The mystery of Nikita Bier's startup success rate: from failure to serial entrepreneur

31-year-old Nikita Bier has completed two high-profile exits and built multiple products valued in the millions of dollars, but behind these dazzling achievements lies a more interesting story—his actual success rate in startups is surprisingly low. According to his own public shares, before his three successful products (Politify, TBH, Gas), he failed at least 14 apps. This suggests his actual success rate may be less than 10%. Today, the entrepreneurial methodology of this “viral growth king” is being reused and validated across the X platform and the entire Web3 ecosystem. The question is: how can an entrepreneur with a failure rate over 90% keep succeeding repeatedly? The answer lies in his understanding of human nature and his obsession with iteration speed.

Three startups, three victories with increasing scale— the logic behind the success rate numbers

From policy simulation to teen social networking to financial discussion platforms, Nikita Bier’s three major entrepreneurial achievements demonstrate vastly different success cycles.

In 2012, Politify, founded by Nikita at Berkeley, seemed just a tax calculator, but was actually a clever application of psychology. It attracted 4 million users with zero marketing budget, topped app download charts, and received support from the Knight Foundation. The key to this success was not feature innovation but addressing the pain point of “information asymmetry” in voters’ political decision-making—after seeing data like “supporting a candidate costs you $2000 net per year,” users naturally stayed, shared, and reflected. This cycle was relatively long but proved Nikita’s ability to translate macro issues into micro user behaviors.

In 2017, TBH changed the game. This anonymous mutual praise app for high school students reached 5 million users and 2.5 million daily active users in two months. Compared to Politify’s longer growth period, TBH’s growth was twice as fast. This success was built on directly tapping into teenagers’ “social validation desire”—anonymous praise triggered dopamine loops that made users addictive. The team had only four members but created a phenomenon-level product quickly. Facebook soon saw the threat and acquired TBH in 2018 to eliminate competition.

In 2022, Gas’s launch proved that this methodology could continue evolving. The upgraded Gas surpassed 10 million users in just three months, generating $11 million in revenue, once surpassing TikTok and Meta to become the most popular app in the US. This time, the product not only experienced explosive growth but also achieved real monetization—by charging for the “who liked you” feature, closing the loop. After being acquired by Discord for $50 million in January 2023, Nikita had demonstrated that he could turn short-term viral growth into a sustainable profit network.

Key observation: these three success stories show an accelerating cycle—from a few months to 2 months to 3 months. Meanwhile, the revenue leap from zero to $11 million is not accidental but reflects a deepening understanding of success models.

How to turn over 90% failure into 10% success: dissecting the product methodology

Nikita Bier’s ability to stand out amid high failure rates stems from his four core principles—this logic is almost always overlooked by failed entrepreneurs.

First, focus on network benefits rather than individual pain points. He repeatedly emphasizes that successful consumer apps are not about fixing bugs of competitors or solving specific user pain points, but about serving the entire social network growth flywheel. This means product design should shift from “what can I help you with” to “what kind of interactions can I generate between you and the entire network.” Politify’s success was not because it was more accurate in tax calculation, but because it turned voting decisions into visual, shareable, discussable social events.

Second, precisely target “life turning points.” Nikita’s products always appear at moments when users are most vulnerable and eager to connect—TBH targeted high schoolers, Gas also targeted teenagers, both during key identity shifts and social status confirmation. He believes that ordinary products trying to acquire users in stable daily scenarios have low success rates; those that can accurately identify moments when users “desire connection” will see exponential viral coefficients. It’s not about feature design but about timing mastery.

Third, confront and amplify the “primitive drives” of human nature. Nikita openly states that humans’ most fundamental needs are not efficiency or convenience, but praise, status confirmation, and social validation. He views consumers as “lizard brains”—political stances or decentralization ideals have almost no behavioral drive; only instincts like making money, dating, and being recognized can truly trigger behavior change. Under this logic, TBH and Gas are highly rational: they are not about improving social experience but about amplifying the human desire for recognition, then converting that desire into addictive dopamine loops.

Fourth, embrace a “madman” mentality and rapid iteration. Nikita has openly shared that after 14 failures, he finally found the successful direction with TBH. This means he is not trying to plan perfectly but is rapidly testing and finding breakthroughs through trial and error. He believes that 99% of decisions are critical, failure rates are extremely high, but the key is iteration speed—quickly acknowledging mistakes, embracing feedback, and adjusting direction, rather than chasing illusions like big companies do. This mindset is highly reusable because it fundamentally involves “scaling trial and error to improve success rate.”

