AI Analyst for Pennies: 10 Prompts for Claude That Will Replace Expensive Consultants
The market for analytical services is undergoing a tectonic shift. A developer under the pseudonym Abhi AI has introduced a set of 10 specialized prompts that transform the Claude language model into a full-fledged stock and cryptocurrency market analyst. It is claimed that these queries can replace the functions of expensive consultants for stocks and digital assets. Importantly: the prompts themselves do not provide investment recommendations, but merely structure the research process.
The First Five: From Business Overview to Valuation
The first prompt places Claude in the role of a senior analyst and requires it to prepare a research report on a company or ticker that is understandable to a beginner. It covers the business model, revenue sources, industry trends, competitors, financial results, valuation, growth drivers, risks, and bull/base/bear scenarios. The query mandates reliance on fresh public sources, specifying dates, and clearly separating facts from assumptions.
The second prompt analyzes the company's latest earnings call: five main takeaways, changes in revenue, margins, management guidance, management tone, analyst concerns, pleasant and unpleasant surprises. Additionally, a table of key metrics is generated with the current and previous results and an explanation of why this is important.
The third prompt turns Claude into a skeptical analyst who looks for red flags in revenue quality, margins, cash flow, debt, dilution, insider actions, and management phrasing. Each issue is assigned a severity rating, and at the end, an overall risk score from 1 to 10 is output.
The fourth and fifth prompts focus on competitive advantages and valuation. One assesses the company's "moat"—brand, network effects, switching costs, scale, intellectual property—on a scale and compares it with competitors. The second compares the company with competitors using multiples (P/E, forward P/E, EV/revenue, EV/EBITDA) and explains whether it appears cheap, fairly valued, or expensive.
The Second Five: From DCF Model to a Beginner's Checklist
The sixth prompt helps build realistic assumptions for a discounted cash flow (DCF) model—a method of valuing a company based on future earnings. It generates bearish, base, and bullish scenarios for revenue growth, margins, tax rate, capital expenditures, and discount rate, explaining the logic behind each assumption.
The seventh prompt creates a catalyst calendar for 3, 6, and 12 months: earnings reports, product launches, investor days, regulatory decisions, lawsuits, macro events, management changes, buybacks, and dividends. For each event, timelines, impact, upside and downside risks, confidence level, and source are specified.
The eighth prompt evaluates the management team: the CEO's track record, the CFO's credibility, forecast accuracy, transparency, capital allocation, acquisitions, insider ownership size, and compensation. The ninth prompt simulates an investment committee debate, where Claude creates a bull analyst and a bear analyst, and at the end, a neutral judge explains whose position is better supported.
The tenth prompt turns Claude into a patient teacher who explains the company in simple terms: what it does, how it makes money, what could go well and wrong, and the state of profitability, growth, debt, and valuation. At the end, a beginner's checklist is generated.
As Abhi AI emphasizes, the value of this collection lies in structuring research. However, the final verification of data and decisions remains with the investor themselves.
My professional opinion: Using AI for preliminary analysis is a powerful tool for saving time and resources. However, relying solely on it without cross-checking facts and conducting your own fundamental analysis is a path to disaster. Especially in volatile cryptocurrency markets, where data can become outdated within minutes.