Knobs, Dials, and UX: Reimagining Digital Services as Tangible Devices

Summary: Gain a fresh perspective on well-known products and UX influencers by reimagining them in a completely different format: as physical devices. Converting abstract pixels into palpable hardware revitalizes your thinking and is a powerful catalyst for ideation.

Gain a fresh perspective by stepping out of the virtual world and away from the wireframes. (ChatGPT)

Gain a fresh perspective by stepping outside the virtual world. Screens flatten experience; knobs, levers, and indicator lights bring it back to life. Our world as UX professionals is dominated by software and intangible pixels, yet the physical realm still crackles with tactile feedback. By consciously translating digital abstractions into three‑dimensional artifacts, we tap a reservoir of sensory metaphors that conventional wireframes rarely expose.

As an experiment in AI-driven visualization, I used ChatGPT’s native image mode to reinvent famous UX services and influencers as if they were physical products.

For example, here is a machine for collecting e-commerce product ratings:

To be honest, I made these images for fun: to see how far we could stretch the conceit of “software as hardware.” Yet there is genuine rigor behind the whimsy: each sketch operates as a miniature thought experiment that questions what matters most to users once a product’s essence is stripped of swipe gestures and drop‑downs.

Here are the serious sides of the fun exercise:

• Brand perception audit. Running this exercise on an existing brand or influencer offers a reality check on how the Internet’s collective memory (where the AI scrapes its priors) currently frames their reputation. The resulting device often emphasizes legacy achievements over recent pivots. For example, Luke Wroblewski still shows up as the Mobile‑First guy, and my own likeness can’t escape the gravity of those 10 heuristics from 1994. Recognizing this lag lets you course‑correct messaging before your audience ossifies you in amber.

• Feature ideation booster. Visualizing a fledgling concept as a tangible contraption forces you to map invisible interactions onto levers, readouts, and moving parts. This constraint surfaces opportunities for progressive disclosure, haptic feedback, or fail‑safe states that pure UI sketches seldom reveal.

• Cross‑discipline conversation catalyst. Physical metaphors speak the universal language of gears and springs, making it easier to loop in stakeholders and colleagues from other disciplines during discovery workshops. A few of the images from this article dissolve jargon faster than a 40‑slide deck.

I used this prompt:

“Please draw 3 very different images showing retro user interface designs for Dovetail as if it were a physical old-school analogue product and not software. Make sure to include a physical UI for the most iconic features of the software. Avoid showing computer screens or keyboards in your design.” [Optionally, instead of “old-school,” specify an exact time period, such as “1960s” or even “1890s.”]

As always, it’s best practice for AI-driven ideation to ask AI to generate multiple solutions and then pick the one you prefer. Usually, 10 variations is a good number to ask for, but because ChatGPT’s native image model is currently so slow, and because it imposes severe limits on the number of images subscribers can generate daily, I only asked for 3 variations in this prompt.

Four Twists

Here are four ways to extend the exercise to stretch your ideation sessions (or your fun) further:

• Map Entire Workflows, Not Just Apps: Instead of designing a single device, craft a workbench made of interconnected gadgets, each symbolizing a stage in the user journey. Besides imaging multiple devices, think up ways they could be connected.

• Location-Dependent Devices: Specify not only an era (e.g., “1890s”) but also a location (e.g., Victorian London vs. Meiji‑era Tokyo). Cultural context changes material choices, embellishments, and default affordances.

• Random Object Mash‑Ups: Roll two dice, one to select a UX method, the other to choose a household appliance. Combine them into a hybrid. Example: “Card Sorting × Espresso Machine” yields a portafilter that sorts cards by roast strength.

• From Design to Advertising: If this were sold in a 1977 Radio Shack catalog, how would it be promoted? Sketch the hypothetical ad copy, complete with a bold product name and a one‑sentence benefit hook.

With these exercises, you might uncover hidden assumptions, legacy baggage, or unexpected super‑powers that could delight users once they resurface in the digital realm.

A card-sorting espresso machine. (ChatGPT)

Prompt Variations

Here are some additional ideas for alternative prompts to stretch the physical-device analogies even further for various purposes. While I used an AI image tool to make pictures of my devices, you can also have human participants in a workshop create the devices. They could also draw their designs, but for even more fun, have them model the devices in 3D using Play-Doh.

The card-sorting espresso machine modeled with Play-Doh. Realistically, you probably wouldn’t create something quite this nice in a workshop, but that’s OK. (ChatGPT)

• Workshop Icebreaker: “Draw 5 pocket‑size devices from the 1970s that embody heuristic evaluation. Each should fit in a blazer pocket.”

• Feature Discovery: “Design 4 interchangeable front‑panels for a modular onboarding radio. Each panel highlights a different first‑time‑use hurdle.”

• Brand Perception Audit: “Create 3 Victorian engravings of Hotjar if it were a steampunk contraption. Emphasize what the public thinks Hotjar is best at.”

• Accessibility Stress‑Test: “Show 2 tactile‑only versions of Notion as a desktop gadget with oversized braille tiles and audio cues.”

• Rapid Divergence: “Illustrate 10 radically different toaster‑sized artifacts representing Jira, each from a different decade 1950–2020.”

UX Tools and Services Reimagined

Here are some of the more popular UX tools and services as information appliances.

Figma (ChatGPT)

Miro (ChatGPT)

UserTesting (ChatGPT)

SurveyMonkey (ChatGPT)

Dovetail (ChatGPT)

Midjourney (ChatGPT)

ADPList (ChatGPT)

Representing Jakob Nielsen and UX Tigers

Of course, I had to try the reconceptualization game with myself and my website, UX Tigers. Here are the best appliances:

Other UX Experts as Physical Devices

I tried the same exercise for seven of my favorite modern UX experts, to see what visualizations I would get for people who are better known for current hot takes than for classic insights. Besides enjoying these 7 UX leaders converted into old-school devices, I recommend that you follow them on your preferred platform (click the links I’ve provided).

Nikki Anderson posts insightful advice weekly on usability in modern product development. One of her key hot takes was “Insight ≠ impact until it changes a decision,” reminding us that pure research insights are only of academic interest unless we can convert them into product changes by impacting the other stakeholders on the team.

Josh Clark coined the notion of “Sentient Design,” calling for AI-powered, context-aware interfaces that adapt fluidly to users’ needs, and today advises companies on ambient, multimodal, and AI-driven product experiences.

Greg Nudelman has earned a reputation as a seasoned AI-focused designer after leading more than thirty machine-learning projects. He holds twenty-four patents and champions the deep integration of UX craft with data-science practices.

Mani Pande is known for advocating for embedding researchers deeply in complex technical product teams and pairing qualitative work with data-science signals. Qual and quant each describe only part of reality; when they partner on segmentation, dashboards, and experimentation, product teams finally “see the whole elephant.” Pande posts less frequently than most of these influencers, but her articles are always worth reading.

Jeff Sauro, PhD, is the statistician of the UX world. He pioneered widely used methods such as SUS benchmarks, the SUPR-Q survey, and task-level confidence intervals.

Ioana Teleanu. She’s known for the “Honest UX Talks” podcast and for sometimes cranking up the sample sizes when testing new AI products.

Luke Wroblewski gained fame as the author of Mobile First. A former Product Director at Google and Intel, he more recently produced ask.lukew.com — a conversational interface that lets an LLM draw answers from his vast archive of 2,000-plus articles and presentations.