This methodology explains why startup success rates are so low and why Nikita can repeatedly rise from the mud—he is not gambling on luck but systematically narrowing the scope of failure.

From Solana advisor to X product lead: reusing the same logic across platforms

After two exits, Nikita did not choose to rest or join a big company, but instead turned his focus to Web3 and finance—yet his approach remains pragmatic.

In September 2024, he joined Lightspeed Venture Partners as a product growth partner, mainly helping Web3 projects in their portfolio optimize viral growth and network effects. This role kept him observing emerging ecosystems while avoiding being tied to a single project. In March 2025, he officially joined Solana Labs as a consultant, focusing on building the mobile consumer ecosystem. In his assessment, Solana is an ideal platform for consumer apps due to improved regulation, more open App Stores for crypto, and the memecoin boom making Phantom wallet popular on millions of devices.

More importantly, during this period, Nikita maintained a rational view of his value—he offers not price predictions or project endorsements but strategic advice on how to expand app scale through viral growth and network effects. This is his core competitive advantage and the key ability he can reuse across multiple platforms.

Six months later, his career path shifted again. By late June 2025, he officially took on the role of product lead at X. This stage is no longer a startup or VC ecosystem but a global social platform with 300 million daily active users. From this perspective, Nikita’s three startups are not isolated events but validations and iterations of the same “human nature-driven growth” theory at different scales.

101 days on X: from feature optimization to content ecosystem reshaping

After joining X, Nikita demonstrated a different speed and complexity compared to early startups—he had to implement his growth philosophy within a large corporate structure, which is itself a challenge.

From early July’s core feed optimization, to October’s community feature preview, to January’s algorithm tweaks and the launch of Smart Cashtags, each step reflects his relentless focus on “improving user retention.” The recommendation page was optimized for “network density”—by increasing the proportion of content from friends, mutual follows, and followers, to show familiar people’s activities and strengthen daily habits. This logic directly inherits from TBH’s like-loop: seeing familiar interactions makes users more eager for social validation.

The launch of Smart Cashtags further solidified X’s unique positioning—real-time stock prices combined with live discussions, making “life turning points” happen within the platform. This is not just a feature innovation but another validation of his “life turning point” theory: users are most active, interactive, and likely to retain during trading decisions.

The results in numbers: X app downloads increased by 60%, daily usage time grew by 20-43%, and subscription users surpassed 1 billion. This growth not only exceeded previous platform expectations but also proved that Nikita’s methodology works on large platforms—low success rate, but once successful, highly scalable.

Killing Infofi: the ultimate showdown between content quality and entrepreneurial logic

The latest development is recent. On January 16, Nikita announced that X would revise its developer API policy, directly banning “infofi” type apps—products that incentivize users to post via points or tokens, like Kaito, Cookie, etc.

On the surface, this is a crackdown on low-quality content (spam generated by AI and “yap” junk replies). But the deeper logic is more complex: infofi products rely on incentivizing users to post to achieve growth, which fundamentally conflicts with Nikita’s growth philosophy—he emphasizes “serving the network, not individuals,” whereas infofi is the extreme of individual incentives, rewarding low-quality content that damages platform network effects.

More profoundly, this decision is also clearing the way for X’s crypto and financial ambitions. X is actively developing financial features, with Smart Cashtags as the first step. The future vision includes integrating payments, DeFi, and even memecoin ecosystems. But all of this depends on high-quality content—if the platform is flooded with low-quality yap from infofi, serious investors and builders will be scared away.

From the success rate perspective, Nikita’s move redefines failure by the standards of success— even if infofi apps can bring short-term user growth, in the long run they undermine the platform’s “network health” indicator. This is a lesson he learned from 14 failures: not all growth is worth pursuing, only those that can be reused, sustained, and reinforce network effects are truly successful.

Conclusion: the inevitability behind entrepreneurial success rates

Looking at Nikita Bier’s trajectory, the low success rate in startups is not a reflection of personal ability but a true picture of the entire entrepreneurial ecosystem. Interestingly, this low success rate makes success more meaningful—his accumulated experience from failures and intuition refined through trial and error have ultimately formed a universal methodology that can be applied across different scales and platforms.

From Politify’s 4 million users, Gas’s $11 million revenue, to a 60% increase in downloads on X, Nikita proves a paradox: the highest success rate often comes from correctly understanding the lowest failure rate. He is not a lucky entrepreneur but a systematic explorer who models failure and success. In an era where startup success rates are generally below 10%, this methodology may well be the next-generation blueprint for entrepreneurs to learn.