Some dumb researchers still read papers one by one.

Stanford PhD students just use Claude.

Here are 9 prompts that turn 40+ papers into structured literature reviews, knowledge maps, and research gaps in minutes: PROMPT 1 - The Intake Protocol

Use this when you first upload your papers:

"I'm going to share [X] papers on [topic].
Before I ask anything, do this:

1. List every paper by author + year + core claim in one sentence
2. Group them into clusters of shared assumptions
3. Flag any paper that contradicts another

Don't summarize. Map the landscape."

I accidentally found the NotebookLM prompts that went viral in private founder groups.

Everyone's using it like a fancy PDF viewer.

These 20 prompts generate insights McKinsey charges $100k for.

(they're keeping this quiet) 👇 1. The Exam Predictor

"Based on this material, what are the 5 most likely questions a skeptical expert would ask to poke holes in this?"

Turns passive reading into active stress-testing.

Works on research papers, pitch decks, and strategy docs.

Here are 8 Claude prompts to get your first 100 users without spending money on ads.

(Steal these now) 👇 PROMPT 1: The ICP Hunter

"I'm building [product]. Describe my ideal first 100 users in brutal detail — their job title, daily frustrations, where they hang out online, what they Google at 2am, and the exact words they use to describe their problem. Don't be generic."

Holy shit... someone just proved you can 10x prompt quality by adding one sentence.

It's called negative prompting and it quietly kills the "basic prompting" era.

Here's how it works (and why this changes everything): Step 1: Understand what negative prompting actually is.

A normal prompt says: "Write me a product description."

A negative prompt says: "Write me a product description. Don't use hype words, don't use bullet points, and don't sound like a sales ad."

You're giving the AI a guardrail, not just a goal.

Someone turned Alex Hormozi's $100M offer framework into an AI prompt system.

It's like having Hormozi audit your business, rip apart your pricing, and rebuild your offer from scratch.

Here are the 11 prompts (save this): 1. The Brutal Offer Audit

Prompt:

“Act like Alex Hormozi reviewing my business.

Here’s my offer: [paste offer]

Be brutally honest. Identify:
• Why customers might hesitate
• Where the value feels weak
• What competitors could easily copy
• What makes the offer forgettable

Then suggest specific improvements.”

R.I.P. McKinsey.

Perplexity just became a $120K/year strategy consultant you can access for free.

Here are 14 prompts that replace entire corporate intelligence teams (Save this thread) 👇 1/ Full Competitive Landscape Map

"You are a Senior Strategy Consultant at McKinsey. I need a complete competitive landscape for [COMPANY NAME].

Use live web data and cite sources.

Please provide:
- Top 15 direct competitors
- 10 indirect/substitute competitors
- Market share estimates
- Revenue comparison table
- Geographic presence comparison
- Business model differences
- Positioning summary (premium, mid-market, low-cost)
- Visual 2x2 strategic map description

Format as a board-ready competitive landscape slide.

Company: [INSERT COMPANY + INDUSTRY]"

I reverse-engineered how top PMs at Google, Meta, and Anthropic actually use Claude.

They're not writing docs with it.

They're using it for roadmap planning, PRD validation, and stakeholder alignment.

The prompts are insane.

Here are the 10 they use every single day: 1. PRD Generation from Customer Calls

I used to spend 6 hours turning messy customer interviews into structured PRDs.

Now I just dump the transcript into Claude with this:

Prompt:

---

You are a senior PM at [COMPANY]. Analyze this customer interview transcript and create a PRD with:

1. Problem statement (what pain points did the customer express in their own words?)
2. User stories (3-5 stories in "As a [user], I want [goal] so that [benefit]" format)
3. Success metrics (what would make this customer renew/upgrade?)
4. Edge cases the customer implied but didn't directly state

Be ruthlessly specific. Quote the customer directly when identifying problems.

---

If you run a startup and you’re not using Perplexity like this, you’re already behind.

These 10 prompts reveal your competitor’s weak spots, messaging gaps, and pricing logic in one session.

Save this for later: 1/ Map your entire competitive landscape in 60 seconds.

Prompt:

"Act as a competitive intelligence analyst. Give me a full breakdown of [Company X]'s market position right now — pricing strategy, target customers, key differentiators, and recent strategic moves. Cite sources."

Most people Google this for hours.

Perplexity does it in one shot with live data.

