Most AI projects have a straightforward logic—complete tasks, output results, move on to the next. Efficiency is paramount. But is this approach really enough?

Some teams are beginning to consider another dimension: what happens after the task is completed? Where exactly is the gap in user experience depth?

This difference in perspective may seem subtle, but from the user's point of view, the impact is significant. Are you interacting with a tool that can provide answers, or collaborating with an intelligent agent that truly understands your needs throughout the entire process? The experience is completely different. The former is a tool, the latter is a partner. This is also why some innovative projects are starting to redefine the role of AI agents in the Web3 ecosystem—not just focusing on execution efficiency, but on establishing ongoing, meaningful interactions.