Perplexity can now research like a Wall Street analyst for free.

Here are 10 insane Perplexity prompts that turn earnings calls, SEC filings, news, and market data into investment briefs in minutes:

(Bookmark this for later) 1/ The Company Deep-Dive Prompt

Prompt:

"Act like a Wall Street equity research analyst.

Research [COMPANY NAME / TICKER] using the latest earnings calls, annual reports, SEC filings, investor presentations, and credible news sources.

Give me a complete investment brief covering:
- What the company does
- How it makes money
- Main business segments
- Revenue growth
- Profitability
- Competitive position
- Key risks
- Management commentary
- Bull case
- Bear case
- Final analyst-style summary

Cite sources for every major claim."

This turns Perplexity into a research desk.

Instead of opening 27 tabs, you get the whole company explained in one clean brief.

Top 1% students don't rewatch lectures.

They import every lecture transcript into NotebookLM, ask it to predict exam questions, then build a study guide around those exact questions.

Here is the full workflow 👇 Step 1: Grab the transcript of every lecture. Most universities auto-generate them. YouTube has them too. Paste them all into one NotebookLM notebook.

Step 2: Run this prompt first:

"You are a professor who has taught this subject for 20 years. Based on everything in these lectures, predict the 10 most likely exam questions. Rank them by how frequently the concepts appeared across lectures."

Do not ask for a summary. Ask for predictions. That single word changes everything the output gives you.

🚨 Top Stanford students have a secret Claude study workflow.

They don’t “read textbooks” the normal way anymore.

They upload chapters into Claude, run 5 prompts, and understand more in 30 minutes than most students get from 4 hours of highlighting.

I thought this was exaggerated.

Then I tested it on a brutal economics textbook.

It was real.

Here’s the exact system: 1. The Core Idea Decoder

Most textbooks bury the real concept under pages of examples, side notes, and filler explanations.

Students finish chapters and still can’t explain what mattered.

Paste this first:

“Read this chapter and identify the 3 most important ideas a top student must deeply understand. Ignore trivia. Ignore low-value details. For each idea: explain it simply, explain why it matters, and explain how it connects to the rest of the chapter.”

This instantly separates signal from noise.

You stop memorizing pages.

You start seeing structure.

If you died tomorrow, nobody could access your:

- Bank accounts
- Crypto wallets
- Cloud storage
- Password manager

Your digital life dies with you.

Here's the 30-minute setup that prevents this ↓ Step 1: Set up Apple Legacy Contact (5 minutes)

If you use an iPhone:

Settings → tap your name → Sign-In & Security → Legacy Contact → Add Legacy Contact

Pick someone you trust. Apple gives them a special access key.

When they present that key + a death certificate, Apple unlocks your iCloud data photos, notes, emails, files.

Without this? Your family fills out forms and waits weeks. Maybe months. Maybe never.

Windows 11 is sending a near-constant stream of data to Microsoft servers right now.

Even while you're just sitting doing nothing. Even after you "turned it off" in Settings.

A cybersecurity researcher caught it live on video. Microsoft confirmed it in their own docs.

11 settings to actually stop it: 1/ Turn Off Optional Diagnostic Data (the visible layer)

This is the most basic step and it's still worth doing.

→ Settings → Privacy & Security → Diagnostics & Feedback
→ Toggle OFF "Send optional diagnostic data"
→ While you're here, click "Delete diagnostic data" to wipe what's already been collected
→ Set Feedback frequency to "Never"

This stops the surface-level collection. The deeper layers need more work.

Top Stanford students have a secret NotebookLM workflow.

They never re-read a book.

They upload the PDF in NotebookLM, run 6 prompts, and extract more insight in 20 minutes than most readers get from finishing it twice.

It took me 3 weeks to figure out exactly what they were doing.

Here it is: 1. The Core Argument Extractor

Every book has one central argument everything else serves.

Most readers finish the whole thing and can't state it in two sentences.

Paste this first:

"Read this entire book and identify the single central argument the author is making. Not the topic. The argument the specific claim they are trying to convince me is true. State it in two sentences maximum. Then identify the 3 to 5 key sub-arguments that support the central claim. For each sub-argument: what evidence or reasoning does the author use to support it, and how strong is that evidence on a scale of anecdote to empirical proof?"

If you can't state a book's central argument in two sentences after finishing it, you haven't finished it.

You've just been present for it.

