I've been using Claude Code for a few months and noticed AI agents consistently skip the same things: hardcoded secrets, unbounded retry loops, referencing tools that don't exist, and massive system prompts that blow context windows.

So I built Agent Verifier — an AI agent skill that acts as an automated reviewer which does more than just code review (check the repo for details - more to be added soon).

GitHub Repo: https://github.com/aurite-ai/agent-verifier

Note: Drop a ⭐ if you find it useful to get more updates as we add more features to this repo.

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2 Steps to use it:

You install it once and say "verify agent" on any of your agent folder in claude code to get a structured report:

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✅ 8 checks passed | ⚠️ 3 warnings | ❌ 2 issues

❌ Hardcoded API key at config.py:12 → Move to environment variable
❌ Hallucinated tool reference: execute_sql → Tool referenced but not defined
⚠️ Unbounded loop at agent/loop.py:45 → Add MAX_ITERATIONS constant

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Install to your claude code:

npx skills add aurite-ai/agent-verifier -a claude-code

OR install for all coding agents:

npx skills add aurite-ai/agent-verifier --all

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Happy to answer questions about how the agent-verifier works.

We have both:
- pattern-matched (reliable), and,
- heuristic (best-effort) tiers, and every finding is tagged so you know the confidence level.

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Please share your feedback and would love contributors to expand the project!

TL;DR: NotebookLM’s new Cinematic Video Overviews turn your sources into fully animated, narrated videos powered by Gemini 3 and Veo 3. It’s not just a slideshow; it generates motion graphics and cinematic visuals from scratch based on your documents. Since you can’t edit the video after it generates, your initial setup and prompt are everything. Feed it clean Markdown, use the CPTC prompting framework, define a strict visual style (like FPV drone shots or macro cinematography), and use anti-repetition constraints.

Google just quietly changed the game for AI-generated content. If you've been living in the Audio Overviews tab in NotebookLM, it's time to open up the Studio panel.

The new Cinematic Video Overviews (launched in March 2026 for Ultra subscribers) don't just pull images from your PDFs. Powered by Gemini 3 and Veo 3, they actually generate fluid, documentary-quality animations and motion graphics to explain your sources.

But here’s the catch: there is no post-generation editing. If the video misses the mark, you have to regenerate from scratch. Your prompt and source materials dictate exactly what comes out the other side.

After spending way too much time testing this, here are my top 10 tips for getting production-grade video shorts out of NotebookLM.

1. Pre-Digest with a Multi-Model Stack

Don't just dump raw, messy PDFs into NotebookLM and pray. Use a multi-model approach. Run your initial research through Claude or ChatGPT's Deep Research first. Have them synthesize the information, format it, and export it as a clean Markdown file. NotebookLM reads Markdown perfectly, giving the video engine a highly structured, pre-digested narrative to follow.

2. Use the CPTC Framework for Your Studio Prompt

There's an optional prompt box before you hit generate—use it. The best results come from the CPTC framework:

• Context: "This is a social media short for an audience of marketing executives."
• Persona: "Act as a high-end cinematic video director."
• Task: "Create a 60-second explainer comparing brand-led demand creation versus pure performance marketing."
• Constraints: "No text overlays, rely entirely on visual metaphors."

3. Specify High-End Camera & Lighting Aesthetics

The visual engine (Veo 3) responds incredibly well to specific cinematography terms. Instead of asking for "cool visuals," dictate the exact lens and aesthetic. Ask for "Hasselblad macro photography style," "FPV drone perspectives," or "cinematic volumetric lighting" to ensure the generated motion graphics look premium, not like generic stock footage.

4. Guard Against "Regression to the Mean"

When generating sequential shorts or splitting up topics, AI models tend to over-explain the core premise every time. Add strict anti-repetition guards to your prompt. Use phrasing like: "Do not reintroduce the main topic. Dive immediately into the advanced mechanics and avoid any conceptual regression to the mean."

5. Give the AI a Visual Anchor (e.g., A Mascot)

To maintain visual consistency throughout the short, give the prompt a very specific recurring subject. For example, instruct it to use "a female red fawn French bulldog with a black mask navigating through a 3D data landscape" to represent the user journey. It grounds the abstract concepts into a cohesive visual story that the AI can easily render shot-to-shot.

