When you’re building for Gen Z, scale is never just about servers, latency, or downloads. It’s about trust. This generation has grown up in the shadows of algorithmic feeds and curated influencer culture, and they’ve learned to spot inauthenticity instantly. The question every builder should ask is not just how do I scale my app, but how do I scale authenticity, personalization, and community without breaking them in the process?
In our work on consumer platforms, we’ve tackled this challenge across products that now engage over four million users. Our music-sharing app surpassed two million downloads and topped the App Store charts in Spain and France. Meanwhile, our AI-driven social simulation gained a million users in its first month, with half a million daily active users, operating with sub-second latency and 95% lower AI inference costs than many competitors. The technical decisions and cultural design choices behind these results offer valuable insights for those building next-generation consumer platforms.
Authenticity as the First Design Principle
One of the earliest bets we made was that Gen Z is allergic to polish. While older networks were built on follower counts and staged feeds, our users were looking for something closer to a group chat with friends: spontaneous, imperfect, and real.
Our music-sharing app was our first attempt to codify this. We called it “the BeReal of music”, a platform where users received a daily prompt to share the song they were listening to at that moment. There was no time to stage a playlist, no opportunity to craft a persona. What emerged was a feed of genuine tastes and moods, which users described as “no pressure to be a certain way.”
That same ethos carried into our AI-driven social simulation. Even though it was a simulation, an AI-driven universe where every other account is synthetic, we built it to encourage honest, creative expression. We allowed players to immerse themselves in storytelling and fandom without the toxicity of traditional feeds by stripping away vanity metrics like public follower counts. In both cases, the design principle was the same: create space for realness, even in fictional or playful environments.
Personalization Without Feed Fatigue
The second pillar was AI personalization but with restraint. Gen Z doesn’t want to be firehosed with endless, random content. Their expectation is that an app will reflect their interests, humor, and cultural shorthand without overwhelming them.
In our AI-driven social simulation, users set their own universe: a Harry Potter fandom, a K-pop community, a fictional high school. From there, AI populates the feed with characters, posts, and drama that feel unique to that world. This upfront curation meant users felt in control of the context.
We also deliberately avoided infinite scroll. Instead, it plays more like a game session. Each day, users have an “energy meter” that allows them to post and interact for about an hour. Once it runs out, they can either wait or pay to continue. This design encourages depth over volume as sessions are story-driven and meaningful, rather than endless background noise.
Behind the scenes, scaling this required engineering discipline. Our first iteration used Anthropic’s Claude 3.0 to generate dynamic feeds, which produced excellent results but at unsustainable costs. To fix this, we fine-tuned our own lightweight model, Gemini 2.0 Flash, and rebuilt the content architecture. The result: over 90% reduction in inference costs and sub-second response times for hundreds of thousands of concurrent users.
Equally important was making the AI “sound” native to Gen Z. We built feedback loops so that whenever users downvoted content as “cringe” or inauthentic, our system adapted. Over time, the AI became more like a friend on Discord, fluent in slang, humor, and cultural cues, rather than a corporate chatbot.
Monetizing Passion, Not Attention
Monetization for Gen Z apps can be a minefield. They can smell a cash grab instantly, and nothing erodes trust faster. Our breakthrough came when we stopped thinking about “features to charge for” and instead asked: what are they already invested in emotionally?
The answer was storytelling. Users role-playing as characters in their chosen universe often became deeply attached to their evolving narratives, making friends with AI classmates, getting into debates, uncovering plot twists. We monetized by letting them extend that story. The energy system provided about an hour of free play each day, but when the narrative got too compelling to drop, many happily paid a small fee to keep going.
This worked because payment was directly tied to the core experience. Users weren’t buying skins or random trinkets. They were paying to continue something that mattered to them personally. Just as important, monetization was optional. Alternative paths such as waiting for energy to recharge or inviting friends meant no one felt coerced. Those who paid did so enthusiastically, while others still retained.
The lesson is that the Gen Z will pay for authenticity and value, but not for artificial scarcity. Align monetization with their passion, not your balance sheet.
Engineering Scale With Limited Resources
As a six-person team, we had no budget for massive paid user acquisition campaigns. Instead, we grew by embedding ourselves where Gen Z already was: TikTok. Instead of investing resources in traditional advertising, we produced catchy memes and short videos highlighting the engaging and distinct parts of the gameplay. Our unique marketing method increased the number of our beta testers from 6,000 to over 500,000 active users daily in a span of one month and all without any paid marketing.
After this, we directed our users to a Discord channel which is currently at 200,000 members. This gave the fans a way of extending the product's life. Even outside of the app, they could collaborate in creating lore and stories. To maintain engagement, the app implemented daily prompts and reward systems which could only be accessed by invitation. Zero-dollar marketing and community-driven growth enabled us to heavily invest in a zero-dollar retention strategy.
From an engineering standpoint, this meant building modular systems that let us spin up and shut down products quickly. During the development, we launched and killed eight experimental apps within months, reusing backend services, analytics, and feedback tools across all of them. That modularity was the only reason a small team could iterate at the speed of much larger organizations.
Convergence of Authenticity, AI, and Niche Commerce As The Future
Looking ahead, I see three threads in terms of authenticity, personalization, and niche communities, weaving together into the next era of social commerce.
Gen Z doesn’t shop through polished ads. They discover through peers, fan communities, and micro-influencers who feel real. I believe commerce will increasingly be woven into those small communities, not as interruptive banners, but as natural extensions of conversations.
AI will play a central role here, but only if it speaks the language of each community. That means fine-tuned models that understand not just individual preferences but the ethos and inside jokes of each subculture. Technically, this demands building leaner, cheaper AI so personalized experiences can scale without prohibitive costs. Our goal is to make hyper-personalized AI interactions cost mere cents per user, cheap enough to support freemium access while monetizing through genuine value-adds.
Finally, niche communities themselves will become the new marketplaces. Instead of giant digital malls, we’ll see fandom conventions, activist groups, and micro-communities functioning as commerce hubs. Trust will be built on authenticity, relevance, and participation.
Closing Thoughts
Scaling Gen Z-focused apps is about building systems that preserve authenticity at scale, AI personalization that feels human, and monetization that respects passion.
The temptation is always to copy the playbook of past networks, infinite scrolls, follower counts, cosmetic microtransactions. But the generation we’re building for has already rejected those models. They want something smaller, more personal, and more creative.
For those of us in product and engineering roles, the challenge and the opportunity is to build technology that amplifies that shift, rather than fight it. That’s been our mission: design products where Gen Z feels seen, empowered, and entertained, while proving that authentic, AI-driven communities can scale sustainably.
Because in the end, scale without authenticity isn’t really scale at all.