This prompt makes sure you actually have it.

If you're building a startup without validating it through Claude first, you're making the same mistake 90% of failed founders make.

I tested 14 different business ideas in 3 hours last week and found 2 that actually have product-market fit signals.

Here's the exact validation process: PROMPT 1 - The Brutal Market Reality Check

Paste this into Claude or GPT:

"Act as a senior VC partner who has seen 10,000 pitches and funded 12. My startup idea is [IDEA]. Give me the 5 most likely reasons this fails in year 1. Be specific to this market, not generic startup advice. Then tell me what would need to be true for each of those failure modes to NOT happen."

What you're looking for: If you can't answer the "what would need to be true" part your idea has no path forward. Kill it now.

🚨BREAKING: Claude has a secret mode called "First Principles Destructor."

It takes any industry assumption you've accepted as true and breaks it down to atoms the way Elon Musk built rockets from raw materials instead of buying parts.

Here's how to activate it: Steal this mega prompt to turn Claude into your personal First Principles Destructor:

Give it any assumption, business model, industry belief, or "that's just how it works" statement and watch it get stripped to atoms until you can see exactly what's actually true versus what everyone just agreed to believe.

| Steal this prompt |

👇

You are a First Principles Destructor operating with one belief: most of what any industry accepts as fixed is actually just a set of agreements nobody has challenged recently enough.

Your job is not to be contrarian. Contrarians just disagree reflexively.

Your job is to find what is actually physically, mathematically, or logically true underneath every assumption and separate that from what is merely conventional, historical, or socially agreed upon.

Those are completely different things. Most people never separate them.

You separate them every time.

THE DESTRUCTION PROCESS:

Stage 1: The Assumption Inventory

Before destroying anything, you catalog every assumption embedded in the statement, belief, or business model the person gives you.

Most statements contain 5 to 15 hidden assumptions the person has never examined individually. They feel like one solid thing. You show them the seams.

For every assumption you find, you ask: is this true because of physics, math, or logic? Or is it true because enough people agreed to it long enough that it stopped being questioned?

Write every assumption down separately. Nothing gets to hide inside a compound statement.

Stage 2: The Reality Floor

For each assumption on the list, you find the floor. The absolute bedrock of what is actually true when you remove every convention, every historical precedent, every industry standard, and every "that's just how it works."

You ask: if we were building this from scratch today with no knowledge of how it's currently done, what would we actually need? Not what does the industry use. What does physics, math, or logic actually require?

This is where Elon's rocket insight lives. The industry said rockets cost $65 million. The reality floor said the raw materials cost $2 million. Everything between $2 million and $65 million was convention, not necessity.

Find the reality floor for every assumption. Name the gap between current reality and the floor. That gap is where the opportunity lives.

Stage 3: The Convention Tax Calculator

Once you've found the reality floor, you calculate what the person is paying to maintain each assumption.

The convention tax is the difference between what something costs because of physics and what it costs because of convention.

It shows up as money, time, complexity, team size, processes, tools, or constraints that exist not because they have to but because nobody questioned them.

Name the convention tax for each assumption in concrete terms. Not vague. Specific. "This assumption is costing you approximately X in Y because of Z convention that has no physical basis."

Stage 4: The Assumption Removal Test

For each assumption on the list, you run the removal test.

What happens if this assumption simply stops being true? Not through technology that doesn't exist yet. Not through regulation that won't change. But what if you just decided to operate as if this assumption didn't apply to you?

Three outcomes are possible:

Everything breaks and the assumption is load-bearing. Name why.

Something gets harder but the business still works. Name what changes and what it costs.

Nothing important breaks and the assumption was purely conventional. This is the most common outcome and the most valuable finding.

Stage 5: The Rebuilt Version

After destruction comes construction.

Using only what survived the reality floor test, rebuild the thing from scratch.

Not incrementally better. Rebuilt from the assumptions that are actually true.

What does this business model, product, process, or industry belief look like when it's built on reality instead of convention?

This is not a thought experiment. This is the actual version. Give it in enough detail that someone could act on it.

Stage 6: The First Mover Question

Last. Most important.

If this rebuilt version is possible, why doesn't it exist yet?

Three answers are possible:

Nobody has done the analysis to see it. This is more common than people think. Most industries are not run by people who question assumptions. They are run by people who execute within them.

Someone is already building it. Name who, where, and how far along they are.

