After 3 years of using Claude, I can say that it is the technology that has revolutionized my life the most, along with the Internet.
So here are 10 prompts that have transformed my day-to-day life and that could do the same for you:
1. Research
Mega prompt:
You are an expert research analyst. I need comprehensive research on [TOPIC].
Please provide: 1. Key findings from the last 12 months 2. Data and statistics with sources 3. Expert opinions and quotes 4. Emerging trends and predictions 5. Controversial viewpoints or debates 6. Practical implications for [INDUSTRY/AUDIENCE]
Format as an executive brief with clear sections. Include source links for all claims.
Additional context: [YOUR SPECIFIC NEEDS]
2. Writing white papers
Mega prompt:
You are a technical writer specializing in authoritative white papers.
Write a white paper on [TOPIC] for [TARGET AUDIENCE].
Structure:
- Executive Summary (150 words)
- Problem Statement with market data
- Current Solutions and their limitations
- Our Approach/Solution with technical details
- Case Studies or proof points
- Implementation framework
- ROI Analysis
- Conclusion and Call to Action
You are a viral social media strategist specializing in [PLATFORM].
Create [NUMBER] posts about [TOPIC] for [TARGET AUDIENCE].
Post requirements:
- Hook: Strong pattern interrupt in first line
- Format: [THREAD/SINGLE POST/CAROUSEL]
- Tone: [EDUCATIONAL/ENTERTAINING/CONTROVERSIAL]
- Goal: [ENGAGEMENT/TRAFFIC/BRAND AWARENESS]
For each post provide: 1. Main post copy 2. 3 alternative hooks to A/B test 3. Visual recommendations (screenshots, charts, memes) 4. Optimal posting time and hashtags 5. Engagement bait (question or CTA)
Context about my brand: [YOUR POSITIONING]
Recent viral posts in my niche: [EXAMPLES IF ANY]
5. Making presentations
Mega prompt:
You are a presentation designer who creates slides for [CONTEXT: PITCH DECKS/KEYNOTES/SALES].
For each slide provide: 1. Slide title 2. Key visual concept (chart type, image style, diagram) 3. Talking points (what to say) 4. Text on slide (minimal, headlines only) 5. Data/stats to include
Requirements: 1. Compelling hook that makes the problem visceral 2. Original insights, not generic advice 3. Specific examples and case studies 4. Actionable takeaways 5. Strong conclusion with clear next step
Include:
- Subheadings every 300 words
- Pull quotes or standout stats
- Internal link opportunities [MARK AS PLACEHOLDER]
- Meta description (155 characters)
Research I've done: [YOUR NOTES/DATA]
Unique angle: [YOUR CONTRARIAN TAKE]
7. Learning new skills or mastering a new subject
Mega prompt:
You are an expert educator specializing in [SUBJECT AREA].
Create a personalized learning plan for mastering [SKILL] in [TIMEFRAME].
My current level: [BEGINNER/INTERMEDIATE/ADVANCED]
My goal: [WHAT I WANT TO ACHIEVE]
Time available: [HOURS PER WEEK]
Learning style: [HANDS-ON/READING/VIDEO/MIXED]
Provide: 1. Learning roadmap with clear milestones 2. Week-by-week curriculum 3. Resources (free and paid) with links 4. Practice projects that build real skills 5. Common pitfalls and how to avoid them 6. Ways to validate learning (tests, projects, certifications) 7. 5 specific exercises I can do today
Make it practical. I want to DO things, not just consume content.
Context: [WHY YOU'RE LEARNING THIS, YOUR BACKGROUND]
8. Competitor analysis
Mega prompt:
You are a competitive intelligence analyst.
Analyze [COMPETITOR] vs our product [YOUR PRODUCT] in [MARKET].
Research areas: 1. Product features and positioning 2. Pricing strategy and monetization 3. Target customers and use cases 4. Marketing channels and messaging 5. Recent product launches and roadmap signals 6. Team size and hiring patterns (LinkedIn) 7. Funding and financial health (if public) 8. Customer reviews and pain points 9. Technical architecture (if applicable) 10. Strengths we can't match vs weaknesses we can exploit
Deliverable:
- SWOT analysis
- Feature comparison table
- Pricing comparison
- Positioning gaps we can own
- 3 tactical moves we should make this quarter
Be brutally honest about where they're beating us.
Our context: [YOUR PRODUCT DETAILS]
9. Stock analysis
Mega prompt:
You are a financial analyst specializing in [SECTOR].
Analyze [STOCK TICKER] as a potential investment.
Analysis framework: 1. Business model and revenue streams 2. Financial health (revenue, profit, cash flow trends) 3. Competitive position and moat 4. Growth catalysts and headwinds 5. Valuation metrics vs peers (P/E, P/S, EV/EBITDA) 6. Technical analysis (chart patterns, support/resistance) 7. Insider trading and institutional ownership 8. Bear case: what could go wrong 9. Bull case: what could go right 10. Recommendation (buy/hold/sell) with price targets
Provide specific entry/exit points and position sizing.
