In a recent LinkedIn post, Teresa Torres discusses the critical role of user feedback in developing effective AI tools for healthcare professionals. Torres emphasizes that building an AI for physicians required a deep and continuous engagement with the target users, moving beyond initial concepts to practical application.
Torres highlighted the iterative process involved, stating:
Building an AI for healthcare professionals meant staying close to users throughout the process—surveys, low-fidelity prototypes, and working demos to capture real physician feedback.
The Importance of User Proximity in AI Development
As Teresa Torres points out, the development of AI, particularly in specialized fields like healthcare, cannot be done in isolation. The insights gleaned from direct user interaction are invaluable. This close proximity allows developers to understand the nuances of the users’ workflows, pain points, and needs. Torres’s approach, involving surveys, prototypes, and demos, is a testament to the belief that user needs should actively shape the product, rather than being assumed.
Capturing the Nuances of Physician Needs
Torres further elaborates on the specific feedback received from physicians, which revealed a complex set of requirements. While efficiency is paramount in a demanding medical environment, the depth of information and the ability to verify it are equally crucial for trust and effective decision-making.
According to Torres, the feedback indicated a dual need:
Physicians wanted bulleted, summarized responses for speed, but they also valued the ability to deep dive into the sources.
This finding underscores a common challenge in user-centered design: meeting seemingly competing demands. As Torres explains, the solution lies in finding a harmonious balance.
Designing for Both Speed and Depth: The Healio AI Case Study
The successful integration of user feedback led to the specific design choices made for Healio AI. Torres frames this outcome as a direct result of listening to and acting upon user input.
In Teresa Torres’s view, this balance is not just a feature but the core of the product’s value proposition:
It’s the balance between efficiency and thoroughness that shaped Healio AI.
This principle of balancing efficiency with thoroughness is a key takeaway for anyone developing AI tools, especially in sectors where accuracy and speed are both critical. Torres’s insights suggest that by actively involving end-users and iteratively refining the product based on their feedback, developers can create AI solutions that are not only technologically advanced but also genuinely useful and adopted by the professionals they are intended to serve. The success of Healio AI, as described by Torres, serves as a compelling case study for user-centric development in the age of artificial intelligence.
📝 About This Content
This article is based on insights shared by Teresa Torres on LinkedIn.
📅 Originally posted on January 25, 2026 | View original post on LinkedIn →