The Aiven blog post by Jay Miller discusses how PostgreSQL Anonymizer, a data masking extension, can help securely share data with large language models (LLMs) by anonymizing personally identifiable information (PII) using static and dynamic masking strategies, thereby minimizing the risk of data breaches. The post emphasizes the importance of safeguarding user information when utilizing LLMs, as AI companies often cache and persist data, making it vulnerable to exploitation. By employing PostgreSQL Anonymizer, organizations can enforce the principle of least privilege, ensuring that LLMs and other users interact only with anonymized data, thus reducing exposure to sensitive information. The blog also provides a detailed walkthrough on implementing both static and dynamic masking techniques, illustrating how these strategies can be applied to a business-to-business ecommerce platform's customer data to prevent unauthorized access and maintain data privacy while leveraging AI for marketing and development tasks.