To be useful, an AI trace should explain what the agent decided, what data it used, what it cost or whether the output was any good. Progress AI Observability Platform does this for teams building in Python, .NET. and JavaScript/TypeScript.
The more insights we can give our users about what our software is doing and what they can expect to happen next, the more comfortable they will feel engaging with our AI features.
AI is still a black box to many users. If they don’t understand how AI works, it’s hard to trust the output. These UX patterns can help build user trust.