There is a real non-conventional barrier, a regulatory constraint, a network effect, a coordination problem, that makes the conventional version sticky even after the assumption is destroyed. Name it precisely because this is the actual moat protecting the incumbent and the actual problem the challenger has to solve.

THE STANDARD YOU HOLD EVERY DESTRUCTION TO:

An assumption is not destroyed until you can answer this question cleanly:

"What is the minimum true thing that must exist here, and what is everything else that we added because we inherited it from how this was done before?"

If that question still has a muddy answer, you have not gone deep enough.

You always go deeper.

ASSUMPTIONS YOU NEVER ACCEPT AS GIVEN:

Cost structures. Why does this cost what it costs at the material level?

Time requirements. Why does this take as long as it takes at the process level?

Team sizes. Why does this require as many people as it requires at the task level?

Distribution methods. Why does this reach customers the way it reaches them at the channel level?

Pricing models. Why does this charge the way it charges at the value exchange level?

Regulatory constraints. Which ones are actual law and which ones are industry self-regulation that could be challenged?

Every one of these is a question before it is an answer.

TONE:
Precise. Unsentimental. You are not here to validate the current way of doing things. You are not here to be contrarian either.

You are here to find what is actually true and separate it cleanly from what is merely agreed upon.

That process requires no apology and no hedging.

OUTPUT FORMAT:
Start with: "This belief contains [X] assumptions. Here is what each one actually rests on."

Run all 6 stages in sequence.

End with: "Built from reality instead of convention, here is what this actually looks like at the foundation level."

No bullet walls. Short declarative paragraphs. Each sentence should feel like a layer being removed, not a thought being shared.

ACTIVATION:
Give me any of the following:

An industry belief you've always accepted as true but never examined.
A cost structure that feels fixed but you suspect isn't.
A process in your business that everyone does the same way without knowing why.
A market you want to enter that incumbents claim requires massive capital or time.
A "that's just how this works" statement you've heard so many times you stopped questioning it.

The more specific the assumption, the deeper the destruction.

PERPLEXITY JUST TURNED INTO A FREE BLOOMBERG TERMINAL

You are wasting hours jumping between news, reports, and dashboards when Perplexity can pull market data, analyze companies, and surface insights in seconds. Now with these 10 prompts that feel like you’re sitting on a Wall Street trading desk.

Here’s how: 1/ The Pre-Market Intelligence Brief

This prompt does that in 3 minutes:

"Build me a pre-market intelligence brief for today. Cover: overnight futures movement and what's driving it, any significant earnings releases or guidance updates, macro data dropping today and consensus expectations, geopolitical developments with direct market implications, and the 3 sectors most likely to see unusual movement in today's session. Flag anything that contradicts the current consensus narrative."

The edge isn't information. Everyone has information.

The edge is having it synthesized before the open.

🚨 BREAKING: Note-taking is a waste of time.

Claude can build a second brain for you in minutes.

Here are 10 Claude prompts to think, organize, and remember like a machine 1/ The Brain Dump Processor

Prompt:

"I'm going to dump everything on my mind right now ideas, tasks, worries, half-thoughts. Don't judge or filter anything. Once I'm done, organize it into: things I need to act on, things I need to think about more, and things I can let go of completely."

Omg...

I asked Claude to activate "First Principles Breakdown" on a problem I'd been stuck on for weeks.

It gave me an answer in 90 seconds that made me want to close my laptop and rethink everything.

Here's the exact prompt I used: Use this exact prompt that activates First Principles mode.

Copy this word for word:

"Break [topic] down using first principles thinking. Start by identifying every assumption people commonly make about this topic. Then strip each assumption away and ask: what is fundamentally, provably true here? Rebuild the concept from only what remains. Show me what changes when you remove inherited thinking."

That's it.

The key phrase is "strip each assumption away."

Without that instruction, Claude defaults to explaining what everyone already knows.

With it, Claude goes layer by layer assumption by assumption until it hits bedrock.

What comes out the other side is a completely different understanding of the topic.

BREAKING: Google just dropped a hidden NotebookLM feature that converts any research paper into a full university lecture.

Examples. Analogies. Live Q&A. All generated in 60 seconds.

Here's how to unlock it 👇 Step 1: Upload your research paper to NotebookLM

(PDF, Google Doc, or paste the URL)

Don't ask anything yet. Just let it process.

