Why Heuristic Detectors Beat LLMs at Finding Agent Failures

1. 1Build a set of core rule-based detectors to identify failures in AI agent traces
2. 2Run the detectors on the TRAIL benchmark to evaluate their accuracy
3. 3Configure the detectors to combine with a single Sonnet call for attribution on the Who&When benchmark
4. 4Test the performance of the detectors against LLMs like GPT-5.4 Mini
5. 5Apply the heuristic detectors to real-world AI agent applications to improve their reliability

AI engineers and researchers can benefit from using heuristic detectors to improve the reliability of their AI agents, while product managers can utilize this approach to enhance the overall performance of their AI-powered products

💡 Heuristic detectors can outperform LLMs in identifying agent failures due to their ability to provide zero false positives and reduce costs

Heuristic detectors beat LLMs at finding agent failures with 60.1% accuracy and zero false positives! #AI #LLMs