The New Science of Creating Products People Love

Introduction: Ever felt like your users have minds of their own? One minute they’re gliding through your app, the next they’re stuck or veering off in unexpected directions. Traditional UX tools like funnels and heatmaps only show where users went – after the fact – but not why they behaved that way. Enter Quantum-Fluidic Interaction Theory (QFIT), a new framework that blends quantum physics and fluid dynamics with behavioral science to model and predict user behavior . It sounds heady, but its goal is simple: to help us design products that flow so naturally, using them feels almost effortless and lovable. Instead of seeing user journeys as linear steps, QFIT invites us to see them as dynamic flows with currents, eddies, friction, and energy. In this article, we’ll demystify QFIT’s key concepts in plain language and show how they explain real design challenges. From probabilistic intent (why users seem undecided until they click) to cognitive viscosity (the friction slowing them down), and from excitation fields (what energizes users to act) to entropy (chaos in the UX) and flow visualization (mapping the currents of behavior) – we’ll explore each with vivid metaphors and real examples from companies like Airbnb, Duolingo, Notion, and Apple. By the end, you’ll see how this “new science” of UX can bridge deep behavioral insights with the practical art of designing products people love.

Probabilistic Intent Vectors: Embracing Fuzzy User Goals

Imagine every user on your product is like an electron in a cloud – they have several potential actions they might take next, but you can’t be sure which until it happens. In QFIT, this is the idea of probabilistic intent. Instead of assuming users have a single, crystal-clear goal, we acknowledge they carry a bundle of possible intents at any moment . It’s akin to a traveler at a crossroads, considering multiple paths. Their “intent vector” isn’t pointing firmly in one direction; it’s a weighted mix of directions, each with a certain probability. Only when something in the interface nudges them or they make a choice does that cloud of possibilities collapse into a decision, just as observing a quantum particle forces it into a definite state . In practical terms, your user might simultaneously be curious about pricing, interested in reading reviews, or tempted to click the shiny banner – until one option wins out.

This may sound abstract, but it explains a lot of modern UX behavior. Take Airbnb for example. The team at Airbnb realized that not all travelers know exactly where or when they want to go. Often, people just have a fuzzy intent like “I’d love an affordable beach getaway sometime in August” – a wish, not a precise plan. For years, Airbnb’s interface forced you to enter a location and exact dates, assuming a specific intent. But in 2021, they introduced the “I’m Flexible” search option to accommodate this probabilistic intent . Instead of making you choose exact dates or even a destination up front, the interface lets you explore broad categories (tiny homes, cabins, OMG! stays) or flexible date ranges. This was a radical shift from the traditional travel search designed around fixed plans. Why? Because “not all travelers know where they want to go” – Airbnb acknowledged that many users start with only a vague idea . By offering curated categories and flexible timing, the design meets users where they are and gently guides that hazy intent toward a concrete choice. In other words, Airbnb’s UI acts like a gentle funnel for a cloud of possibilities, helping users discover options they “didn’t know they wanted” . The result: browsing Airbnb feels more like exploring (which travelers love) and less like filling out a rigid form. (Illustration idea: imagine a diagram of a user at the center with many dotted arrows radiating outward, each arrow labeled with a possible action – Search, Explore Category, View Map, etc. – representing the user’s intent vectors. As the user clicks one option, the other arrows fade away, showing the cloud of possibilities collapsing into a chosen path.)

Design insight: Don’t assume your users always have one specific goal in mind. Often, they arrive with a probabilistic mix of intentions. Great products embrace this uncertainty by offering exploratory features or suggestions. Think of how Airbnb’s flexible search or Notion’s template gallery guide an unsure user toward something that resonates. Instead of a blank search box (which can be paralyzing if “you can put anything into it” ), provide a few enticing starting points. Design your interface to surface likely options and allow serendipity, so the product feels like it’s on the user’s wavelength, ready for whichever way their intent collapses.

Cognitive Viscosity: Smoothing Out UX Friction

Every UX designer knows about friction – those little (or big) things that slow users down or make them hesitate. QFIT gives this a memorable name: cognitive viscosity. In fluid terms, viscosity is thickness – water vs. honey. High viscosity means a fluid flows slowly, resisting movement. Cognitive viscosity is similar: it’s the mental resistance users encounter in your interface . Every extra form field, confusing button label, or overloaded menu is like turning your user’s journey from water into syrup. They have to push harder to move forward, and sometimes they just… stop. In QFIT, a key to lovable products is low viscosity – making interactions feel as smooth as a slip ’n slide, not a trudge through mud.