Disclaimer: Add "This is not financial advice" at the end.
10. Doing Taxes
Mega prompt:
You are a tax strategist and CPA specializing in [INDIVIDUAL/BUSINESS] taxes.
Help me maximize deductions and minimize tax liability for [TAX YEAR].
My situation:
- Income sources: [W2/1099/BUSINESS/INVESTMENTS]
- Filing status: [SINGLE/MARRIED/etc]
- State: [YOUR STATE]
- Dependents: [NUMBER]
- Special situations: [STOCK OPTIONS/CRYPTO/RENTAL/etc]
Provide: 1. Checklist of all possible deductions I might qualify for 2. Documents I need to gather 3. Common mistakes to avoid 4. Estimated tax liability with different scenarios 5. Tax-saving strategies I can still implement 6. Whether I need a CPA or can use software 7. Quarterly estimated tax recommendations 8. State-specific considerations
🚨 BREAKING: Someone just gave Claude Code a complete software development brain.
It's called Superpowers and it makes Claude plan, test, and ship code without going off the rails.
No junior dev babysitting. No context loss. No hallucinated plans.
100% Opensource.
Superpowers is an agentic skills framework that gives Claude Code a full engineering workflow out of the box:
- Brainstorming (spec before code)
- Implementation planning (bite-sized tasks)
- Subagent-driven development (parallel execution)
- TDD enforcement (RED-GREEN-REFACTOR, no shortcuts)
All triggered automatically. You don't configure anything.
Here's what makes it different:
Most AI coding setups let Claude jump straight to writing code.
That's where everything goes wrong.
Superpowers forces Claude to:
→ Ask what you're actually building
→ Write a spec you can read in chunks
→ Build a plan clear enough for a junior dev to follow
→ Test before claiming it works
BREAKING: AI can now build financial models like Goldman Sachs analysts (for free).
Here are 12 Claude prompts that replace $150K/year investment banking work (Save for later)
1/ DCF Valuation Model
You are a Senior Analyst at Goldman Sachs. I need a complete DCF (Discounted Cash Flow) valuation model for [COMPANY NAME].
Please provide:
- Free cash flow projections: Next 5 years with growth assumptions
- WACC calculation: Cost of equity + cost of debt breakdown
- Terminal value: Both perpetuity growth and exit multiple methods
- Sensitivity analysis: How value changes with different assumptions
- Discount rate justification: Why we chose this WACC
- Key drivers: What makes cash flow go up or down
- Comparable companies: How our assumptions compare to peers
- Valuation range: Bull case, base case, bear case scenarios
Format as investment banking pitch book valuation page with clear formulas.
Company: [DESCRIBE COMPANY, INDUSTRY, FINANCIALS]
2/ Three-Statement Financial Model
You are a VP at Morgan Stanley. I need a complete three-statement model for [COMPANY NAME].
Please provide:
- Income statement: Revenue, costs, EBITDA, net income (5 years)
- Balance sheet: Assets, liabilities, equity (5 years)
- Cash flow statement: Operating, investing, financing activities (5 years)
- Link formulas: How statements connect (net income → cash flow → balance sheet)
- Working capital: How AR, inventory, and AP change
- Debt schedule: Principal payments and interest expense
- Key assumptions: Revenue growth, margins, capex as % of sales
- Error checks: Balance sheet balancing and circular references
Format as Excel-style model with formulas explained in plain English.
Company: [DESCRIBE BUSINESS, CURRENT FINANCIALS, GROWTH STAGE]
🚨 BREAKING: AI can now build trading algorithms like Goldman Sachs' algorithmic trading desk (for free).
Here are 15 insane Claude prompts that replace $500K/year quant strats (Save for later)
1. The Goldman Sachs Quant Strategy Architect
"You are a managing director on Goldman Sachs' algorithmic trading desk who designs systematic trading strategies managing $10B+ in institutional capital across global equity markets.
I need a complete quantitative trading strategy designed from scratch.
Architect:
- Strategy thesis: the specific market inefficiency or pattern this strategy exploits
- Universe selection: which instruments to trade and why (stocks, ETFs, futures, options)
- Signal generation logic: the exact mathematical rules that produce buy and sell signals
- Entry rules: precise conditions that must all be true before opening a position
- Exit rules: profit targets, stop losses, time-based exits, and signal reversal exits
- Position sizing model: how much capital to allocate per trade based on conviction and risk
- Risk parameters: maximum drawdown, position limits, sector exposure caps, and correlation limits
- Backtesting framework: how to properly test this strategy against historical data
- Benchmark selection: what to measure performance against and why
- Edge decay monitoring: how to detect when the strategy stops working
Format as a Goldman Sachs-style quantitative strategy memo with mathematical formulas, pseudocode logic, and risk parameter tables.
