AI agents aren't confidently wrong because of bad context — they're wrong because of bad data engineering

AI chatbots are often confidently wrong not due to context issues but because of poor data engineering. Despite initial accuracy, as external data like pricing or policies change, the system fails to keep up, leading to significant errors over time. This highlights a critical oversight in how enterprises manage AI systems: the importance of maintaining and updating the underlying data sources. This issue underscores the need for more robust data management practices to ensure AI systems remain reliable and accurate in dynamic environments.