Felipe Sinisterra and Dave Wang have been making big money by telling Wall Street bankers what’s missing from their artificial intelligence plans.
One afternoon in March, the two coaches — today one of the most sought after in the financial market — gave a class to employees of a venture capital fund in New York. Wang, 31, showed how Gemini, an AI model developed by Alphabet’s Google, can be used to analyze videos of founder presentations. He demonstrated how a web application that incorporates behavioral analysis methods used by the FBI helps compare transcripts with visual cues, such as body language and facial expressions, to identify potential “red flags.”
Next, Sinisterra, 30, led the class step by step to scour transcripts of earnings conference calls with ChatGPT, from OpenAI, and Claude, from Anthropic, in search of the most relevant phrases for the market. The machine performed sentiment analysis and translated management’s statements into numerical entries in a spreadsheet, used to project future results. Attendees were able to see how AI can simplify some of the most labor-intensive parts of their everyday lives.
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The bill for the class? US$25 thousand. And the schedule is full for the next two months.
“What is happening now is that people see AI as a source of advantage, of attack,” said Sinisterra. “In the future, what we will see is that people will see it as a necessity.”
Big banks, gripped by anxiety around AI, are rushing to hire more artificial intelligence experts and reduce traditional banking functions. Standard Chartered is preparing to cut thousands of support positions over the next four years. Citigroup, Wells Fargo and Bank of America together eliminated more than 5,000 jobs in the first quarter of 2026 alone, despite a record earnings season.
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Top executives, willing to spend heavily to apply technology far beyond basic tasks, are experimenting with AI tools themselves, increasing the pressure to embed the technology throughout the hierarchy. Sinisterra and Wang, former SoftBank fund managers, sell confidence and fluency to firms hungry for this transformation.
Wall Street Prompt, a company they founded in July 2025, has worked with T. Rowe Price, Citigroup and Bank of America, according to people familiar with the matter. T. Rowe Price hired the pair to train its investment professionals, these sources say. Citigroup and Bank of America have used them to conduct sessions with external fund clients. Bound by confidentiality agreements, Wall Street Prompt declined to confirm its client list. T. Rowe Price, Citigroup and Bank of America also did not comment on training with specific suppliers.
The qualification bar is rising
Financial institutions haven’t always been enthusiastic about AI. In 2022, when ChatGPT was launched, large global banks restricted access to the chatbot on their internal networks for fear of security breaches.
JPMorgan has since launched the LLM Suite, a generative AI tool used by most employees. Goldman Sachs works with Anthropic to develop AI agents. Bank of America says its 18,000 developers have become 20% to 25% more productive using artificial intelligence.
“What’s happening now is that people see AI as a source of advantage, of attack.”
Still, many bankers lack the training to use these tools effectively, while others are stuck with outdated models — a combination that has created space for trainers capable of getting the most out of AI systems.
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“The biggest challenge within a big bank isn’t the technology, it’s the people,” said Jake Bridge, managing director for Asia-Pacific at Evolution, a British technology recruitment company. “The scale goes from Luddite to AI super-adopter; the biggest problem in a bank is: how to serve both profiles at the same time?”
Asia is at the forefront of incorporating AI into banking and finance, with payments, credit and customer service increasingly automated.
Especially in Singapore, fluency in AI is becoming a prerequisite for anyone wanting to pursue a career in the sector. The country leads the ranking of 174 nations in the International Monetary Fund’s (IMF) AI Readiness Index, and 64% of financial institutions already use AI in key business functions, according to a 2026 survey by Finastra, a London-based financial software company.
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Wang and Sinisterra are now considering whether to move there to take advantage of the demand from banks and professionals looking to protect their positions and maintain employability.
Duncan, 55, who lives in Singapore and preferred not to have his last name used, spent nights and weekends last year in a class supported by Nanyang Technological University practicing using AI. His employer, a large bank, had previously moved operations from Singapore to a cheaper hub overseas.
After being unemployed for nine months, he got a back office job at a local bank last month and now says he is confident with his new skills.
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As many executives attribute productivity gains to AI, fears are growing that solid balance sheets are no longer enough to guarantee job security. The analyst position is not likely to disappear, but tends to “tune” from the bottom up, says Igor Sydorenko, CEO of Neurons, an AI consultancy whose clients include HSBC and AXA. “Highly qualified people, with AI tools, will be able to do 10, 20 times more, much better, much faster,” he said. “They won’t need junior analysts, associates. They will do everything themselves.”