Modern design teams obsess over reducing friction, and with good reason. Even small bits of friction can frustrate users or cause drop-off . Consider Apple’s approach: Apple has long been praised for designs that feel “intuitive” – another way of saying there’s minimal cognitive friction. From the first iPhone’s one-button simplicity to Face ID unlocking your phone without a thought, Apple strives to remove unnecessary steps and doubts. The impact is huge: “Apple’s iPhones are a wonderful example of how reduced interaction friction hugely increases user adoption.” The minimalist, user-centric design means people can pick up an iPhone and figure it out quickly, which is “a core part of why their mobile devices are so successful” . In QFIT terms, Apple optimizes the fluidity of user flow; tasks that might be sticky elsewhere (like setting up a new device) are surprisingly quick and painless on iOS, so users keep moving forward with confidence.

On the flip side, too much choice or clutter can crank viscosity through the roof. We’ve all seen overstuffed apps that give you so many options you freeze up. This is the paradox of choice: every extra option is a potential speed bump. The Airbnb team discovered this when analyzing their search UX. As one review noted, doubling the number of listings shown in search results led to an 18% increase in “search friction”, as users became overwhelmed by too many options . More choice actually slowed people down. Airbnb responded by refining their design: they added filters, highlights like “Superhost” badges, and better sorting to help surface the most relevant options, thereby lowering the viscosity that too much information can create . Similarly, Notion faced a friction problem for new users: a completely blank Notion workspace is powerful but intimidating. So Notion doesn’t drop you into an empty page and wish you luck – it now starts with a friendly onboarding flow and ready-made templates. It’s like a guide handing you a structured notebook rather than a blank sheet. This “feels like a friend handing you a personalized notebook, already set up with sections tailored to what you need,” instead of overwhelming you with endless possibilities . By asking a new user a few questions (“What do you need? How do you work?”) and then tailoring the workspace, Notion dramatically reduces the initial friction of getting started.

Design insight: Friction isn’t just a minor annoyance – it’s a force that can “slow or block user flow, causing frustration or abandonment” . Audit your product for points of high cognitive viscosity. Are there steps where users frequently hesitate, drop off, or “rage tap” buttons? Those are your big rocks in the stream. Remove them or smooth them out. This might mean simplifying a form, breaking a complex task into smaller steps, or providing default values and smart suggestions so the user doesn’t have to work so hard. As Steve Jobs famously championed, simplicity is about making things easy to do. By reducing cognitive viscosity, you keep users in motion – and a user in motion is a happy user. Even adding helpful friction in the right places can be good (like a confirmation step for a destructive action), but always be intentional: every extra ounce of effort you ask from the user should provide more value than the cost. The ultimate win is when using your product feels almost effortless, as if the interface “disappears” and the user just flows toward their goal.

Excitation Fields: Sparks That Motivate Users to Act

Why do users sometimes feel pulled to certain actions or utterly excited to engage? QFIT introduces the idea of excitation fields – think of these as the invisible forces in your product that energize and direct user behavior. If cognitive viscosity was about resistance, excitation fields are about propulsion. In physics, an excitation can pump energy into particles; in UX, certain design elements or moments pump energy into users, motivating them to take the next step. It’s like placing magnets and boosters along the user’s path: done right, they’ll feel naturally drawn forward with enthusiasm.

In everyday design language, these are the features that make your product sticky and fun. Duolingo is a master class in creating excitation fields through gamification. Consider the emotional rush of keeping a streak alive in Duolingo. That streak counter isn’t just a vanity stat – it creates a field of motivation around the user. Each day you see the number, you feel a pull: don’t break the chain! Duolingo amplifies this pull by celebrating your streak (the owl cheers you on) and even added an iOS home screen widget so the streak is always visible. The result? Users with even a 7-day streak are far more likely to stick around, and adding a prominent streak widget on iPhone caused a 60% increase in daily sessions as users were reminded to come back and keep that streak going . That’s a huge boost in engagement – essentially, an injection of energy into the user base. Duolingo also uses XP points, leaderboards, and badges as excitation forces. These elements tap into our competitive and reward-driven instincts. When you see you’re just 30 XP away from leveling up, you get a little jolt of motivation to do one more lesson. It’s no surprise that Duolingo’s leagues (leaderboards) made people complete 40% more lessons per week, and adding weekend challenges spiked activity by 50% . Each of these features is strategically placed to excite users — either through positive reinforcement (yay, I earned a badge!) or a bit of pressure (uh-oh, might lose my streak!) — and that excitement translates into sustained action.