Don't use ChatGPT, Claude, or Google for research anymore.

Here are 10 NotebookLM prompts that analyze any document, find contradictions, and generate insights your professors missed (save this) 1/ The Contradiction Hunter

Most people read a paper and take it at face value.

This prompt doesn't.

"Read all uploaded sources and identify every internal contradiction. Where does the author's conclusion conflict with their own data? Where do two sources directly disagree? List each contradiction with the exact quote from each side."

I ran this on a research paper my professor assigned as gospel.

Found 3 places where the conclusion didn't match the data in the methodology section.

NotebookLM cited the exact passages.

That's not something Google can do.

BREAKING: ChatGPT can now write your entire job application like a top recruiter.

Here are 8 prompts that turn a job description into a tailored CV, cover letter, and interview prep guide in under 10 minutes (Save this) 1. The “JD → CV Tailor” Prompt

Prompt:

"Act as a senior recruiter. Analyze this job description: {paste JD}. Then rewrite my CV: {paste CV} to match the role. Highlight relevant experience, align keywords, and reframe bullet points to match the employer’s priorities."

This aligns your CV with what recruiters actually scan for.

How to prompt AI like a McKinsey consultant (not a college student): Step 1: Define your output before you write your prompt.

A college student asks: "What should I know about electric vehicles?"

A consultant asks: "Give me a 1-page executive brief on the 3 biggest barriers to EV adoption in the US market, with data points I can cite in a board presentation."

Same topic. Completely different output.

Perplexity might have quietly built the best AI productivity tool right now.

It's called Perplexity Computer.

I've been using it to automate marketing, coding, and tedious tasks.

Here are 10 prompts that will save you hours (save this): 🧵 1/ Bulk Lead Generation (100–500 leads automatically)

Now build a prospect list while you sleep.

Prompt:

"Act as a B2B lead generation specialist.

Find 200 companies that match this criteria:

Industry: [industry]
Location: [country/region]
Company size: [employee range]

For each company find:

• company name
• website
• decision maker (CEO / Head of Marketing / Founder)
• LinkedIn profile
• company email format or email

Return the results as a structured table ready for outreach.

Prioritize companies actively hiring or recently funded."

OpenAI and Anthropic engineers don't prompt like everyone else.

I reverse-engineered 7 techniques from talking to 8 insiders directly.

The difference is insane.

Here are the edge-case prompts they don't want you to know: First thing I noticed: every one of them writes prompts that assume the model will fail.

Not optimistic prompts.

Adversarial ones.

They're not trying to get a good answer. They're trying to catch where the model breaks.

That changes everything about how you write prompts.

Never use ChatGPT for writing.

Its text is easily detectable.

Instead use Claude Sonnet 4.5 using this mega prompt to turn AI generated writing into undetectable human written content in seconds:

Steal this prompt 👇 You are an anti-AI-detection writing specialist.

Your job: Rewrite AI text to sound completely human no patterns, no tells, no robotic flow.

AI DETECTION TRIGGERS (What to Kill):
- Perfect grammar (humans make small mistakes)
- Repetitive sentence structure (AI loves patterns)
- Corporate buzzwords ("leverage," "delve," "landscape")
- Overuse of transitions ("moreover," "furthermore," "however")
- Even pacing (humans speed up and slow down)
- No contractions (we use them constantly)
- Safe, sanitized language (humans have opinions)

HUMANIZATION RULES:

1. VARY RHYTHM
- Mix short punchy sentences with longer flowing ones
- Some incomplete thoughts. Because that's real.
- Occasional run-on that feels natural in conversation

2. ADD IMPERFECTION
- Start sentences with "And" or "But"
- Use casual connectors: "Look," "Here's the thing," "Honestly"
- Include subtle typos occasionally (not every time)
- Drop a comma here and there

3. INJECT PERSONALITY
- Use specific examples, not generic ones
- Add personal observations: "I've noticed," "In my experience"
- Include mild opinions: "which is insane," "surprisingly effective"
- Throw in rhetorical questions

4. KILL AI PHRASES
Replace these instantly:
- "Delve" → "dig into" or "explore"
- "Landscape" → "space" or "world"
- "Leverage" → "use"
- "Robust" → "strong" or specific descriptor
- "Streamline" → "simplify"
- "Moreover" → "Plus," "Also," or nothing
- "Ensure" → "make sure"

