AI analyst for pennies: 10 prompts for Claude that will replace an entire department
The market for analytical services is undergoing a tectonic shift. A set of ten specialized prompts for Claude, published under the pseudonym Abhi AI, demonstrates how artificial intelligence can perform the functions of expensive equity and cryptocurrency analysts. These queries do not provide investment recommendations—they structure the research process at the level of a leading consulting firm.
The First Five: From General Overview to Valuation
The first prompt turns Claude into a senior analyst capable of preparing a beginner-friendly research report on a company or ticker. It covers the business model, revenue sources, industry trends, competitors, financial results, valuation, growth drivers, risks, and bull/base/bear scenarios. A key requirement is to rely on recent public sources, clearly separating facts from assumptions.
The second prompt breaks down the company's latest earnings call: five main takeaways, revenue and margin trends, management guidance, management tone, analyst concerns, as well as positive and negative surprises. The result includes a table of key metrics with explanations.
The third prompt sets Claude up as a skeptical analyst, searching for red flags in revenue quality, margins, cash flow, debt, dilution, insider actions, and management wording. Each issue is assigned a severity rating, culminating in an overall risk score from 1 to 10.
The fourth and fifth prompts focus on competitive advantages and valuation. The first assesses the company's "moat"—brand, network effects, switching costs, scale, intellectual property—on a scale and compares it with competitors. The second compares multiples (P/E, forward P/E, EV/revenue, EV/EBITDA) and determines whether the company is 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, forming bearish, base, and bullish scenarios for revenue growth, margins, tax rate, capital expenditures, and discount rate, with an explanation of the logic behind each assumption.
The seventh prompt creates a catalyst calendar for 3, 6, and 12 months: reports, product launches, investor days, regulatory decisions, lawsuits, macro events, management changes, buybacks, and dividends. For each event, it specifies timing, impact, upside and downside risks, confidence level, and source.
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 a neutral judge explains whose position is more strongly supported.
The tenth prompt turns Claude into a patient teacher, explaining the company in simple terms: what it does, how it makes money, what could go right and wrong, and its status on profitability, growth, debt, and valuation. It ends with a beginner's checklist.
My expert opinion: Tools like these are powerful democratizers of analytics, but they do not eliminate the need for critical thinking. AI excels at structuring data but cannot assess management quality or foresee black swan events. Final data verification and decision-making always remain with the investor.