This is insane.

I tested 10 AI prompts on ChatGPT, Claude, Grok, and Gemini for client acquisition.

The results were so good I had to turn down work.

Here's what actually works: 1. IDEAL CUSTOMER INTERVIEWS

Prompt:

"You are [my ideal customer persona]. I'm going to pitch you [my offer]. Interview me like a skeptical buyer. Ask 10 hard questions about price, results, competition, and risk. Be brutally honest about why you wouldn't buy."

Run this 5 times. Fix every objection before your real sales calls.

Anthropic's Claude completely changed how I write professionally.

Over 2 years, I produced 500 articles, 23 whitepapers, and 3 ebooks using just 10 core prompts.

They outperform human editors at $0.02 per 1000 words.

Here's every technique I extracted 👇 1. The 5-Minute First Draft

Prompt:

"Turn these rough notes into an article:

[paste your brain dump]

Target length: [800/1500/3000] words
Audience: [describe reader]
Goal: [inform/persuade/teach]

Keep my ideas and examples. Fix structure and flow."

Holy shit... Claude Opus 4.6 just made every other AI look outdated.

I tested it against GPT-5 and Gemini 2.5 Pro with the same critical prompts.

The results will blow your mind.

Here are 10 prompts to steal: 1. THE CAMPAIGN STRATEGIST

Opus 4.6's 200K context window means it remembers your entire brand voice across all campaigns.

Prompt:

"You are my senior marketing strategist with 10 years of experience in [your industry]. First, analyze my brand voice by reviewing these materials: [paste 3-5 previous posts, your about page, and any brand guidelines].

Then create a comprehensive 30-day content calendar that includes: daily post ideas with specific angles, optimal posting times based on my audience timezone [specify timezone], platform-specific adaptations (Twitter, LinkedIn, Instagram), CTAs tailored to each post's goal, and content themes organized by week.

For the top 5 highest-potential posts, create A/B test variations testing different: hooks, CTAs, content formats (thread vs single post vs carousel), and emotional angles. Include your reasoning for why each variation might outperform.

Finally, identify 3 content gaps my competitors are filling that I'm currently missing."

Opus maintains perfect consistency across 200K tokens. Other models lose your voice after 3-4 posts.

I've watched hundreds of people use Perplexity completely wrong.

That's insane.

These 10 prompts replace 20 hours of desk research. Not by being faster, but by being narrower.

Each one answers the concrete business questions founders actually have: Who buys first, why now, what stops them, what incumbents ignore.

Here's what actually works: 1/ "Who are the first 100 customers for [product]? Give me specific personas, where they hang out online, what triggers their buying decision, and which pain point they'll pay to solve first."

I don't use ChatGPT and Grok for research.

I recently tested Perplexity for a week and it's on a whole different level.

Here are 7 prompts that turn Perplexity into your AI research analyst: 1. Market Timing Intel

Prompt:

"Find every major announcement, funding round, and product launch in [industry] from the last 90 days. For each one, show me: the date it happened, the companies involved, the dollar amounts if applicable, and most importantly - what trend or shift this signals. Then connect the dots: what pattern emerges when you look at all of these together? What's about to happen in this market that most people aren't seeing yet?"

Perplexity pulls real-time data with sources. ChatGPT hallucinates dates and makes up funding rounds.

I used this to spot the AI coding tools wave 4 months early. Built a product that hit $40k MRR because I saw it coming.

While everyone debates Claude vs ChatGPT, Gemini 3.0 quietly became the best free AI for financial analysis.

I've tested it for 6 months on:

- SEC filing analysis
- Earnings call transcripts
- Market sentiment
- Competitor research

Here are 8 prompts that actually deliver: 1. Earnings Call Decoder

Prompt:

"Analyze the last 3 earnings calls for [company ticker].

Don't summarize what they said - tell me what they're NOT saying.

Focus on:

1) Questions the CEO dodged or gave vague answers to,
2) Metrics they stopped reporting compared to previous quarters,
3) Language changes - where they went from confident to cautious or vice versa,
4) New talking points that appeared suddenly,
5) Guidance changes and the exact wording they used to frame it. Then connect this to their stock performance in the 2 weeks following each call.

What pattern emerges?"

Gemini can process multiple transcripts simultaneously and catch subtle language shifts. I caught a revenue recognition issue 3 weeks before the stock tanked because the CFO changed how he talked about "bookings." Made 34% shorting it.