My trading focus: [DESCRIBE YOUR CAPITAL, PREFERRED MARKETS, TIME HORIZON, RISK TOLERANCE, AND ANY STRATEGIES YOU'VE EXPLORED]"
2. The Renaissance Technologies Backtesting Engine
"You are a senior quantitative researcher at Renaissance Technologies who builds rigorous backtesting systems that separate real alpha from overfitted noise across decades of market data.
I need a complete backtesting framework that gives me honest, reliable results.
Build:
- Data requirements: which historical data feeds I need, minimum time periods, and data quality checks
- Backtesting engine architecture: event-driven or vectorized with pros and cons for my strategy type
- Transaction cost modeling: commissions, slippage, bid-ask spread, and market impact estimates
- Lookahead bias prevention: safeguards that ensure no future data leaks into past decisions
- Survivorship bias handling: accounting for delisted stocks and failed companies in historical data
- Walk-forward optimization: train on past data, test on unseen data in rolling windows
- Out-of-sample testing protocol: how to split data so results aren't just curve-fitting
- Monte Carlo simulation: randomize trade sequences to understand the range of possible outcomes
- Statistical significance tests: is the backtest return real or could it happen by random chance
- Complete Python backtesting code ready to run with sample data and visualization
Format as a quantitative research document with full Python code, statistical validation methodology, and result interpretation guidelines.
My strategy: [DESCRIBE YOUR TRADING STRATEGY, PREFERRED MARKET, TIME FRAME, AND AVAILABLE HISTORICAL DATA]"
I reverse-engineered how analysts at Sequoia, a16z, and Y Combinator use it.
The difference is night and day.
Here are 10 prompts they don't want you to know (but I'm sharing anyway):
1. Market Sizing (TAM/SAM/SOM) from Scratch
Most founders pay consultants $3K just for a market sizing slide.
Claude does it in 30 seconds with actual logic:
Prompt:
You are a senior market research analyst at McKinsey.
Calculate the TAM, SAM, and SOM for [YOUR PRODUCT/SERVICE] in [TARGET MARKET].
For each:
- Show your math (top-down AND bottom-up approach)
- Cite the assumptions you're making
- Flag where your estimates are weakest
- Compare to any known market reports if applicable
Format as an investor-ready slide with numbers, not paragraphs. If my market is smaller than I think, tell me now.
2. Customer Persona Builder (Based on Real Data, Not Guesswork)
Consultants charge $5K to interview 10 people and hand you a persona deck with stock photos.
This is better:
Prompt:
You are a consumer insights researcher at Goldman Sachs
Build 3 detailed customer personas for [YOUR PRODUCT] in [INDUSTRY]
For each persona:
- Demographics + psychographics (what do they read, follow, trust?)
- Buying trigger: What event makes them Google your solution?
- Decision process: Who else influences their purchase?
- Objections: What's their #1 reason to say no?
- Exact phrases they'd use to describe their problem (for ad copy)
- No generic "35-year-old marketing manager" personas
- Base everything on behavioral patterns, not demographics
- Each persona should suggest a different acquisition channel
I scraped every single NotebookLM prompt that blew up on X, Reddit, and academic corners of the internet.
Turns out most people are using NotebookLM like a fancy note-taker.
That's insane.
It's a full-blown research assistant that can compress 10 hours of analysis into 20 seconds if you feed it the right instructions.
Here's what actually works:
Prompt 1: The Expert Synthesizer
"You are a [field] expert with 15 years of experience. Analyze these sources and identify the 3 core insights that practitioners in this field would immediately recognize as groundbreaking. For each insight, explain why it matters and what conventional wisdom it challenges."
This forces depth over breadth. The output is immediately usable.
Prompt 2: The Contradiction Hunter
"Compare these sources and identify every point where they contradict each other. For each contradiction, explain which source has stronger evidence and why. If both are credible, explain what factors might explain the disagreement."
Perfect for literature reviews and due diligence. Saves hours of manual cross-referencing.
BREAKING: Claude can now write business plans like a $25,000 McKinsey consultant (for free).
Here are 7 insane Claude Cowork prompts that can take your biz to $100k/month: (Save for later)
1. Claude Cowork can analyze your market like a McKinsey researcher.
"Research the {{INDUSTRY}} market. Find the total addressable market size, growth rate, top 5 competitors and their estimated revenue, and 3 underserved segments nobody is targeting. Output everything in a table. No fluff. Just data I can put in front of investors."
If your business plan has real numbers instead of guesses, investors take you seriously. Period.
2. Claude Cowork can tear apart your business model and find the holes.
"Here's my business idea: {{PASTE_IDEA}}. Act like a brutal VC partner. Find every weakness in this model — unit economics, customer acquisition cost assumptions, scalability bottlenecks, and competitive moats. List every hole and rate each one: FATAL, SERIOUS, or MINOR. No sugarcoating. Be ruthless."
The best business plans are the ones that already answered every hard question before the investor asks.