Wall Street Pays Ex-Workers $25K a Day as AI Trainers
▼ Summary
– Two former investment bankers, Felipe Sinisterra and Dave Wang, charge up to $25,000 a day to teach senior bank staff how to use AI tools their employers already own, and are fully booked for two months.
– Their clients include T. Rowe Price, Citigroup, and Bank of America, reflecting a gap between billions spent on AI infrastructure and actual workforce proficiency.
– The training covers practical tasks like analyzing video pitches with Gemini, earnings interpretation, and due-diligence synthesis, using commercial models such as Claude, ChatGPT, and Gemini.
– The $25,000 daily rate signals to procurement that the cost is negligible compared to a managing director’s quarterly fees, and outpaces big-four consulting firms for similar training.
– The value of their service may decline as vendors like Anthropic push plug-and-play financial workflows, though the pair stay relevant by teaching novel, undocumented use cases.
Two former investment bankers are now commanding $25,000 a day to teach senior staff at major financial institutions how to actually use the AI tools their employers have already purchased. Felipe Sinisterra and Dave Wang, both ex-bankers, are fully booked for the next two months, according to a recent Bloomberg feature.
Clients so far include T. Rowe Price, Citigroup, and Bank of America, the report said. On the surface, the premise of their work is embarrassing for the broader industry. Global banks have spent the past two years pouring billions into AI infrastructure, model licenses, and internal tooling, betting that generative AI will reshape financial workflows.
What Sinisterra and Wang are selling isn’t new technology. It’s the working knowledge of how to use what is already installed. In demonstrations, they show senior bankers how to deploy commercial models like Anthropic’s Claude, OpenAI’s ChatGPT, and Google’s Gemini for tasks the bank’s own staff haven’t figured out. In one session described by Bloomberg, the pair used Gemini’s video-understanding mode to analyze a video pitch from a startup founder.
The credibility behind the steep price tag comes from the founders’ own pre-consultant careers. Sinisterra worked at Goldman Sachs and Bank of America before leading fintech investments at SoftBank, where he deployed $2 billion and incubated several AI ventures. Wang was at Morgan Stanley and led crypto for SoftBank Latin America; he now sits on the Harvard Data Science Initiative’s advisory board. Sinisterra runs the training business under the banner of Wall Street Prompt.
The shape of demand tells its own story. Banks are not, based on the booking calendar, struggling with model access. They are struggling with the granular, ground-level work that the McKinsey-style AI strategy decks of 2023 and 2024 left out: fitting probabilistic tools to a profession built on deterministic outputs.
Earnings interpretation, market-analysis prompting, due-diligence synthesis, and pitch-deck review are all areas where, according to Sinisterra and Wang, most analyst desks are operating at a small fraction of what the underlying tools can do.
The price point itself does a particular kind of signaling work. A $25,000 day rate roughly matches what a single managing director at a large US investment bank generates in fees in a quarter. It signals to procurement that the cost is too small to bother negotiating. It also outpaces what big-four consulting firms charge for comparable training engagements, consistent with a broader shift toward smaller, faster, ex-practitioner consultancies pulling work out of the McKinsey-Bain-BCG envelope on AI-specific mandates.
The longer-term question is whether the trainer category compresses. Anthropic itself has been actively pushing into financial services since early 2026, including a Moody’s data partnership and full Microsoft 365 integration. As model vendors move closer to delivering plug-and-play financial workflows, the value of a bespoke prompting tutorial naturally declines.
Sinisterra and Wang have so far stayed ahead by emphasizing live, novel use cases that vendor documentation does not yet cover. How long that gap stays open is a different question. For now, the two-month waitlist is what banks are paying for. The actual training, as several recent client testimonials note, can be replicated by a moderately curious analyst with a corporate ChatGPT license and a weekend.
(Source: The Next Web)