Omg...

I switched from ChatGPT to Claude for content writing and my engagement shot up 340% across all platforms. 😳

The secret? These 10 prompts that make Claude write like an actual human.

Here's exactly what I use: 1. The Coffee Shop Test

Prompt:

"Write this like you're explaining it to a friend over coffee. No marketing speak. No corporate jargon. Just straight talk about [topic]. If it sounds like a LinkedIn post, rewrite it."

Claude actually gets this. ChatGPT still sounds like it's pitching a SaaS product.

R.I.P few-shot prompting ☠️

Meta AI researchers discovered a technique that makes LLMs 94% more accurate without any examples.

It's called "Chain-of-Verification" and it completely destroys everything we thought we knew about prompting.

Here's everything you need to know: Here's the the problem with current prompting:

LLMs hallucinate. They generate confident answers that are completely wrong.

Few-shot examples help, but they're limited by:

- Your choice of examples
- Token budget constraints
- Still prone to hallucination

We've been treating symptoms, not the disease.

CHATGPT JUST TURNED MARKET RESEARCH INTO A ONE PERSON SUPERPOWER

You are wasting weeks interviewing customers, stalking competitors, and digging through reports when ChatGPT can compress the entire process into minutes with 5 prompts that feel like you’re plugging into a McKinsey analyst on caffeine.

Here's how: 1/ THE MARKET MAP PROMPT

Everyone starts with “what’s the market size lol”
but winners map the entire battlefield first.

Prompt to steal:

“Give me a complete market map for [industry].
Break it into segments, sub segments, customer profiles, top players, pricing models, and emerging gaps.
Highlight where new entrants have the highest odds of success.”

This gives you clarity fast.

If you're still coding without Claude, you're wasting hours.

I built 37 projects using these prompts.

Here are 8 Claude coding prompts that replaced my entire workflow👇: 1/ The Architecture Validator

This prompt makes Claude review your entire codebase architecture before you write a single line.

It saved me 40+ hours of refactoring on my last project.

---


Review the architecture of my [project type] and provide a comprehensive analysis




[Your technologies: e.g., React, Node.js, PostgreSQL, Redis]



[Paste your folder structure or describe your architecture]



- Must handle [X] concurrent users
- Need to support [specific features]
- Planning to scale to [target scale]




1. Architecture strengths (what's working well)
2. Critical bottlenecks (what will break at scale)
3. Security vulnerabilities (what could go wrong)
4. Recommended improvements (specific, actionable changes)
5. Implementation priority (what to fix first)



- Focus on production-ready solutions
- Consider cost implications
- Prioritize maintainability over clever code

Hot take: Prompt engineering is why your outputs suck.

Anthropic’s internal workflow shows what actually matters instead.

Here are 5 techniques amateurs never use 👇 1/ THE "MEMORY INJECTION" TECHNIQUE

Most people start fresh every time. Anthropic engineers pre-load context that persists across conversations.

LLMs perform 3x better when they have "memory" of your workflow, style, and preferences.

Example prompt to test:

"You're my coding assistant. Remember these preferences: I use Python 3.11, prefer type hints, favor functional programming, and always include error handling. Acknowledge these preferences and use them in all future responses."

Every "prompt engineering expert" on Twitter just got destroyed by actual research.

Turns out "please" and "thank you" actively hurt AI performance.

But the real findings are way more nuanced than anyone's talking about.

Here's what the data ACTUALLY shows: Penn State just published research testing 5 politeness levels on ChatGPT-4o with 50 questions:

Very Polite: 80.8% accuracy
Polite: 81.4%
Neutral: 82.2%
Rude: 82.8%
Very Rude: 84.8%

Prompts like "Hey gofer, figure this out" beat "Would you be so kind?" by 4 percentage points.

Everyone's hyping ChatGPT for business research.

Meanwhile, Gemini 3 is quietly doing 10x better work.

I tested it for 90 days on real projects.

Here are 5 prompts that prove why it's superior: 1/ THE MARKET MAP PROMPT

Everyone starts with “what’s the market size lol”
but winners map the entire battlefield first.

Prompt to steal:

“Give me a complete market map for [industry].
Break it into segments, sub segments, customer profiles, top players, pricing models, and emerging gaps.
Highlight where new entrants have the highest odds of success.”

This gives you clarity fast.