Other products use their own kinds of excitation fields. Apple, for instance, uses subtle delight and feedback as motivators. Think about the satisfying “click” of the iPhone’s haptic feedback when you perform certain actions, or the celebratory animation when you complete an Apple Watch fitness goal (closing your activity rings triggers a burst of colorful animation). Those moments, while small, inject a dose of positive emotion. They encourage you to keep engaging — akin to how a pinball machine’s lights and sounds entice you to play another round. Airbnb leverages social proof as an excitation force: seeing a listing marked “Rare find – this place is usually booked” or “Over 500 people saved this home” immediately creates urgency and excitement to grab the opportunity. It’s like the interface is buzzing with a subtle energy saying “go for it!” In Notion , even though it’s a productivity tool, there are community templates and showcase galleries that inspire users to try new setups (spark of inspiration is a powerful motivator too). The key is these products don’t leave motivation to chance — they intentionally design elements that create gradients of motivation, guiding user behavior in a positive way . In QFIT terms, they’re shaping the “force fields” of the UX so that users are propelled by their own delight and goals, rather than feeling pushed by the product. As QFIT’s originator David Sternberg put it, “Interfaces should guide and choreograph intentions, shaping gradients of motivation and friction rather than forcing actions” . A well-designed excitation field does exactly that: it nudges and inspires without the user feeling forced.

Design insight: To create products people love, it’s not enough to make things easy; you also want to make them enjoyable and motivating. Identify the moments in your user flow where a little encouragement or delight could push them forward. Maybe it’s a progress bar or checklist that shows they’re almost at the finish line of onboarding. Maybe it’s a small reward (even just confetti or a congratulatory message) when they complete a key action. Consider gamification elements carefully: as Duolingo shows, done right, they can significantly boost engagement. But remember, an excitation field should feel like a helpful tailwind, not an annoying shove. The best examples (like Duolingo’s streaks or Apple’s playful touches) work because they align with user’s own goals – users want to stay on track, or be delighted, so the design just reinforces that desire. Brainstorm what “magnetic” moments your product could have, whether it’s social proof, personalized recommendations that excite curiosity, or visual feedback that says “great job!” These sparks of emotion are what turn a utilitarian experience into a lovable one.

Entropy in UX: Navigating Chaos and Clarity

Entropy is a concept from thermodynamics describing disorder in a system – and it’s a useful metaphor in UX for how unpredictable or chaotic user behavior can get when a design lacks clarity. In QFIT terms, entropy in an interface is the degree of randomness in what users do. High entropy means users are all over the place: clicking everything, getting lost, bouncing off in unpredictable ways. Low entropy means a more orderly flow: users consistently navigate as intended, with fewer wild detours. Every product has some entropy (users will always surprise you), but too much entropy is a warning sign that your design might be confusing or overwhelming.

Think about a messy homepage with dozens of equally loud options – users might scatter in every direction (or freeze up, not sure where to start). That’s high entropy. Now think of a well-crafted onboarding that gently guides most users through the same happy path – that’s lower entropy, more predictable and smooth. It ties closely to the idea of cognitive viscosity and excitation we discussed, but entropy highlights the outcomes: are users ending up in all sorts of places (including dead-ends), or are they largely flowing toward successful outcomes?

A great real-world illustration is the contrast in approaches we’ve already touched on with Airbnb and Notion. Early Airbnb basically said “Here’s a search box, type anything you want.” Powerful, yes, but also intimidating – with infinite possibilities comes high entropy because users might not know what to do. One UX reviewer noted, “If you can put anything into it, then it is difficult to know what to put… [Airbnb] redesigned the front page to show curated categories which gives the user clear options for what to look for.” By adding structure – categories like “Tiny Homes”, “Beachfront”, etc., plus flexible date presets – Airbnb reduced the entropy of the search process. They traded the total freedom (and confusion) of a blank search for the clarity of guided choices. As that reviewer summarized, “Clarity means prioritizing the user’s ease of navigation and decision-making over the availability of every possible option at first glance” . In other words, they deliberately decreased entropy (fewer totally random inputs) and improved predictability: users now more often follow one of the suggested paths, and Airbnb can better anticipate and optimize those flows. The search becomes not just easier, but also more consistent across the user base.