6. Aggressively Command High-Contrast Elements

If you are generating explainer videos with charts or text, the default styling can sometimes wash out on mobile screens. Explicitly prompt: "Aggressively display high-contrast, bold text labels and data visualizations that fit cleanly within a 9:16 vertical frame without running off the edge."

7. Ditch the Pleasantries

By default, the AI narrators want to introduce themselves and say goodbye. For a viral short, you need a hook in the first 2 seconds. Add a constraint: "Skip all greetings, sign-offs, and introductions. Start immediately with the most controversial or surprising fact."

8. Feed it Structured Arguments, Not Just Facts

The Cinematic Video engine builds narratives based on the tension in your documents. If you want a compelling short, ensure your uploaded Markdown files have a clear "Villain vs. Hero" dynamic. For example, frame the source doc as "The Efficiency Epidemic vs. Omnichannel Growth." The AI will pick up on this contrast and generate visuals that reflect that exact tension.

9. Optimize for the 60-Second Window

While you can generate longer explainer videos, shorts thrive on pacing. NotebookLM tends to pace things like a traditional documentary. Force its hand in the prompt: "Pace the narration and visual cuts rapidly. Cover a new visual concept every 5 seconds to optimize for short-form retention."

10. Iterate the Prompt, Not the Video

Because you can't edit the video once it's rendered, treat your prompt like code. If a generation fails to hit the mark, don't just hit regenerate blindly. Look at why it failed, tweak your CPTC variables, adjust the aesthetic keywords, and run it again.

Sample prompt to put into NotebookLM

The NotebookLM Studio Prompt

Copy and paste this directly into the Studio prompt box before hitting generate. This utilizes the CPTC framework to strictly govern the Veo 3 engine's visual output.

Context: This is a 60-second viral social media short for an audience of AI developers and tech operators. The narrative is a humorous but highly cinematic documentary about a female red fawn French bulldog with a black mask who secretly runs a multi-model AI stack (ChatGPT, Claude, Gemini).

Persona: Act as a high-end cinematic video director specializing in tech documentaries and luxury automotive commercials.

Task: Create an epic, fast-paced video short that visually translates the uploaded document into a dramatic narrative. Contrast the cute, small stature of the bulldog with intense, high-tech hacker visuals.

Constraints:

• Visual Style 1: Use "Hasselblad macro photography style" for extreme, dramatic close-ups of the Frenchie's paws aggressively hitting a mechanical keyboard, and her snout illuminated by the glow of three different monitors.
• Visual Style 2: Utilize "FPV drone perspectives" to show high-speed, sweeping shots flying through the living room, dodging furniture, right up to the dog's high-tech command center.
• Visual Style 3: Bathe all indoor scenes in "cinematic volumetric lighting" (thick, atmospheric shafts of light piercing through the blinds, catching the dust motes and highlighting the Frenchie's red fawn coat and black mask).
• Pacing & Audio: Skip all introductions and greetings. Start immediately with a booming, dramatic bass drop and rapid-fire visual cuts every 3 seconds. No generic stock footage; all generated graphics must look premium, dark, and intense. Ensure the text overlays (Claude, Gemini, ChatGPT logos) are high-contrast and fit within a 9:16 mobile frame.

Are you ready for Good Girl Intelligence?

Want more great prompting inspiration? Check out all my best prompts for free at Prompt Magic and create your own prompt library to keep track of all your prompts.

TL;DR: To get true power-user results, you need to change how you interact with the model. Stop sending follow-up corrections (edit the original instead), start using voice-to-text to dump context, turn off custom instructions for maximum creativity, and leverage features like Projects, Skills, MCP, and Artifacts. Here are 10 proven hacks to get significantly better output from Claude today.

Most people hit their usage limits quickly and get frustrated with generic answers because they do not understand how Claude processes context. After analyzing how power users actually operate, I have compiled the 10 best hacks and use cases you can implement in five minutes.

Here is how to get so good at Claude they cannot replace you.

1. Never Send a Follow-Up Prompt

This is the biggest mistake people make. When you send a follow-up message to correct a mistake, Claude has to re-read the entire chat history up to that point. That means message 30 costs 31x more compute than message 1. You will burn through your message limits incredibly fast.

Instead of typing "No, I meant do it this way," simply scroll up, click edit on your original prompt, fix the instructions, and hit save. You save your token budget and keep the context window perfectly clean.

