Citibank and Bank of America are both clients.
Author and source: Quantum Bit
Two young men in their early thirties are charging Wall Street $25,000 per lesson, equivalent to 170,000 RMB.
They set up a booth in the office of a venture capital fund in New York and first demonstrated a method using AI to analyze pitch videos of startup founders.
Next is the second set: they feed the transcripts of earnings call recordings into AI, extracting the few sentences most likely to move the stock price from tens of thousands of words, and then deconstructing management’s vague phrasing into specific numbers that can be plugged into financial models.
Image generated by AI
After both demonstrations were completed, they took the $25,000.
The institutions footing the $250,000 are top-tier financial firms such as Citibank, Bank of America, and T. Rowe Price.
These organizations have spent billions on AI and bought a multitude of tools, only to find that their employees don’t know how to use them.
So they invited these two individuals to help their people learn this lesson.
An AI course, earn 170,000
The company that immediately asked Wall Street for $25,000 is called Wall Street Prompt, founded by two young men, Felipe Sinisterra and Dave Wang.
Sinisterra is Colombian and moved to the United States with his parents at the age of six.
After graduating from university, he worked as an engineer at Facebook, with his desk just six meters away from Zuckerberg. He later switched careers to join Goldman Sachs and Bank of America, and subsequently joined the SoftBank Latin America Fund as head of fintech, overseeing investments exceeding $1.5 billion.
Wang was born in New York and moved to Ohio at the age of eight.
While studying at Harvard, he conducted campus promotions for a ride-hailing company, wrote scripts to scrape student email addresses from nearby universities, and sent targeted discount codes, earning enough referral commissions to cover his tuition.
After graduation, Wang joined Morgan Stanley, then moved to the same SoftBank fund where he led cryptocurrency investments. After leaving, he founded his own digital assets fund, generated strong returns for investors, and sold the fund before moving on.
During their time working together at SoftBank, each developed a workflow for using AI to make investment decisions. Wang later said that was the most rewarding year of his career and felt he should dedicate 100% of his time to it.
In the summer of 2025, the two flew to San Francisco, rented an apartment together, and spent their days hunched over in a nearby co-working space, writing newsletters and posting content.
They originally intended to run a data business, but the readers who stayed—hedge fund managers and financial analysts—weren’t interested in their data; instead, they expected the two to teach them how to use AI.
“We have the tools, we just don’t know how to use them.” We’ve heard this too many times from different people.
This made the two realize that the requirement they had found was not the one they thought they were seeking when they started.
In July 2025, Wall Street Prompt was officially established. Less than two months later, its first major client came knocking.
Two people booked tickets and took a two-hour train ride to the other company’s headquarters. When they walked into the meeting room, they found that the equities, fixed income, and macro teams were all present and waiting for them to begin.
After that talk, the other person immediately asked if we could schedule another meeting.
Later, Citibank and Bank of America invited them to conduct exclusive sessions for their external fund clients, and T. Rowe Price even brought them in to train their own investment team.
In short, almost all customers who attended their classes became repeat customers.
Wall Street employees are trapped in AI anxiety
Wall Street's attitude toward AI has only completely reversed over the past two years.
When ChatGPT was first released in 2022, the initial response from major financial institutions was to block it, prohibiting access on internal networks due to security concerns.
But soon after, these institutions began to enthusiastically embrace AI, rushing to invest heavily in it.
JPMorgan Chase has rolled out its LLM Suite to nearly all employees, Goldman Sachs is collaborating with Anthropic to develop AI agents, and Bank of America claims that its 18,000 developers have seen a 20% to 25% increase in productivity after adopting AI.
Money has been poured in, but the cracks have also emerged.
The AI skills of regular bank employees have far lagged behind—they either don’t know how to use it at all or are still struggling with last year’s outdated version.
On one side, senior management is pushing hard; on the other, frontline employees are struggling to keep up—this gap has plunged the bank into collective anxiety.
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This anxiety is even more plainly reflected in the numbers of layoffs.
Citibank, Wells Fargo, and Bank of America collectively laid off more than 5,000 employees in the first quarter of 2026, while all three banks reported record-breaking financial performance during the same period.
Earnings are increasing, but jobs are disappearing at the same time.
This signal is clear enough for everyone working in a bank: a strong balance sheet is no longer a guarantee of job security.
For those caught in this storm, learning AI is no longer about advancement—it’s essential just to avoid being left behind.
It was this pervasive anxiety throughout the industry that provided Sinisterra and Wang with the most fertile ground.
The bank bought tools, but employees don’t know how to use them; employees know they must learn, but don’t know where to start; executives want to drive transformation but can’t find enough people who understand both financial operations and AI to lead the effort.
Sinisterra and Wang uniquely possess both years of frontline investment experience and proven, real-world implementation of AI workflows.
Thus, their classes became an outlet for the industry's anxiety.
The AI training sector is becoming increasingly crowded.
The scent drifting through this market has certainly been noticed by others as well.
Multiverse is a London-based professional skills training platform that promises to train 15,000 AI apprentices within two years, with clients including Citigroup, Microsoft, and KPMG.
Rogo Technologies is a New York-based startup founded by former bankers from Lazard and JPMorgan Chase, specializing in software that automates analyst research and due diligence. This year, the company completed its Series D funding round, raising $160 million at a $2 billion valuation.
In short, more and more people are focusing on the same issue, and this space is becoming increasingly crowded.
Sinisterra and Wang’s response was to deepen their moat even further.
They built a library of AI agents specifically designed to understand the mindset of financial institutions, aiming to have AI handle 90% of routine and technical tasks, freeing people to focus on judgment, relationship management, and making the decisions that truly impact returns.
At the same time, they are moving their classes online, developing live courses priced at approximately $1,500 per person for individual finance professionals who feel they haven’t learned enough about AI and can’t afford corporate training programs.
The two were even considering moving to Singapore, where AI anxiety runs even hotter, to take their business one step further.