Charging $25,000 a day, two former fund managers conquer Wall Street with AI financial training

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AI training company Wall Street Prompt, founded by two former SoftBank fund managers, charges financial institutions $25,000 per day for training, with a current waiting list of two months. (Background: Anthropic report: In the 2028 battle for AI supremacy, the US risks being overtaken by China if it fails to maintain its computing power advantage) (Context: University of California research on the "AI brain fog" phenomenon: 14% of office workers driven crazy by Agents and automation, with intent to resign 40% higher) According to reports, Felipe Sinisterra and Dave Wang co-founded Wall Street Prompt in July 2025, both having previously held key investment positions at SoftBank's Latin America fund. $25,000 a day, with a two-month waiting list. This is the price tag two former fund managers in their early thirties have set by teaching Wall Street bankers how to use AI tools. According to Bloomberg, their courses don't discuss model principles, but focus on how to embed AI directly into financial analysts' daily work — scanning earnings call transcripts, comparing whether founders' body language matches their verbal expressions, and converting management statements into financial forecast figures. Major banks are advancing their AI deployment in two directions simultaneously: cutting traditional positions on one hand, while spending heavily to teach remaining staff how to use AI on the other. In Q1 2026, Citigroup, Wells Fargo, and Bank of America collectively laid off over 5,000 employees, yet all three banks reported record profits in the same quarter. Standard Chartered announced it will cut thousands of support positions over the next four years. JPMorgan's 2026 technology budget reached $19.8 billion, with CEO Jamie Dimon clearly stating that the bank will hire more AI specialists and fewer traditional bankers going forward. Analysts estimate that major banks combined could lay off as many as 200,000 employees over the next three to five years. Neurons Lab CEO Igor Sydorenko stated directly: highly skilled employees combined with AI tools can produce 10 to 20 times the output of the past. He said, "They will no longer need any junior financial analysts or assistants — they can do it all themselves." This assessment is making bank employees from Singapore to New York uneasy. In 2022, when ChatGPT was first released, most major banks blocked the tool on internal networks citing security concerns. In less than four years, JPMorgan has deployed LLM Suite — a large language model toolkit for virtually all employees — across the bank; Goldman Sachs is partnering with Anthropic to develop AI agent systems capable of autonomously completing tasks, and has joined a $1.5 billion joint venture led by Anthropic together with Blackstone and H&F; Bank of America stated that its 18,000 developers experienced a 20% to 25% productivity increase after using AI. Bloomberg's report noted that Wall Street Prompt's client list includes T. Rowe Price, Citigroup, and Bank of America, though the company is bound by non-disclosure agreements and declined to publicly confirm. T. Rowe Price has arranged for the pair to provide training to its investment professionals; Citigroup and Bank of America have used them to host courses for external fund clients, with the banks footing the bill. Each course involves about 20 to 30 participants, and nearly all clients return for more. Currently, a fund managing over $50 billion in assets is finalizing a renewal contract. The backgrounds of Sinisterra and Wang explain why financial institutions are willing to pay this price. Wang previously worked at Blackstone and Morgan Stanley, led cryptocurrency investments after joining SoftBank, and later founded digital asset fund 99 Capital. Sinisterra, after graduating from university, first worked as a software engineer at Facebook, then moved to Goldman Sachs and Bank of America, and joined SoftBank in 2019 as head of fintech, helping deploy over $1.5 billion in investments. What they sell is not just technical operating skills, but financial-scenario intuition that investment institutions can "recognize." The two are also currently planning online live-streamed courses, priced at around $1,500, targeting financial practitioners who feel training resources are insufficient and cannot wait for institutional invitations. This is an attempt to bring "elite customized courses" down to the retail market, and also their second revenue line for building scalable income beyond traditional high-ticket business. Bloomberg noted that Asia leads the world in AI embedding within the financial industry, especially Singapore. According to the IMF's AI Preparedness Index, Singapore ranks first among 174 countries; financial software company Finastra's 2026 survey shows that 64% of Singapore's financial institutions have deployed AI in core business. Sinisterra and Wang are currently considering relocating to Singapore to directly serve the local market. The case of hedge fund analyst Justin Tang outlines the contours of this market demand. He spent three years self-studying AI at Regal Funds Management with little success; after meeting Wang and Sinisterra last year, company analyses that once took hours now produce a draft in 90 seconds. This time difference is exactly what Wall Street Prompt's paying customers are buying. Singapore provides another dimension of supporting evidence: 55-year-old Duncan, after being laid off due to bank outsourcing and unemployed for nine months, rebuilt his AI skills through a Nanyang Technological University course and ultimately found new employment at a local bank. His story shows that AI training is not just an offensive tool — it has also become a threshold for maintaining employment eligibility. The $25,000 daily training fee is essentially a liquidity premium that financial institutions are willing to pay to "shorten the learning curve." Sinisterra's words are direct: "What people are really paying for is transformation, not just prompts or templates." When AI evolves from a competitive advantage to an employment baseline, those who can accelerate this learning curve hold the business with the least worry about demand for some time to come.

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