Six Real-World Bugs Found After Deploying AI Compliance Agent on Qwen Cloud

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A developer building an AI-powered environmental compliance tool for Peru's regulator OEFA discovered six critical bugs that only emerged when testing with live Qwen qwen-plus model output on Alibaba Cloud. The system, designed to answer queries about company sanctions and draft regulatory reports, passed all 315 offline tests but broke in production due to unexpected model output patterns. Key issues included the model returning status labels like 'success' or 'done' instead of the expected 'completed' or 'failed', causing strict parsers to reject otherwise valid responses. Other failures involved the planner generating empty task lists, citation fields arriving with mismatched names or wrong-language values, and approval steps triggering before required report drafts existed. The developer resolved each issue through tolerant preprocessors, alias mapping, per-item validation, and honest fallback messages, concluding that offline tests alone cannot catch failures rooted in live model output distribution.

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