Every week it seems, another AI startup launches with fanfare, a bold manifesto, and a promise to “change how people work.” The product is often technically remarkable: faster, more powerful, even a bit magical. Yet, two months later, the buzz dies, the sign-ups stall, and the founders find themselves asking the same question: Why aren’t people using it?
It’s not that users don’t need what you’ve built. It’s that they don’t feel what you’ve built. The gap between a working model and a product that resonates is what I call the Magic Moment Problem—the point where the brilliance of your technology fails to land with a human audience.
The Illusion of Value
In most AI-native startups, founders are engineers or machine-learning specialists. They see the model as the core product. But users rarely care about the underlying architecture. They care about outcomes—speed, simplicity, power, delight.
When you demo your product, you’re watching it with insider eyes. You understand the data transformation happening behind the curtain, and you see elegance in the algorithm. Your user doesn’t. To them, it’s another tool that claims to “save time” or “enhance creativity.”
That’s why some of the smartest AI products on the market get beaten by simpler, less capable competitors. The winners have figured out how to create one clear, emotionally resonant moment where users instantly understand why this tool matters. Think of the first time someone used ChatGPT and realized they could ask software to write for them. That’s the magic moment. It wasn’t about the model; it was about the revelation.
The Experience Curve in AI Products
Traditional software follows a predictable adoption pattern: users explore, learn, integrate, and then depend. AI flips that upside down. The most successful AI products deliver value before the user even knows how they work.
Take Midjourney. You don’t need a tutorial to be impressed. You type “cinematic portrait of a person made of glass,” hit enter, and within seconds, you’ve experienced generative power. The UX is deliberately minimal because the output does all the convincing. That immediate gratification is everything.
Compare that to a dozen other AI tools that bury their value behind complex setup steps or vague explanations of “how to get the best results.” They may be technically stronger, but they fail to deliver an emotional hook early enough to keep people engaged.
Your product needs to front-load that payoff. Users should experience your value in under a minute. Anything longer, and curiosity fades.
Simplicity as a Competitive Weapon
Here’s the uncomfortable truth: complexity kills momentum. Most AI-first products are overbuilt—not because founders love complexity for its own sake, but because they equate capability with value. More features, more sliders, more options. But capability doesn’t equal clarity.
Simplicity, done well, is a strategy. It’s not about dumbing things down; it’s about reducing cognitive overhead so the user can appreciate what’s unique about your product.
Look at how Notion integrated AI. It didn’t add a separate “AI workspace” or force users to learn new syntax. It quietly embedded AI into the workflow people already knew—write, edit, summarize, brainstorm. The experience felt natural, not revolutionary. That’s the secret: invisibility. The best AI products make intelligence feel like a feature of the environment, not an alien presence.
When users can focus on the result, not the system, they stay longer and explore deeper.
The Founder’s Blind Spot
Founders often believe their biggest risk is technical failure. In reality, it’s emotional indifference. The danger isn’t that your product doesn’t work—it’s that it doesn’t matter.
This blind spot happens because founders live in a feedback loop of peers, investors, and early adopters who value novelty over clarity. It’s easy to mistake curiosity for traction. A few hundred power users can make you feel like you’re onto something when, in fact, you’re sitting on a fragile illusion of product-market fit.
You need to step outside your own echo chamber and study the moments when users abandon your product. What were they trying to do? What expectation wasn’t met? Every churn point hides a design flaw disguised as a technical limitation.
Building for Non-Experts
AI-native founders love to build for people like themselves. That’s natural—you understand their mindset, their expectations, their patience for technical quirks. But that’s not where scale lives.
To build a sustainable company, you have to design for people who don’t think like engineers. They don’t care about token limits or vector embeddings. They care that your product feels responsive, forgiving, and rewarding.
Human-centred design in the AI era isn’t a buzzword; it’s a growth strategy. It’s how you translate capability into comprehension. A great product doesn’t just work; it makes people feel competent and confident. If your onboarding experience requires an explainer video or a Discord community to understand the basics, you’ve already lost half your potential users.
From Features to Feelings
The most common question I hear from AI founders is: “What feature should we build next?” My answer is always the same: “What feeling do you want your users to have?”
Every product interaction is emotional. When users feel powerful, they trust you. When they feel confused, they leave. The best AI products map features to feelings deliberately.
• Instant feedback creates excitement.
• Showing your sources adds credibility.
• Explaining what the AI did and why is key.
• Predictable behaviour builds trust.
• Gentle guardrails reduce anxiety.
• Small wins early in the journey trigger retention.
If you want users to keep coming back, don’t give them more functionality—give them more confidence.
Designing for Discovery
One of the overlooked challenges in AI UX is that users often don’t know what’s possible. Traditional software has clear boundaries. AI products, by nature, are open-ended. That’s both liberating and paralyzing.
You need to guide discovery. Don’t wait for users to ask “what can it do?”—show them. Use contextual prompts, templates, and suggestions to make exploration effortless. Think of it like stage direction: you’re not scripting their experience, but you are setting the scene so they can improvise successfully.
Products that rely on users to figure out their power will always underperform. Products that teach users through interaction create advocates.
The Importance of Restraint
When everything feels possible, restraint becomes your greatest asset. Resist the temptation to show off the full spectrum of your AI’s capability at once. Instead, build momentum through progressive revelation—let users uncover new abilities naturally as they deepen their engagement.
Overwhelming users with potential makes your product feel chaotic. Letting them discover its depth makes it feel alive.
That’s how Apple sells wonder. It’s how Figma turns complex collaboration into play. And it’s how your AI product can transform from “powerful” to “beloved.”
How to Engineer Emotion
Engineering emotion sounds contradictory, but it’s the next frontier of AI product strategy. Here’s the shift: you’re not just building features—you’re designing emotional arcs.
Start by identifying your product’s core emotion. Is it relief? Excitement? Confidence? Then design every interaction to reinforce that feeling. From loading states to error messages, from animations to copy tone, consistency is what turns a function into a relationship.
The hardest part isn’t building the feature; it’s deciding what not to build. Simplicity requires courage. But that courage pays dividends in retention, advocacy, and brand differentiation.
The Role of Product Strategy
At Tension, this is where we live. We help AI-native founders translate their technology into experiences that land emotionally, commercially, and strategically. We start early—well before wireframes or mockups—defining not just what the product does, but why it matters.
We look for the friction points where users fall off, the missing context that breaks trust, and the opportunities to create clarity without slowing momentum. The result isn’t just better design—it’s faster growth, deeper loyalty, and products that stand out in a sea of sameness.
AI will keep getting smarter. That’s inevitable. What isn’t inevitable is whether your users will care. The winners of this wave won’t be the ones with the best models, but the ones who make those models matter.
That’s what the magic moment is all about. It’s the intersection of technology and feeling—the point where innovation becomes adoption. When you find it, everything changes.
Starting something? Maybe you’re building a new product or service from the ground up, or revamping an existing one? We can help.
