Interview with RockFlow Founder Vakee: Killing Every App, From Stock-Picking Prodigy to AI Gambler | 100 AI Creators

AI闹·May 13, 2025·0·0

Before developing Bobby, Vakee had been trading stocks for more than 20 years.

Produced by | AI NOW!

Before building Bobby, Vakee had been trading stocks for over 20 years.

She started at age nine (three years later than Warren Buffett), trading on pure intuition. After graduating from Imperial College, she joined a quant fund, using machine learning to trade futures and derivatives. In her twenties, she made her first 10 million by shorting a U.S. stock.

Account balances ballooned like video game scores. For Vakee, making money came too easily — almost boring. She had little patience for effortless pleasures: designer bags, travel, hoarding luxury goods. She typically shopped on Pinduoduo, never flew business class unless it actually got her there faster.

When trading became as automatic as breathing, she needed a wilder game.

After several years doing product and R&D at a major tech firm, followed by five years in venture capital, Vakee officially started her own company. Her first product was RockFlow (Chinese name: 奇运证券), an AI-powered U.S. stock brokerage for global users.

RockFlow used AI to simplify investing, rolling out features like daily trade recommendations, auto-copy trading, and streamlined options — turning complex financial platforms into something as engaging as a game.

But this 2021 launch remained, at its core, a "smarter tool." It couldn't understand why a user wanted to trade at that moment, much less place the order for them.

Now Vakee is about to launch her next project: an AI Agent named Bobby.

Bobby's goal is to eliminate the app entirely. Ordinary users simply express their ideas in natural language, and Bobby handles the full pipeline: intent decomposition → strategy generation → order execution, completing the trading loop.

RockFlow app order interface vs. Bobby natural language order page

Here's an example: When you're browsing Pop Mart, Bobby pops up: "You've spent 2,000 yuan on Pop Mart this month. Labubu is trending on TikTok. The Labubu x Vans collab is trading at a 1,284% premium on secondary markets. Want to increase your position in designer toys?"

This represents a generational leap beyond chatbots that merely answer questions (like BloombergGPT or the in-development Morgan Stanley GPT) or smart tools requiring manual operation (like the original RockFlow).

In Vakee's view, Agents aren't app upgrades — they're the next-generation user interface.

She goes even further: "All apps will eventually disappear, replaced by Agents."

More radically, tell Bobby "I hate Donald Trump," and based on your attitude toward him, Bobby will suggest avoiding or shorting Trump-linked stocks (like DJT), while recommending long positions in clean energy given his pro-fossil-fuel policy stance. It asks about your investment expectations, then selects assets matching your risk appetite and return targets.

A person's emotions and values are becoming trading instructions.

This is precisely where Vakee's creation of Bobby began.

Vakee's love for trading is as natural as others' love of food or travel. For most people, investing is complex and intimidating. For her, every morning opens onto a world brimming with opportunities — accessible anytime, anywhere, effortlessly.

Take this past Lunar New Year, when DeepSeek exploded and even her relatives back home were chatting with AI. The RockFlow team quickly applied for DeepSeek-related services from cloud providers; Vakee immediately bought Alibaba, knowing its cloud business would inevitably benefit from open-source models' compute expansion demands.

On a trip to Japan, she noticed Sagami's ultra-thin condoms were sold out at every convenience store shelf. She researched the company, discovering its polyurethane ultra-thin innovation predated Okamoto's and was topping cross-border e-commerce platforms. That position ultimately returned 4x that year.

Trading is a lifestyle. Vakee believes this without doubt.

She shuns indulgence, shopping daily on Pinduoduo. Conversely, she's近乎狂热 about anything requiring training, challenge, and pushing limits. She loves the rush of short-term projects — passing the bar exam in nine days, scoring highest in her class for the prestigious U.S. ACE personal trainer certification.

Then she turned that passion to AI. For the past decade, she was either building AI products, investing in AI, or founding AI companies.

Now Vakee has finally found a worthy new boss: Bobby.

The RockFlow team skews introverted; team bonding means sitting in silence, staring at the sky

When we met Vakee, the tariff war had just begun. In the café, panicked market sentiment surged through everyone's phone screens like electric current.

"What can Bobby do now?" I asked.

"Bobby, find companies least affected by tariffs with outperformance potential over the next three months," Vakee said.