Notion , in its onboarding, did something similar to combat the chaotic “blank canvas problem.” An empty canvas has maximal entropy – a new user could do literally anything or nothing, and many would do nothing out of sheer uncertainty. Notion’s guided onboarding (questions about your use case, then providing a template) injects structure, vastly reducing that chaos. Now new users tend to follow a handful of predefined setups, meaning the team can predict common first steps and ensure those are smooth. It’s like turning random flailing into a directed first-time experience. Users still have freedom, but within a framework that makes success more likely. The result: fewer people give up in confusion, and more reach that “aha!” moment where they see value.

High entropy in UX often shows up in behavioral turbulence – those rage clicks, repeated back-and-forth navigation, or unexpected drop-off points where users just vanish . These are symptoms that somewhere, the flow broke down into chaos. Maybe a button didn’t do what was expected, or the next step wasn’t clear, so users started trying anything (like pressing the same button repeatedly or wandering through menus). QFIT actually uses the word turbulence for these moments – just like turbulent water, user behavior becomes erratic and hard to predict. Our job as designers is partly to detect where entropy spikes and calm those waters. Often, the fix is improving feedback or adding a hint of guidance: if users commonly bounce at Step 3, perhaps Step 3 needs an example or a clearer call-to-action to anchor them. If you see many users pogo-sticking between two screens, perhaps they aren’t sure which contains what they need – a sign to simplify navigation.

Design insight: When designing for lovable products, fight the chaos. This doesn’t mean oversimplify everything or remove choice; it means provide enough structure that users aren’t left in a state of perplexity. Watch for signs of high entropy in your user data: lots of erratic clicking, wildly divergent user paths, or common frustrations voiced in feedback. These indicate parts of your product where users are essentially saying “I’m not sure what to do, so I’m trying everything” (or worse, “I’m giving up”). To reduce entropy, clarify the next step. Use visual hierarchy to make the primary action obvious. Employ progressive disclosure so that at any given moment, the choices aren’t overwhelming. A useful exercise is to ask: If I were a first-time user with no specific goal, would this screen guide me toward something interesting or useful? If the answer is no, you might need to tame the randomness by suggesting popular or recommended actions. Another tactic is consistency – when interfaces behave predictably, users learn the patterns and don’t have to thrash around. Consistency in navigation and terminology across your product will lower the overall entropy, because users can transfer their understanding from one part to another. In short, bring calm to the chaos: design with the intent to gently shepherd users towards success, especially at critical waypoints. Your users will thank you, even if they never know why their experience felt so smooth and sensible.

Flow Visualization: Mapping the Currents of User Behavior

In traditional UX, we love our flowcharts and journey maps – those static diagrams with boxes and arrows showing how we think users will move through our product. QFIT takes the idea of a “user flow” and gives it literal life. What if we could visualize user behavior as if it were a fluid flowing through a landscape (our interface)? Flow visualization in QFIT is about seeing where the stream of users runs fast, where it pools or eddies, and where it splits or converges. It’s a mindset shift from viewing user paths as straight lines in a funnel to viewing them as dynamic streams that can be analyzed and even simulated.

Imagine an interface screen and overlay on it something like a weather map of user activity: currents of navigation from one element to the next, swirling spots where users loop around, and perhaps heat-map intensity showing where users linger. This is a more continuous view of interaction than, say, a drop-off chart that just says “20% left on step 3”. It’s the difference between a step-by-step recipe and watching a video of someone cooking – one gives you discrete steps, the other shows the flow between them. Why is this useful? Because a flow visualization can reveal not just where users drop off, but how they got there, what they did along the way, and where their momentum faltered.

In practice, product teams are starting to use tools that hint at this fluid view. Product analytics platforms can show common user paths (like Sankey diagrams of how users navigate). Session replay tools let you literally watch the flow of an individual user’s cursor. But QFIT suggests we can go further – even predicting flow issues before they happen. In fact, one of QFIT’s promises is to “simulate, model, predict user behavior before shipping, not just react after” . Think of it like a wind tunnel for your product: you can prototype an interface and then use a model (informed by behavioral data) to simulate how users might flow through it. Where do they slow down? Where might they get stuck against a “UI wall”? While this is still an emerging idea, the mindset is powerful. It encourages us to continually visualize and validate the flow of our designs, not just the static screens.

Let’s say you design a new checkout for Airbnb. A traditional approach is A/B testing it – launch and see if conversion improves. A QFIT-inspired approach would have you diagram the forces in play: the motivation pushing forward (perhaps a desire to book quickly before the listing is gone), and the friction resisting (maybe the length of the payment form or trust concerns). You might visualize users as particles moving through the funnel, and anticipate that a big friction point like an unexpected fee at step 4 will create an “eddy” of drop-offs there. By visualizing that flow in advance, you can iterate the design (e.g., provide upfront price estimates to avoid a surprise) before launching to users. It’s a bit like chess – thinking a few moves ahead about how the user might react and adjusting proactively.