Justin Tang, who lives in Singapore, knows the anxiety of trying to close that gap. Analyst buy-side At hedge fund Regal Funds Management, he spent three years trying to learn AI on his own, in between breaks during the day: on buses, between meetings, in those minutes when most people are scrolling on their phones. Last year, he met Wang and Sinisterra. “It was like turning on a light bulb,” Tang said. “Before, I would take hours to analyze a company. Now, I put a prompt and in 90 seconds I get the key points: what the company does, what the profit drivers are, what the narrative is.”
Since then, Tang has attended several Wall Street Prompt trainings, including one hosted by Bank of America. Each class brings together 20 to 30 people, according to him, with the places covered by the host bank.
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“It didn’t surprise me when the big banks started offering Wall Street Prompt classes to clients like us,” he said. “The question was more about when, not if it would happen.”
Tang says he mainly uses the techniques he learned for personal purposes, but he also uses them at work. At Regal, limit the use of tools to public materials, such as filings and transcripts of results. Customer data does not enter the system.
Children of immigrants
Sinisterra and Wang got involved in finance from an early age, always leaning towards technology. Sinisterra moved from Colombia to the United States with her parents when she was six years old. Wang was born in New York to Chinese parents who emigrated in the 1980s.
Wang says he sold scripts for the online game RuneScape around the time he moved to Ohio at age eight. As an undergraduate at Harvard, he was one of five students recruited by Lyft to promote the company’s expansion in Boston by handing out cards on the street. Instead of limiting himself to that, he says he pulled emails from students at local universities, ran mail-merge and created personalized coupons — generating enough referrals to pay for college itself.
After interning at Blackstone Inc. in 2016 and working for more than two years at Morgan Stanley starting in 2017, he joined SoftBank’s Latin America Fund in 2019, where he led crypto investments. He left around two and a half years later, founded 99 Capital, a digital asset manager, sold his managing partner stake and left the fund after delivering robust returns to investors.
“It was very obvious to me,” Wang said. “If I was spending like 30% of my time developing playbooks of AI and this was clearly the best return year of my career, that’s where I should be dedicating 100% of my time.”
Sinisterra, in turn, joined Facebook as a software engineer right after college — according to him, his desk was about six meters away from Mark Zuckerberg’s. He then worked at Goldman Sachs and Bank of America, until joining SoftBank in 2019 as head of fintech, helping to apply more than US$1.5 billion in investments.
Working side by side at the Japanese technology conglomerate, the two talked all the time, each developing their own playbook by AI.
Wang left SoftBank in 2022 and Sinisterra in 2023. In the summer of 2025, they spent a month in San Francisco, sharing an apartment and working in a coworkingwhile publishing newsletters and texts about AI and finance. The most loyal readers were hedge fund managers and financial analysts. The initial plan was to set up a data business, but the opportunity in education proved more attractive, they say.
“People said: we have the tools, we just don’t know how to use them like you do”, recalled Sinisterra. “They wanted to learn, not buy more software.”
Two months after the founding of Wall Street Prompt, in July 2025, a large manager approached them. The pair took a two-hour train from New York to the firm’s headquarters, where they trained equity, fixed-income and macro teams, according to people familiar with the meeting. Participants ranged from senior strategists to junior analysts.
Nearly all clients returned for additional sessions, Sinisterra said, including one fund with more than $50 billion in assets that is currently negotiating a contract. He didn’t want to say the name.
Wang and Sinisterra also continue to adjust their own model to maintain their competitive advantage. They assembled a library of AI agents trained to understand how an investment house thinks. The goal, they say, is to have AI take care of 90% of the logistical and technical work, freeing people for relationship, judgment and decision-making tasks — those that really move the result.
The field, however, is becoming more competitive. Multiverse, a British training platform founded by Euan Blair, son of former Prime Minister Tony Blair, has committed to training 15,000 “AI learners” in two years, with clients including Citigroup, Microsoft and KPMG. Rogo Technologies, a New York startup founded by former Lazard and JPMorgan bankers, raised $160 million in a Series D round, at a valuation of $2 billion, for software that automates research and due diligence that previously consumed an analyst’s day.
Sinisterra and Wang are now working on a webinars live for finance professionals who feel unprepared in AI and are willing to pay around $1,500 each.
“What people are really buying is transformation, not just prompts or ready-made models,” said Sinisterra. “What we do is arrive and ignite this change. Everyone is already thinking about these transformations — they just don’t know which direction to go in.”
© 2026 Bloomberg L.P.