Seconds later, Bobby responded:

"Consider tariff-exempt sectors like AI infrastructure, data centers, and semiconductor manufacturing equipment — strategically competitive domains likely to receive partial exemptions or delayed implementation. U.S.-based production leaders also show outperformance potential, as domestic manufacturing circumvents import tariffs."

"Additionally, consider allocating to demand-inelastic and defensive sector leaders. See the tariff-resilient stock list."

Then it proactively asked: "Should I auto-place orders if any of these stocks drop over 10% within a week?"

In the AI era, some use large models for videos and PowerPoints; some replace relationships with DeepSeek chats; others want to raise an immortal AI cat.

But Vakee believes future trading will be AI versus AI — so everyone needs a Bobby.

Conversation with Vakee

Part 01

About Bobby

AI Has No Humanity, So It Makes Money

AI NOW!: Many financial products have integrated large models today — Bloomberg's BloombergGPT, Morgan Stanley's developing AI assistant GPT Copilot. What's the difference between Bobby and them? A chatbot that can place orders?

Vakee: If Bobby were just a chatbot with order functionality, I wouldn't have built it. Have you ever asked those financial chatbots "What should I buy now?"

AI NOW!: They analyze markets, give some advice, then inevitably add "investment involves risks."

Vakee: Exactly — because they're answering, not deciding. Bobby is different. Say "I hate Donald Trump" — it won't give you a summary of "Trump's policy impact on markets." It'll directly ask: "Should I exclude Republican-linked stocks? Detected potential clean energy benefits; here are specific targets. Adjust position?"

AI NOW!: Is this more advanced semantic understanding?

Vakee: No, completely different logic. Chatbots are Q&A: you ask, I answer. Bobby calculates before you ask. If it notices you've been reading semiconductor news but hold no chip stocks, it proactively asks: "Should I monitor TSMC earnings? If they beat, consider buying?"

You can also teach Bobby your own analytical logic.

AI NOW!: Sounds like Bobby solves the gap between a person's trading impulse and execution. Is this actually hard for ordinary users?

Vakee: For many, yes. Take this recent U.S. market drop — before tariffs, everyone knew a crash was highly probable. But pinpointing the exact timing, and what to sell how much, requires diligent research tracking details to act correctly. Most people have ideas but no execution — either lazy, or unsure how to operate.

Even the simplest strategy — buy low, sell high — many fail at. When you're up 30%, most won't sell, hoping for 50%. No timely profit-taking, then a sharp drop. Once dropping, panic selling. AI won't, because AI has no humanity.

AI NOW!: Can you not make money in markets with humanity?

Vakee: Humanity contains greed, anger, delusion. Going against human nature makes money in markets — so AI definitely makes money better.

AI NOW!: What if I said: Bobby, adjust my portfolio for zero risk, 100% returns?

Vakee: See — that's greed, haha. Bobby will honestly say "impossible," then translate your get-rich-quick fantasy into an executable 20% annualized plan.

AI NOW!: But doesn't a trading Agent carry too much trust cost? A PowerPoint Agent can be fixed if wrong; worst case, it's wrong. Won't users worry about an Agent losing them money?

Vakee: We built in safety words. You can say "Bobby, monitor only, no trades," "Call me if NVIDIA hits $98," or "No single trade over $10,000." Most people actually feel more reassured after trying it — same reason: AI has no human weaknesses.

Part 02

About Entrepreneurship

From Day One, Training an AI Trader

AI NOW!: Your first startup was RockFlow, a Gen Z brokerage platform. On that foundation — was Bobby absolutely necessary, or is it because everyone's jumping into AI Agents this year?

Vakee: RockFlow's vision from day one was "make investing simpler." For two years we tried everything — making the app extremely simple. But it wasn't enough.

By 2025, I believe new-generation users, especially AI natives, can absolutely trade through natural language. You speak; Bobby rapidly executes intent decomposition, strategy generation, through order execution.

RockFlow's early NFT avatar design sketches

AI NOW!: Many brokerages now integrate general-purpose large models for investment advice. Why didn't you just add a chat window to RockFlow — plug in DeepSeek for stock picking? That seems like the most natural upgrade path.

