Put your LLM output under test, or every prompt tweak is a silent regression
In our platform, we run a multi-step AI agent that generates content for customers in the sports world. The agent is never fixed: we change the underlying models, reword prompts, restructure workflow steps, adjust the agent logic. Any of those can quietly make the output worse, and for a while the only safeguard was a human, reading generated content and forming an opinion. That doesn’t scale at all, highly subjective and misses slow drift completely. ...