Using ChatGPT for input validation in cloud-native apps presents several significant challenges, primarily concerning accuracy and reliability, as LLMs can hallucinate or misinterpret complex validation rules. This can lead to security vulnerabilities or incorrect data processing, particularly when dealing with domain-specific or strict API schemas that ChatGPT might fail to comprehend perfectly. Another major hurdle is the performance overhead and increased latency introduced by external API calls to the LLM, which directly impacts the responsiveness of high-traffic cloud-native services, alongside potential escalating operational costs. Furthermore, maintaining and debugging LLM-generated validation logic can be exceptionally complex and opaque, making it difficult to ensure the system evolves correctly with changing business requirements. Finally, inherent challenges related to trustworthiness and data privacy arise, as sending potentially sensitive user input to a third-party model raises concerns about data leakage and compliance with regulations. More details: https://image.google.st/url?rct=i&sa=t&url=https://abcname.com.ua/