DeepSeek-R1 didn’t just impress with its reasoning capabilities; it also underscored that understanding how an AI “thinks” is central to the user experience when engaging with one. Even Sam Altman weighed in on this and moved quickly to introduce reasoning tokens into the ChatGPT UI.

At Markprompt, we’re tracking the steps an agent takes when thinking and solving a customer support case. We’ve been showing these steps in our dashboard as part of our QA/review features — but clearly, exposing these “thought traces” can also benefit end customers when engaging with our agents in real time.

Why does a transparent, step-by-step thought process matter for AI agents? Three important benefits:

• Clarity – A behind-the-scenes look at how the AI arrives at its conclusions. Users can better trust the system when they see it actively working through details.
• Speed – Even if a final answer takes time, seeing each step of the process confirms it’s not stuck. You can literally watch the system make progress.
• Engagement – There’s something almost magical about watching an AI “think.” It adds an extra layer of excitement and engagement to the support experience.

As AI continues to evolve, more solutions will start exposing their reasoning traces because it’s an incredibly effective way to build trust and the perception of speed. It’s no longer enough to have a powerful engine under the hood—you also need a clear, intuitive, and engaging UI that shows what’s happening along the way.

“Show me your thought process!” used to be what teachers asked their students. Now, it’s time for the AIs to be held accountable too.