For more than a decade, fashion tech has largely meant one thing: selling clothes online, faster and more efficiently. From recommendation engines to resale marketplaces, startups and industry titans alike have focused on smoothing the path from discovery to checkout. Amongst a slew of well-funded startups vying to compete in this space, Google also fielded its own entry, a virtual try-on experience which uses AI-generated imagery to help shoppers visualize how clothing might look on their bodies.
In fashion, the e-commerce space shows no signs of slowing down: consumers spent roughly a trillion dollars on fashion globally in 2025, and with year-over-year growth expected to remain steady through 2030, the industry has reached a certain maturity. However, for some founders, that maturity invites the question: Will shopping continue to be the primary frontier of innovation in fashion tech?
“I’m not sure the biggest shifts will necessarily be in the e-commerce space,” says Max Hui, co-founder and COO of Lookbook, a San Francisco startup that has raised $150,000 in angel funding to build the next evolution of fashion tech. In his view, emerging technologies like virtual try-on could meaningfully improve the buying experience, but largely in additive ways. They may help confirm decisions or increase conversion, he argues, without fundamentally altering the rhythms of how people shop.
“Online shopping will still look like online shopping,” Max says. “And in-person behaviors like thrifting will still look like thrifting, at least in the near future.”
The two cofounders of Lookbook, CTO Avery Chen (left), COO Max Hui (right)
Gen Z and Seeking Understanding
Instead of chasing incremental gains in the shopping process, founders are looking elsewhere for inspiration—sometimes, outside of fashion entirely.
“A lot of the most compelling consumer products right now aren’t about buying at all,” Max points out. “Especially amongst Gen Z? They’re about tracking behavior and reflecting it back to the user.”
Max, who is responsible for Lookbook’s operations and product strategy, cites apps like Spotify Wrapped, Strava, and Beli as platforms that inspire his approach to the fashion space. Beli is a mobile app for restaurant ratings, reviews, and sharing, but it fundamentally revolves around helping the user maintain and curate a personalized ranking of their dining history. Products like these, Max posits, focus less on immediate spending and more on helping the user build an understanding of themselves and their own habits over time.
This approach has resonated with younger users: in the four years following Beli’s inception in 2021, the number of restaurant reviews logged to its platform has almost caught up to incumbent Yelp—75 million to 84 million over the same period, as reported by the New York Times.
“You see this behavior in clothes, too, for Gen Zers like myself,” Max says. “We take fit pics, we screenshot inspo, we collect, and we curate.” None of this is framed as shopping, yet it nonetheless shapes taste, identity, and eventually the user’s purchasing choices.
This gap is where Max is positioning Lookbook to disrupt the fashion space: systems that help users gain an understanding of their personal style over time. “We’ve used some complex techniques and technologies that have been used in other domains, and we apply that to break down what you like to wear.”
To put their vision to the test, Max and his team began running a structured beta program with hundreds of users, onboarding small cohorts for two-week cycles. The founders met with participants at the start, midway, and at the end, allowing the team to observe not just usage, but how their perception of their own style evolved. “In some ways, users engaged as we expected. In other ways, we were surprised,” Max says. Overall, the program was a success that the team hopes to replicate: within the first two weeks, the platform identified thousands of unique clothing items from the photos that users had uploaded. “We were able to use over five hundred photos to understand each individual user’s style on a granular level that platforms previously haven’t been able to achieve.” They now have their sights set on expanding the test from hundreds to thousands of users, says Max.
AI: Not a Silver Bullet?
Any conversation about the future of fashion tech inevitably involves AI. But consumer sentiment around AI-driven products has grown increasingly mixed.
Against a backdrop of corporate interest in deploying models to bolster worker productivity, critics have popularized terms like “AI slop” to describe a growing volume of low-quality, derivative output produced by generative AI models. More recently, safety and consent controversies have further tarnished the image of AI in the public eye.
“Consumer sentiment towards AI is actually quite negative,” Max says. “I think there’s a big disconnect between what Silicon Valley thinks people want, and what people are actually asking for.”
For consumer-facing products, that skepticism has concrete implications. Startups that position AI as the headline feature increasingly struggle to articulate lasting value beyond novelty. In response, some teams are rethinking how the technology shows up in the user journey.
For Lookbook, Max has seen firsthand that the less AI, the better. “In speaking with our users and Gen Zers broadly, we’ve found that AI-forward language has a neutral to negative impact on what people think of a product.” This has led the team to adopt a wary position on the technology: “We avoid relying on AI to do what can be achieved by traditional computing methods. We’re not going to slap a chatbot on something and call it a day.”
Social Fatigue
The same recalibration is playing out around social features. Social platforms have long shaped how people engage with fashion, from Instagram to TikTok, empowering creators and accelerating trends at unprecedented scale. But for many consumers, pictures of their daily outfits are not something they’re keen on sharing with the public.
Lookbook has been cautious about leaning into social features, according to Max, arguing that trust and personal value need to come before distribution. “Once you add sharing, you change the incentives,” he says. “You have to be really intentional about what kind of behavior you’re encouraging.” The team recognizes the power of a good social mechanism, he admits, but he also emphasizes that the feature has to feel in harmony with the rest of the product.
Style Beyond Shopping
Taken together, these choices reflect a broader thesis. For Lookbook’s founders, the next generation of fashion platforms should function more like personal systems than sales associates—helping users make sense of their own behavior before telling them what to do next.
“Once you understand the user, you’ll also understand what they might be interested in buying,” Max says. “But understanding the user is the hard part. That’s a big focus of our beta program, where we’re interviewing our users and tracking tens of thousands of interactions to see what resonates.”