2. Stop Typing. Start Talking.

Typing naturally limits how much context you provide because it feels tedious. By using a free voice-to-text tool like Wispr Flow, you can speak 4x faster than you type, which means you will naturally provide 4x more context.

Hold a hotkey, dump your entire thought process, explain the nuances, and let the tool turn your lazy, short prompt into a rich, detailed set of instructions.

3. Turn Everything Off for Maximum Creativity

We have been taught that loading up custom instructions makes AI smarter. But if you give Claude too much persistent context, it starts looping the exact same answers and loses its creative edge.

If you want the sharpest, most creative, and most lateral-thinking outputs, empty your settings. A completely blank slate allows Claude to adapt perfectly to the specific prompt you are giving it right now.

4. Drop to Sonnet for Quick Fixes

Stop paying Opus-level compute prices for grammar checks. Opus is designed for deep, complex, multi-step reasoning. If you just need a quick rewrite, formatting help, or a fast brainstorm, open the model picker and drop down to Sonnet.

Matching the model to the task frees up to 70% of your usage budget for when you actually need the heavy lifting.

5. Batch Three Tasks Into One Message

Every time you hit enter, you trigger a reload of the entire context window. If you have three related tasks (e.g., summarize this text, extract the action items, and draft an email to the team), do not send three separate prompts.

Put all three requests into a single, clearly structured prompt. One prompt equals one reload, saving you massive amounts of tokens and keeping you further away from the rate limit.

6. Spread Your Work Across the Day

Claude runs on a rolling 5-hour usage window. If you sit down at 9:00 AM and burn through your entire message limit on a massive coding or writing sprint, you are going to be locked out for the rest of the afternoon.

Pace your deep-work sessions. Use Claude heavily for an hour, then move to execution mode while your limit slowly regenerates.

7. Turn Your Best Chats Into a /Skill

When you finally get Claude to do a complex workflow perfectly, do not let that chat die in your history.

Type /skill-creator and tell Claude to turn the current workflow into a repeatable command. Add "ask me first" so it knows to prompt you for variables next time. You do the hard work of prompting once, and you can reuse it flawlessly forever.

8. Use Projects for Long-Term Memory

If you are working on a codebase, a book, or a massive marketing campaign, stop uploading the same PDFs every day.

Create a Project, upload your brand guidelines, code documentation, or research papers into the Project Knowledge base. Claude will automatically reference this exact context in every new chat you start within that Project.

9. Connect Your Tools with MCP

The Model Context Protocol (MCP) is the biggest unlock of the year. Instead of copying and pasting data between tabs, use MCP servers to connect Claude directly to your local files, your database, or your internal APIs.

You can ask Claude to "summarize the latest notes in my Obsidian folder," and it will actually go read them.

10. Build with Artifacts

Conversations are great for advice, but Artifacts are for building. When you ask Claude to write code, design a landing page, or create a complex SVG diagram, it generates an interactive Artifact on the right side of your screen.

You can see the result instantly, iterate on the design, and copy the final code without ever leaving the window.

Which of these features is saving you the most time right now? Let me know in the comments.

In September 2022, Perplexity AI raised $3.1 million from just 10 seed investors — a group that included the inventors of the Transformer architecture, founding members of OpenAI, and the godfather of deep learning. Those early backers are now sitting on 400–700x paper returns as Perplexity has grown to a $20B+ valuation with $500M in annualized recurring revenue as of mid-2026. No other AI startup's cap table combines elite scientific credibility, strategic insider access, and multi-generational tech pedigree quite like Perplexity's — and that composition helps explain both the company's rapid trajectory and its outsized competitive moat.

The Founding Premise: Why the Cap Table Matters

Investor lists are often dismissed as vanity signaling. In Perplexity's case, the composition carries genuine strategic weight for three reasons:

1. Technical validation at the source. Several seed investors aren't just "AI-adjacent" — they authored the foundational papers that made all modern AI possible. Their investment represents a peer-level technical endorsement.
2. Network-as-moat. Every name on the list is a door into a different part of the AI ecosystem — compute, research, distribution, enterprise, and financial markets.
3. Insider conviction. Several investors committed personal capital while holding senior roles at Google, Meta, and other incumbents — a remarkable signal of conviction about the disruption ahead.