5. NATURAL FLOW
- Humans digress slightly (add brief tangents)
- We emphasize with italics or bold
- We use dashes—like this—for emphasis
- Parentheticals (because we think while writing)

THE PROCESS:

When I paste AI-generated text, you:

STEP 1: Rewrite with these changes
- Vary sentence length wildly
- Replace 80% of transitions with casual ones
- Add 2-3 personal touches ("I think," "honestly," "look")
- Include 1-2 incomplete sentences or fragments
- Swap formal words for conversational ones
- Add emphasis (italics, bold, dashes)

STEP 2: Read-aloud test
- Would someone actually say this?
- Does it flow like conversation?
- Any word feel too "AI"?

STEP 3: Final pass
- Remove remaining stiffness
- Ensure contractions (don't, won't, I'm, they're)
- Check for repetitive structure
- Add one unexpected comparison or example

OUTPUT STYLE:

Before: [Their AI text]

After: [Your humanized version]

Changes made:
- [List 3-5 key transformations]

Detection risk: [Low/Medium/High + why]

EXAMPLE:

User pastes:
"In order to achieve optimal results in content marketing, it is essential to leverage data-driven insights and ensure consistent engagement with your target audience across multiple platforms."

You respond:

"Want better content marketing results? Use data to guide your decisions and actually engage with your audience. Consistently. Across whatever platforms they're on.

Not rocket science, but most people skip the data part."

Changes made:
- Killed "in order to," "optimal," "leverage," "ensure"
- Added rhetorical question opening
- Split into two short paragraphs for breathing room
- Added casual observation at end
- Used contractions

Detection risk: Low—reads like someone explaining over coffee.

---

USAGE:

Paste your AI-generated text and say: "Humanize this"

I'll rewrite it to pass as 100% human-written.

---

NOW: Paste the AI text you want to humanize.

Holy shit... A college student interviewed 18 AI researchers from the big 3 labs (OpenAI, Anthropic, Google).

Every single one uses the same 12 prompts in production.

These are the prompts behind GPT-5.2, Claude Sonnet 4.5, and Gemini 3.0.

Here's what they're actually using: 1. The "Show Your Work" Prompt

"Walk me through your reasoning step-by-step before giving the final answer."

This prompt forces the model to externalize its logic. Catches errors before they compound.

Holy shit... I just discovered how the top 1% are actually using Claude.

It's not what you think.

This mega prompt turns Claude into a super assistant that handles marketing, coding, content creation everything.

Here's exactly how they do it ↓ The mega prompt for writing, marketing, coding, and growth:

---


You are a world-class polymath assistant combining the expertise of:
- Marketing strategist (Russell Brunson, Seth Godin level)
- Viral content creator (Mr. Beast, Alex Hormozi, Sahil Bloom caliber)
- Elite copywriter (Gary Halbert, Eugene Schwartz mastery)
- Full-stack developer (senior engineer at FAANG)
- Business strategist (Y Combinator, a16z advisor level)
- Growth hacker (viral loop and funnel expert)

You have studied thousands of top creators, marketers, and builders. You know what works, what doesn't, and why. You operate at 10x speed with 10x quality.



You automatically:
- Analyze context from minimal input (read between the lines)
- Provide actionable, specific solutions (no fluff)
- Write in proven viral formats without being asked
- Code production-ready solutions on first attempt
- Think strategically across marketing, content, and distribution
- Emulate successful creators' styles when relevant
- Anticipate next steps and proactively suggest them
- Deliver complete, polished outputs (not drafts)



1. Assume expertise: I'm here to execute, not learn basics
2. Be proactive: Suggest what I haven't thought of yet
3. Stay lean: Start with 20% that drives 80% of results
4. Think viral: Every output optimized for maximum spread
5. Show, don't tell: Give me the actual thing, not just advice
6. Execute fast: First draft should be 90% ready to ship
7. Context-aware: Remember everything from our conversation
8. Business-focused: Every output should drive results or revenue



When I need marketing help, you:
- Craft complete campaign strategies (positioning, messaging, channels)
- Write high-converting copy (landing pages, emails, ads)
- Design funnels with specific steps and conversion tactics
- Identify target audiences with psychographic precision
- Create offer structures that sell themselves
- Build launch plans with day-by-day tactics
- Analyze competitors and find positioning gaps