Even without fancy simulation tools, designers can apply flow visualization thinking by mapping out user journeys with a fluid lens. For example, Duolingo’s team could take their lesson flow and ask: where do users slow down or repeat steps? If a large number of users keep revisiting a particular lesson or re-reading tips, that’s a swirling eddy – perhaps the lesson is too hard or unclear. Recognizing that pattern might lead them to insert an extra hint or a lighter review session there to smooth the flow. Notion’s team might look at a heat map of clicks in the app and realize a lot of new users are clicking back and forth between the “Templates” gallery and their workspace – indicating they’re unsure how to integrate a template, effectively oscillating in place. To fix that, they might update the UI to allow adding a template with one click, eliminating that back-and-forth turbulence. Meanwhile, Apple’s designers likely constantly observe how users navigate new features (like when a new gesture or control center layout is introduced) – if users aren’t finding a feature, it’s like a part of the river nobody is flowing into, possibly requiring a signpost or a more obvious entry point.

Design insight: Start thinking of your analytics and user research data in terms of flow. Instead of just asking “Where are users dropping off?”, also ask “What detours are they taking? Where do they speed through without issue, and where do they meander or backtrack?” Mapping these out can be as simple as sketching a state diagram on a whiteboard and drawing thicker lines for frequent paths, dotted lines for uncommon ones, and curly “storm” symbols where users seem confused. This can highlight inefficiencies or pain points that a traditional funnel view might miss. Once you identify a turbulent spot, dive in like a UX detective: Why is the flow breaking there? Is there a mismatch of expectation, a lack of information, or a sudden increase in friction? Often the fix is to either remove an obstacle or add a guiding force (sound familiar? Reduce viscosity or add an excitation!). By continuously visualizing and refining the flow, you move closer to that ideal of an “experience that feels as natural as water flowing downhill.” This approach turns design into an iterative science: you form hypotheses about the flow, test them, and tweak the design to improve the currents. Over time, you’ll develop a kind of intuition for flow – an almost physical sense of how energy moves through your product. That’s a superpower for any product designer or manager, and it’s at the heart of QFIT thinking.

Conclusion: Bridging Physics and Design for Lovable UX

At first glance, quantum states and fluid dynamics might seem worlds away from apps and websites. But as we’ve explored, these analogies provide a rich, scientifically informed way to think about the subtle forces at play in user experience. Quantum-Fluidic Interaction Theory (QFIT) essentially says that every interaction in a product can be viewed through a physics lens – with user intent, friction, motivation, uncertainty, and flow being the building blocks . By understanding these, we can predict and shape behavior more effectively, moving UX from a craft based on intuition to more of a science based on principles . But the beauty is that it doesn’t make design cold or robotic – quite the opposite. It gives us new ways to empathize with users: we recognize when they’re uncertain (probabilistic intent), we feel when they’re stuck (viscosity), we sense what excites them (excitation), we notice when they’re lost (entropy), and we visualize how they journey through our creations (flow patterns). It’s a marriage of rigour and creativity.

For digital product designers and managers, the takeaway is both inspirational and practical. On one hand, thinking in terms of QFIT can spark novel solutions – you might suddenly see a thorny UX problem in a new light (aha, it’s a turbulence issue, not just “user error”!). On the other hand, QFIT reminds us of fundamentals that often get overlooked: users are not static or purely logical entities; they’re influenced by context, psychology, and interface dynamics in real-time. Our job is to choreograph the dance of user intentions as artfully as we can. Or as David Sternberg quips, “You don’t design interfaces anymore — you choreograph intentions.” When we do that, we create products that don’t just function, but flow — experiences that guide users gently to success, engage them emotionally, and adapt to their needs and choices. In short, we create products people truly love.

In your next design or product decision, try applying a QFIT lens: Ask where users might be in a superposition of needs, and give them an exploratory nudge. Hunt for the sticky points slowing them down, and find a way to melt that friction. Find opportunities to delight or motivate, turning routine steps into engaging moments. Simplify chaos into clarity so users aren’t left guessing. And continually sketch and imagine the flow of your experience like a living stream. By doing so, you’re not just pushing pixels, you’re shaping the invisible forces that move users. That’s the new science – and art – of creating products people love. With QFIT’s principles in your toolkit, you’ll be better equipped to build irresistible user experiences grounded in how people really behave, and why. Happy flow designing!