Founding Story: The IIT Madras Kid Who Went to Reinvent Search

Aravind Srinivas was born and raised in Chennai, India — the same city as Google CEO Sundar Pichai. He earned a dual degree in Electrical Engineering at IIT Madras, completed his PhD in Computer Science at UC Berkeley, and then did research stints at the three most powerful AI labs on the planet: Google Brain, DeepMind, and OpenAI — a path very few humans have ever taken.

In 2022, he co-founded Perplexity with Denis Yarats (Facebook AI Research), Johnny Ho (Quora/OpenAI), and Andy Konwinski (Databricks co-founder). The original idea was an AI copilot for SQL queries, but Srinivas pivoted: instead of natural language to database queries, why not rethink how humans search the internet itself? The insight was deceptively simple — stop returning 10 blue links, start returning actual answers with citations. That pivot became the foundation of a company now doing half a billion dollars in recurring revenue.

The Seed Round: Where History Was Written

$3.1 Million, 10 Investors, September 2022

The entire first financing was led by super-angel Elad Gil as the sole investor in the first tranche, with angels joining across subsequent seed tranches. The full seed-round roster:

Investor	Credential	Significance
Yann LeCun	VP & Chief AI Scientist, Meta; Turing Award winner	Godfather of deep learning; invented convolutional neural networks
Andrej Karpathy	Founding member of OpenAI; ex-Head of Tesla AI	One of the world's most respected AI researchers and educators
Ashish Vaswani	Lead author, "Attention Is All You Need"	Co-invented the Transformer architecture that powers ALL modern LLMs
Jakob Uszkoreit	Co-author, "Attention Is All You Need"	Co-inventor of the Transformer
Elad Gil	Super-angel; 40+ unicorns at seed stage	First money into Stripe, Anduril, Harvey, AirBnB, Coinbasel
Nat Friedman	Ex-CEO, GitHub; Co-founder AI Grant	His AI fund with Daniel Gross being partially acquired by Meta for ~$1B at 220% IRRl
Clément Delangue	CEO, Hugging Face	Runs the "GitHub of AI" — the central hub for the global ML research community
Amjad Masad	CEO, Replit	Pioneer of browser-based AI coding environments
Pieter Abbeel	Co-Director, Berkeley AI Research (BAIR)	Pioneered imitation learning and robot training from demonstration
Oriol Vinyals	VP Research, Google DeepMind	Invented sequence-to-sequence learning; creator of AlphaStar

The most profound signal: Vaswani and Uszkoreit co-authored the 2017 paper "Attention Is All You Need" — arguably the single most important AI research paper of the 21st century. That paper introduced the Transformer architecture that underlies GPT-4, Claude, Gemini, Llama, and effectively every powerful language model in existence today. The literal inventors of the mathematical foundation of modern AI wrote personal checks into Perplexity at seed. That is not hype — it is the scientific community voting with its savings accounts.

The Returns Math

• Seed shares priced at $0.83–$2.00 per share
• Latest reported price: ~$629 per share at the $18B valuation benchmark
• A $1 million seed check = approximately $700 million on paper
• That represents a ~700x return in under three years

For context, most institutional VC funds celebrate a 10x return as exceptional. These angels achieved ~70x better than that in a fraction of the typical fund lifecycle.

Series A: The Credibility Compound ($25.6M, 2023)

The Series A, led by New Enterprise Associates (NEA), added several more household names:perplexity+1

• Susan Wojcicki — Ex-CEO of YouTube, who scaled it from a Google acquisition to a $300B+ business
• Paul Buchheit — Creator of Gmail, the product that gave Google its first consumer identity beyond search
• Bob Muglia — Ex-President of Microsoft Server & Tools, ex-CEO of Snowflake
• Soleio — Designer who created Facebook Messenger's core UX and was a key early Figma advisor
• Brad Gerstner — Founder & CEO of Altimeter Capital, one of tech's most respected growth-stage investors

The Series A validated that the product had found real traction beyond the research community, and that top-tier institutional money was willing to back it at a larger scale alongside the technical luminaries who'd seeded it.

