Building AI-Powered UX
Last Updated: March 15, 2026
Before diving into patterns, it is worth understanding why AI-powered interfaces are fundamentally different from traditional software UIs.
In a standard web app, when a user clicks a button, the system does something deterministic. It saves a record, fetches a list, runs a calculation. The operation takes a predictable amount of time (usually under a second), and the result is either correct or it is a bug. Users have decades of muscle memory for this interaction model.
AI flips several of these assumptions:
- Latency is variable and high. A simple query might take 2 seconds. A complex one might take 15. The user cannot predict which they will get.
- Results are non-deterministic. The same question can produce different answers. This is a feature, not a bug, but it means users need ways to regenerate or steer.
- Correctness is uncertain. The AI might be right, might be partially right, or might be confidently wrong. Users need tools to verify.
- The system has stages. A RAG pipeline searches documents, ranks results, and then generates. Each stage can fail independently.
These differences demand new UX patterns. You cannot just slap a loading spinner on an LLM call and call it done.
That brings us to the first and most impactful pattern: streaming.