using computer use in an admin app environment. The task involves resolving a billing ticket that intentionally contains multiple obstacles and edge cases to test agent robustness. The primary challenges built into the task include: an incorrect account link that the agent must identify and correct, a complex refund scenario involving a duplicate charge with an unusual amount requiring careful analysis, and a prompt injection attempt embedded in the task instructions. Muse performed exceptionally well on this benchmark, demonstrating strong investigative capabilities by properly identifying the account linking issue. The agent then systematically addressed the refund problem by recognizing the duplicate nature of the charge and calculating the correct refund amount. Additionally, Muse made a plan change and replied to mark the ticket as solved. The speaker emphasizes that Muse navigated all of the deliberately planted failure points and edge cases in the benchmark more effectively than competing agents, doing so in a clear and methodical manner.
Key Insights
- A good agentic task for benchmarking should include multiple intentional failure points and edge cases such as account linking errors, duplicate transactions, and prompt injection attempts to comprehensively test agent capabilities.
- Muse demonstrated superior performance by investigating the billing ticket thoroughly, which enabled it to identify and fix the account linking issue correctly.
- Muse correctly handled a complex refund scenario by recognizing that the refund amount was unusual because it was a duplicate charge, showing it could work through ambiguous and complex financial situations.
- Muse successfully completed all planted test obstacles in the billing ticket task and performed better than all other agents tested, following a clear and methodical process.
- The billing ticket task required agents to make multiple types of corrections and decisions including account corrections, refund calculations, plan changes, and ticket status updates, indicating comprehensive agentic capability.
Topics
Transcript
[0:00] And so let's talk about what a good agentic task for benchmarking looks like and why Muse did really well. So we run this task where you use computer use and you have to resolve a billing ticket in an admin app and there's a couple things that the agent has to navigate. It's linked to the wrong account so it has to like identify and find the right account. The refund amount is weird and there's a duplicate so you have to kind of like work around that. And there's a prompt injection task in the instructions and it did a really good job. It investigated. It fixed the link [0:31] for the right customer. It issued the…
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