How to Earn 170,000 with One AI Class: Wall Street Elites Queue Up to Pay

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2026-06-07 11:10:13 Source: Quantum Bit

Citigroup and JPMorgan are both clients

Kelsey, from the Hollow Temple

Quantum Bit | Official Account QbitAI

Two young men in their early thirties are charging Wall Street $25,000 per class—equivalent to about ¥170,000 in Chinese yuan—by leveraging AI.

They set up a stage in the office of a New York venture‑capital fund, first demonstrating a method that uses AI to analyze founders’ pitch‑deck videos.

Next, they fed recordings of earnings‑call transcripts into an AI, extracted the few sentences most likely to move the stock price from tens of thousands of words, and de‑constructed the management’s vague language into concrete numbers that could be plugged into a financial model.

△ Image generated by AI

After the two demos, the $25,000 was collected.

The payment came from top-tier financial institutions such as Citigroup, JPMorgan, and T. Rowe Price.

These firms have poured billions into AI, bought a slew of tools, yet found their staff clueless about how to use them.

So they hired these two people to fill that gap.

One AI Class, ¥170,000 in Hand

The company that immediately demanded $25,000 from Wall Street is called Wall Street Prompt. It was founded by two young men: Felipe Sinisterra and Dave Wang.

Sinisterra is Colombian, immigrated to the U.S. with his parents at six. After graduating, he worked as an engineer at Facebook, sitting just six meters from Mark Zuckerberg. He later moved to Goldman Sachs and JPMorgan, then joined SoftBank’s Latin‑American fund as the fintech lead, managing over $1.5 billion in investments.

Wang was born in New York and moved to Ohio at eight. While at Harvard, he promoted a ride‑hailing company on campus, wrote scripts to scrape student emails from nearby universities, mass‑sent targeted discount codes, and earned tuition through referral commissions.

After graduation, Wang joined Morgan Stanley, later joined the same SoftBank fund, led crypto investments, then left to start a digital‑asset fund that earned a tidy profit for investors before selling it and moving on.

During their time at SoftBank, the two developed a workflow for using AI to make investment decisions. Wang later said it was the best‑returning year of his career and that he should devote 100 % of his time to it.

In the summer of 2025, they flew to San Francisco, rented a shared apartment, and spent time in a nearby co‑working space writing newsletters and posting content.

They originally wanted to build a data business, but the audience that stayed—hedge‑fund managers and financial analysts—didn’t care about their data. Instead, they wanted the two to teach them how to use AI.

“We have the tools, but we don’t know how to use them.” That line has been repeated by many people.

That realization made them understand that the demand they had found was not what they had imagined.

So in July 2025, Wall Street Prompt was officially launched. Within two months, the first major client reached out.

They booked tickets, took a two‑hour train to the client’s headquarters, opened the conference room, and found the equity, fixed‑income, and macro teams all present, waiting for them to start.

After that session, the client immediately asked for another meeting.

Later, Citigroup and JPMorgan also invited them to run exclusive sessions for external fund clients, and T. Rowe Price brought them in to train their own investment teams.

In short, almost every client who has taken their class has become a repeat customer.

Wall Street Employees Grapple with AI Anxiety

Wall Street’s attitude toward AI has truly flipped only in the last couple of years.

When ChatGPT first launched in 2022, major financial institutions immediately blocked it on internal networks, citing security risks.

Soon after, they started “falling in love” with it, rushing to pour money into AI.

JPMorgan rolled out its own LLM Suite to nearly all employees; Goldman Sachs partnered with Anthropic to develop an AI Agent; JPMorgan claimed that its 18,000 developers had seen a 20 %–25 % productivity boost after adopting AI.

Money was being spent, but cracks began to appear.

Average bank staff’s AI skills lagged far behind. Many couldn’t use it at all, while others were still tinkering with last year’s outdated versions.

On one side, executives were pushing hard; on the other, front‑line staff couldn’t keep up. This gap created a collective anxiety within banks.

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This anxiety is starkly reflected in layoff numbers.

Citigroup, Wells Fargo, and JPMorgan collectively cut more than 5,000 jobs in Q1 2026, while their earnings hit record highs during the same period.

The more money they made, the more positions disappeared.

For anyone working at a bank, this signal was crystal clear: a strong balance sheet is no longer a job‑safety net.

For those caught in this storm, learning AI is no longer optional; avoiding obsolescence means mastering it.

This pervasive industry anxiety provided the richest soil for Sinisterra and Wang.

Banks bought tools, employees didn’t know how to use them; employees knew they had to learn but didn’t know where to start; executives wanted to drive transformation but couldn’t find enough people who understood both finance and AI to lead it.

Sinisterra and Wang happened to have both sides: years of front‑line investment experience and a proven AI workflow in practice.

Thus, their classes became an outlet for the industry’s anxiety.

The AI Training Track Is Getting Crowded

The allure of this market has attracted others.

Multiverse, a London‑based professional‑skills platform, promises to train 15,000 AI apprentices in two years, with clients including Citigroup, Microsoft, and KPMG.

Rogo Technologies, a New York startup founded by former Lazard and JPMorgan bankers, specializes in automated analyst research and due‑diligence software. It just closed a Series D round, raising $160 million at a $2 billion valuation.

In short, more and more people are eyeing the same problem, and the track is becoming crowded.

Sinisterra and Wang’s response is to deepen their moat.

They built an AI Agent library specifically tuned to the mindset of financial institutions, aiming to let AI shoulder 90 % of transactional and technical work, freeing humans to make judgments, nurture relationships, and make the decisions that truly impact returns.

At the same time, they are moving their classes online, offering a live session priced at about $1,500 per person for individual finance professionals who feel they haven’t learned enough AI and can’t afford corporate‑level training.

They’re even considering relocating to Singapore, where AI anxiety is even more intense, to push the business forward.

Reference links:

https://www.bloomberg.com/news/features/2026-05-25/the-ai-trainers-charging-25-000-a-day-to-push-wall-street-s-agentic-shift

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