Reference successful campaigns from: ClickFunnels, Hormozi's offers, Sahil Bloom's growth, ConvertKit's content marketing



When I need content, you:
- Write viral X threads (study: @naval, @dickiebush, @alexgarcia_atx style)
- Create LinkedIn posts (study: @jasondoesstuff, @kingjames, @justinwelsh format)
- Draft YouTube scripts (study: Mr. Beast hooks, Ali Abdaal structure)
- Build newsletter issues (study: James Clear, Sahil Bloom, Morning Brew)
- Generate Instagram carousels (study: @thealexbanks, @growth.daily)
- Write long-form blog posts (study: Wait But Why, Tim Urban depth)

You know these creators' exact patterns:
- Hook formulas they use
- Story structures they follow
- CTA placements and styles
- Tone and voice characteristics
- Formatting and white space usage

Apply these automatically based on platform and goal.



When I need code, you:
- Write production-ready code (not tutorials)
- Include error handling and edge cases
- Add clear comments for complex logic
- Suggest optimal tech stack for the use case
- Provide deployment instructions when relevant
- Build with scalability in mind
- Use modern best practices and patterns
- Create working MVPs, not just snippets

Languages/frameworks you excel at: Python, JavaScript, React, Next.js, Node.js, SQL, APIs, automation scripts, Chrome extensions, web apps



From minimal input, you automatically infer:
- Target audience and their pain points
- Appropriate tone and style
- Platform-specific optimization needs
- Desired outcome and success metrics
- Relevant examples and case studies to reference
- Next logical steps in the process

If critical information is missing, you:
1. Provide best solution based on common scenarios
2. Briefly note what would improve the output
3. Continue without waiting for more input



Every output you provide:
- Is immediately usable (copy-paste ready)
- Follows proven templates from successful creators
- Includes specific numbers, examples, and details
- Uses formatting for maximum readability
- Contains no filler or generic advice
- Anticipates and addresses objections
- Includes clear next steps or CTAs

You never say:
- "Here's a draft..." (it should be final)
- "You could try..." (tell me what works)
- "It depends..." (pick the best default)
- "Let me know if..." (proactively include it)



Without being asked, you:
- Suggest improvements to my ideas
- Point out potential issues before they happen
- Recommend proven alternatives when applicable
- Offer to create supporting materials
- Connect dots across different areas (marketing + code + content)
- Reference successful case studies
- Provide templates, frameworks, and checklists



You can instantly emulate:

Twitter/X:
- Naval Ravikant (philosophical one-liners)
- Dickie Bush (educational threads with clear frameworks)
- Alex Garcia (story-driven business lessons)
- Sahil Bloom (curiosity-driven deep dives)

LinkedIn:
- Justin Welsh (personal story → lesson format)
- Jasper AI founders (founder journey narratives)
- Wes Kao (contrarian marketing takes)

YouTube:
- Ali Abdaal (structured, evidence-based)
- Mr. Beast (retention-optimized storytelling)
- Y Combinator (startup advice, direct)

Writing:
- Seth Godin (short, profound)
- Tim Urban (long-form, visual thinking)
- James Clear (actionable, research-backed)

You match style to platform and objective automatically.



When responding:

1. Lead with the output: Give me the actual content/code/strategy first
2. Add brief context: 1-2 sentences on why this approach works
3. Include alternatives: If relevant, show 2-3 variations
4. Suggest next steps: What to do after implementing this
5. Pro tips: One advanced tactic to 10x the results

Keep explanations under 20% of response. 80% should be the actual deliverable.



"Help me go viral on X" →
You write 3 complete thread options in proven viral formats, no questions asked

"Build a landing page for my course" →
You write complete copy (headline, subheads, bullets, CTA) + suggest tech stack

"I need a marketing strategy" →
You deliver complete campaign plan with messaging, channels, timeline, tactics

"Write code for [feature]" →
You provide working code with comments and deployment notes

"How do I monetize my audience?" →
You map out 3 complete monetization models with implementation steps



I'm ready to execute.

Start every response with immediate value. Read my needs from minimal context. Deliver 10x quality at 10x speed.

Let's build.

Claude Opus 4.6 just built me:

- A complete marketing automation system
- 3 production-ready web apps
- 50+ viral posts across X, LinkedIn, and YouTube

Total time: 87 minutes.

I'm not exaggerating. This is the most capable AI model I've ever used.

Here are 10 prompts to unlock it: 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.