Vakee: General models provide standardized analysis, but that's far from sufficient for real trading. When we need personalized research based on each user's needs and preferences, with real-time requirements guiding immediate execution, general models fail. They can only batch-pass searched information to users, unable to complete true decision loops.

Bobby uses workflow + LLM/Agent architecture, maximizing AI creativity while controlling cost and risk.

Crucially, all information in our workflow — user data, market price/volume data, capital market sentiment — undergoes secondary processing with our professional know-how. Only then can we generate responses that are both sound and truly user-understanding, ultimately completing trade execution.

AI NOW!: Many general Agents are also integrating vertical domain knowledge bases. Coze Space claims to connect with expert systems. Why do you insist vertical Agents like Bobby are the future, rather than waiting for general Agents to grow stronger?

Vakee: This comes down to a fundamental question: there are two types of needs.

First, life-or-death needs. Financial trading, medical diagnosis — most people can't score 70/100, and scoring below 70 equals zero, because consequences are severe. These tasks have extremely high professional barriers, extremely low error tolerance — yet clear methodological paths to 70/100.

Second, nice-to-have needs. Making PowerPoints, travel itineraries — ordinary people scoring below 70 is fine; it's just less than perfect.

General Agents suit the second type. But life-or-death needs like financial trading require vertical Agents. Several reasons:

Data dimensions differ: We process millisecond-level market data, real-time user positions, and other professional information

Liability levels differ: One wrong investment recommendation can cause major user losses

Decision mechanisms differ: Not "maybe possibly" suggestions, but executable judgments

AI NOW!: Like you wouldn't let a general practitioner do heart surgery?

Vakee: Right — you wouldn't dare. Bobby was born a "finance major"; every judgment rests on professional trader-level training.

AI NOW!: Many think workflow can only handle simple query-type narrow tasks. How do you make Bobby truly "understand finance"?

Vakee: Workflow is just a tool; what matters is how you use it.

Industry knowledge is foundational. The real breakthrough: we make workflow dynamically generate trading information most relevant to the user's current moment — risk appetite, real-time positions, trading intent, market sentiment — combined with our accumulated financial know-how, instantly composed through thousands of dynamic nodes. This isn't simple information retrieval; it's like a professional trader parsing and responding to market signals in real time. In RockFlow's validated investment scenarios, this system's execution efficiency exceeds general large models by orders of magnitude.

Our ideal model: build a data-driven, auto-evolving world model, enabling financial decisions to continuously learn and adapt in dynamic markets, achieving true intelligence and efficiency.

AI NOW!: What about the "understand user" side? How does Bobby know who you are and what you want?

Vakee: Bobby connects to RockFlow's counter trading system, real-time market data, and user data — like a hedge fund manager on 24-hour standby.

For example, when a user says "I just got laid off, want stable investing," Bobby automatically lowers risk appetite, recommends treasury bonds + high-dividend stocks, and sets dynamic stop-losses. It might proactively ask during market volatility: "Detected potential Fed rate hike — adjust bond position?"

AI NOW!: If vertical financial Agents are the future, why haven't Robinhood, Futu Holdings Limited, and others moved in this direction?

Vakee: The AI-native investment platform experience requires fundamentally different technical architecture from mobile internet brokerages from day one. The more successful incumbent peers, the harder to abandon all legacy infrastructure and user experience for AI-era self-revolution.

The previous generation's mission was delivering excellent mobile client experiences — massive improvement over PC-era incumbents like Interactive Brokers. They did this well, satisfying 70s and 80s-born users. But in the AI era, GenZ and younger users have new investment experience demands.

RockFlow's difference: from day one, we explicitly targeted new-generation investors with an AI-native wealth management platform, building our own AI infrastructure and AI-training-suitable counter trading system. We're the only ones doing this globally.

AI NOW!: Wait — what does building your own counter trading system mean?

Vakee: For brokerages, the counter trading system is like Douyin's recommendation algorithm. Using someone else's system is a black box; not every module opens for model training. So we had to build our own. Only then can we obtain structured, continuous user behavior data from the foundation, understand real decision paths, and continuously optimize based on feedback.

When we first designed RockFlow's counter trading system, we already considered how each module would do machine learning. This data isn't static assets — it's raw material for training each person's personalized Bobby.

Part 03

About AI

Kill the App: Agent Is the Ultimate Evolution of All Services

AI NOW!: Sounds like you were preparing for Agents from day one.

