Don't Stop Listenin': What Teaching UX Design Taught Me About Leading Robotics Teams

"An engineering listening to stakeholders while creating a robot" image generated by OpenAI's DALL-E 2, October 22, 2025.

The fastest way to slow a team down is to start building too soon.

Back when I taught UX and HCI, my students would show up excited and ready to pick tools. “Are we using Figma? What’s the dev stack?” Great energy, wrong starting point. The real unlock wasn’t software, it was conversations. We spent weeks learning how to talk to people, run semi-structured interviews and turn messy, human stories into clear design choices. By the time we opened any design tool, we already knew what mattered and why.

Leading engineering teams in robotics, I’ve learned the exact same lesson applies. Brilliant builders love to ship. But the work that makes robots useful and safe in real environments doesn’t start with parts or code. It starts with people.

1) Bring the user into the room, even when they aren’t there

In health settings, a “small” decision like robot speed can have big implications. Faster is technically impressive; safer is what clinicians actually need. When we loop frontline perspectives into daily stand-ups, it is all about derisking resource burn. Human-centered design is a safety feature. It keeps us aligned to benefits that will actually be realized in practice, not just imagined on a whiteboard. Research backs this: HCD in healthcare improves fit-for-use and benefit realization when it is embedded early and iteratively.

How to make this practical:

• Appoint a “voice of the user” in every team, responsible for summarizing 2–3 real observations from the field.

• Replace vague “the robot will move at 3 mph” with specific statements: “The charge nurse worries about liability at the patient elevators at 8 am.”

• Convert each observation into an acceptance test.

2) Scope like your success depends on it, because it does

Users ask for ten features. Your budget supports two. The habit from HCI studio that still serves me best is obsessing on measures of success in order to control scope. Prioritization isn’t about saying no to customers, it’s about saying yes to outcomes. In software engineering literature, effective requirements prioritization consistently correlates with value delivery and time-to-market, especially when teams rank by impact, confidence and effort.

A simple pattern we use:

• List pains, not features. “Shift handover confusion” is a pain; “LED color picker” is a feature.

• Score by outcome potential. If solving one pain unlocks 80% of the perceived value, ship that first.

• Design for graceful incompleteness. A product that solves one critical job well gets adopted, even if the rest is still rough.

3) Treat interviews as engineering tools

Interviews aren’t just for researchers. Semi-structured interviews are efficient, repeatable and surprisingly compatible with engineering culture. They surface constraints you won’t see in logs or metrics. There’s robust evidence in health and HCI contexts that this method yields actionable, nuanced insight when done systematically.

Start simple:

• Ask for a story, not an opinion: “Tell me about the last time the robot made your shift harder.”

• Follow the friction: “What did you do next?” “What else was happening?”

• Close with prioritization: “If we fixed one thing this month, what should it be?”

Log these notes in your issue tracker with tags (e.g., safety, workflow, training) so they shape backlog decisions, not just slide decks.

4) Safety, trust and flow are features

In hospitals, success is not just “does it work,” it’s “is it safe, does it fit the workflow and does it improve lives?” State-of-the-art reviews in human-robot collaboration emphasize safety control, predictable behavior and clear affordances as prerequisites for acceptance.

Design implications:

• Prioritize predictable motion over flashy speed; predictable wins trust.

• Signal intent clearly with lights, sounds and pathing that nurses can anticipate.

• Build training and recovery paths right into the UX. If a fault occurs at 2 am, the robot should guide the user to a safe reset without a manual.

5) Curiosity and humility scale better than heroics

The best engineers I’ve worked with are relentlessly curious. They don’t just close tickets, they open questions. They assume the system includes people and moments of stress, not just software and hardware. That posture builds better robots because it creates faster learning loops and fewer “surprises” in deployment. The literature on empathy in engineering design links empathic practices with better translation of stakeholder perspectives into solutions that actually get used.

A simple operating cadence

• Monday: Share three fresh stakeholder conversations, including metrics used to measure success. Convert at least one into a testable hypothesis.

• Empathy: Run a 20-minute “friction audit” on the top workflow. Ask, “Where do we cause extra steps?”

• Friday: Demo the smallest thing that reduces real risk or effort. Celebrate removal of complexity as much as addition of features.

In my teaching days, students thought the magic was in the tool. In robotics, teams often think the magic is in the mechatronics. The real magic is earlier and quieter: listening carefully enough to know what not to build.

Don't Stop Listenin'. That’s how you ship technology people don’t just admire, they rely on.

Follow me here, or follow Rovex Technologies Corporation, as we continue to share how thoughtful design in hospital logistics can restore time, energy, and focus back to the people delivering care.

#HumanCenteredDesign #Robotics #HealthcareInnovation #ProductLeadership

References:

1.     Melles M, Albayrak A, Goossens R. Innovating health care: key characteristics of human-centered design. Int J Qual Health Care.2021;33(Suppl_1):37–44. doi:10.1093/intqhc/mzaa127.

2.     DeJonckheere M, Vaughn LM. Semistructured interviewing in primary care research: a balance of relationship and rigour. Fam Med Community Health. 2019;7(2):e000057. doi:10.1136/fmch-2018-000057.

3.     Haney JM, Liang C-J. A literature review on safety perception and trust during human–robot interaction with autonomous mobile robots that apply to industrial environments. IISE Trans Occup Ergon Hum Factors. 2024;12(1–2):6–27. doi:10.1080/24725838.2023.2283537.

image prompt: "generate an image for an article titled "Don't Stop Listening'. Make it more about people being happy about what's being made instead of focusing on the tech. Make the image more about listening to people while engineering a robot at the same time. Make the image in landscape. remove headphones. Make the center person east asian."