Production Patterns for Generative AI APIs

Deploying Generative AI applications at production scale demands careful attention to architecture and security, starting with the realization that large language models are entirely stateless and state must be constructed and passed through (e.g., via a database) to avoid losing conversation context and enable proper scaling. To achieve production readiness and control costs, developers should implement basic patterns like rate limiting for tokens and messages, restrict maximum payload size to prevent exhaustion attacks, and proactively utilize message analytics to monitor abuse and understand user behavior.

Ref: https://www.youtube.com/watch?v=hn2Dn3fLIfg&list=PL03Lrmd9CiGey6VY_mGu_N8uI10FrTtXZ&index=23