LLM in Product Search: Failures and Lessons Learned
Challenges and lessons learned from developing a natural language product search engine.
While developing a natural language product search engine, the language understanding performed well, but numerous issues arose in other areas. Price filters failed, the LLM generated plausible category IDs, and queries returned incorrect results. These experiences provided critical lessons for engineers in system design.
This synthesis was produced from its source by AI; there is no human editor or manual review step. How we work