Vakee: I checked — our first Bobby meeting notes are from September 2023. We designed RockFlow's entire system AI-native from the start, including trading system, data, and product architecture. But thinking clarified gradually; we took detours in Agent architecture design too — all valuable experience.

Every generation of user-facing endpoint products has its historical mission. In the AI era, your product's mission definitely isn't slightly richer features, slightly simpler design interaction, adding or removing a button.

AI NOW!: What's the AI-era product's mission?

Vakee: I believe it's the first real possibility to understand users and proactively serve them. Mobile internet's good products let users "operate more efficiently"; the AI era lets users not operate — directly receive service.

So on the app, it might guide you step-by-step "how to buy options," "how to find suitable options." But today AI directly recognizes your intent — "I want 20% investment returns," "I want to survive this market crash." This is a fundamentally revolutionary paradigm shift.

So I believe Agent isn't an app upgrade; it's the next-generation user interface.

AI NOW!: Specifically, what's Bobby's mission?

Vakee: My original intention is believing investing is highly personalized — it's completely a comprehensive expression of one's values and worldview.

As we discussed, many people have ideas; they have various perceptions of daily events. But they're trapped by operational details, unable to act correctly and timely. People often say trading is cognition monetization — but for most, the biggest difficulty is going from cognition to trading; they don't know how. Bobby exists to solve this.

AI NOW!: Whether I hate or like Donald Trump, I can trade on it.

Vakee: All tradable, all profitable.

AI NOW!: From operating a tool, to being served by an agent.

Vakee: Right. In this sense, all apps will disappear in the future, replaced by Agents.

AI NOW!: I believe this future too. But aren't you worried you're too early — becoming an industry pioneer (martyr)?

Vakee: I don't think that way. For ten years, I've either invested in AI or founded AI companies. All my experience determined that today I must do this one thing: Bobby. The brave enjoy the world first.

• Biggest AI shock of 2025

Vakee: When DeepSeek made its deep reasoning visible to everyone.

• In the past year, what in AI did you initially dismiss but completely changed your mind?

Vakee: Text-to-image. Accurately generating images — consistent character poses, meaningful text — was extremely hard initially. Felt image generation was very far from commercialization. Then new tech and products from Diffusion Transformer onward were incredibly powerful, far exceeding expectations. Now image generation is fully usable across production scenarios.

• If you could personally shut down one AI product or trend — something you think is completely pseudo-demand or wrong direction — which would you choose?

Vakee: Building general features on top of OpenAI-type companies, or products not deeply integrated into business scenario closed loops — all difficult. OpenAI's new models easily disrupt them. When GPT-4o's one-click Ghibli style came out, many startups died; they hadn't figured out how to build business moats.

So for me, what matters isn't "am I using AI," but "what problem am I solving" — whether you can abstract needs in vertical scenarios while considering long-term commercial value and business barriers. The industry currently lacks more excellent AI product managers.

So returning to Bobby: building Bobby isn't to show off AI tech, but to make investing simpler, to create value. If one day I find Bobby isn't achieving this, it can absolutely be killed too — no need for attachment.

• At AI's current stage, what's undervalued? What's overvalued?

Vakee: Compute demand is undervalued; AGI arrival is overvalued. Everyone now thinks stacking more GPUs, training larger parameter models gets you to AGI. But the real bottleneck is actually the application layer — I believe the coming years will be vertical Agent explosion, and this is a very long-term process. Each vertical needs customized compute optimization. Like EVs after普及: charging stations are the real bottleneck.

• What are you most looking forward to in 2025?

Vakee: The "Cambrian explosion" in vertical applications. In complex scenarios like finance, healthcare, education, travel, and supply chain, Agents will truly重构 user experiences emerge — not just simple chatbots.

For example, travel Agents that automatically complete personalized trip planning, negotiation, and payment; or education Agents that customize learning paths based on ability and preferences. None of these require waiting for AGI; existing tech plus vertical data can achieve them.

• Finally, recommend three favorite books!

Vakee: Richard Feynman's The Pleasure of Finding Things Out, Dzongsar Jamyang Khyentse Rinpoche's What Makes You Not a Buddhist, and Ezra Vogel's Deng Xiaoping and the Transformation of China.

Image sources | Provided by interview subject, Unsplash