Series B and Beyond: The Heavy Artillery ($73.6M → $200M → $1.6B Total)

Series B: Bezos, Nvidia, and the Incumbent Insiders

The $73.6M Series B is where the story became genuinely surreal:thecobf+1

• Jeff Bezos — Founder of Amazon, arguably the most transformative business builder of his generation, betting directly against Google's search dominancegizmodo
• NVIDIA — The company whose GPUs are the physical infrastructure of the AI revolution, investing in one of its most prominent end-user applications
• Jeff Dean — Google's Chief Scientist, who invested while actively serving at Google in a company directly threatening Google's core search business
• Naval Ravikant — Founder of AngelList, one of the most influential voices in startup investing philosophy
• Balaji Srinivasan — Ex-CTO of Coinbase, ex-General Partner at a16z
• Tobias Lütke — CEO of Shopify (>$100B public company), signaling enterprise and e-commerce distribution potential
• Guillermo Rauch — CEO of Vercel, the developer infrastructure platform
• Daniel Gross — Co-Founder of Pioneer.app and AI Grant, one of the early AI incubator architects
• Stan Druckenmiller — Legendary macro investor known for 30+ years of ~30% annual returns; his participation signals confidence in Perplexity as a generational business, not just a hot startup

Later Rounds: Institutional Scale

Subsequent rounds brought in:startupintros+1

• SoftBank Vision Fund 2 — One of the world's largest technology investment vehicles
• Accel — Led a round at a $14B valuation
• IVP — Led a $500M+ round
• Bessemer Venture Partners — Top-tier multi-stage VC with deep enterprise software expertise
• Databricks — Strategic investor with deep data infrastructure alignment
• DAMAC Group — Middle East sovereign-adjacent capital, expanding Perplexity's global backer base

Total raised as of mid-2026: ~$1.6 billion across 9+ rounds.

Perplexity vs. Peers: A Cap Table Comparison

Dimension	Perplexity	OpenAI	Anthropic
Seed investors	Transformer paper authors, OpenAI founders, Meta AI chief	YC, Reid Hoffman, Peter Thiel	No traditional seed round
Primary institutional backers	NEA, IVP, Accel, Bessemer, SoftBank	Microsoft ($13B), Thrive Capital	Google, Amazon, Spark Capital
Strategic / corporate investors	NVIDIA, Databricks, SoftBank	Microsoft (full integration)	Google ($2B+), Amazon ($4B+)
Notable angels	LeCun, Karpathy, Vaswani, Bezos, Jeff Dean, Stan Druckenmiller	Reid Hoffman, Khosla Ventures	—
Current valuation (2026)	~$20–22.6Bsacra+1	~$300B+	~$380B
ARR (mid-2026)	~$500M+economictimes.indiatimes	~$10B+	~$3-4B (est.)

The critical distinction: Perplexity's cap table is anchored by the scientists who built the tools that OpenAI and Anthropic rely on. That's a different category of credibility signal.

What This Means for Perplexity's Trajectory

1. The "Unfakeable Signal" Effect

When the lead author of "Attention Is All You Need" and a founding member of OpenAI both write personal seed checks into a company, that isn't marketing — it's a technical endorsement from people who understand the underlying architecture better than anyone alive. They aren't investing in a pitch deck; they're investing in a thesis they helped create.

2. The Strategic Network Moat

Each investor category opens a different strategic door:

• Nvidia = preferential GPU access and compute pricing discussions
• Bezos = AWS infrastructure, Amazon distribution, and e-commerce search partnerships
• Nat Friedman / Daniel Gross = the open-source AI research community pipeline
• Tobi Lütke = enterprise SaaS and e-commerce vertical expansion
• Stan Druckenmiller = macro credibility and signals to other institutional investors

3. Insider Bets Against Incumbents

Jeff Dean (Google Chief Scientist) and Yann LeCun (Meta Chief AI Scientist) invested from inside their respective companies. These are not outsiders speculating on disruption — they're people with real-time visibility into how incumbents are (or aren't) responding to the AI search threat. Their personal conviction, expressed in dollars, is one of the most telling signals in the entire AI funding landscape.

4. The Agentic Pivot: Where the Money Is Going

The cap table is no longer just backing an AI search engine. Perplexity pivoted in early 2026 to "Perplexity Computer" — an agentic platform that orchestrates 19 specialized AI models in parallel to complete complex multi-step tasks autonomously. This is a direct expansion from answering questions to doing work — a significantly larger TAM than search. Revenue surged 50% in a single month (March 2026) after this pivot.

Business Performance: The Numbers Behind the Hype

The investor list would be a parlor trick if the fundamentals didn't back it up. They do:

Metric	Value	Source / Period
ARR	$500M+	April 2026
ARR YoY Growth	335%	vs. 2025
Monthly Queries	780 million	Early 2026
Active Users	45 million	2026
Valuation	$20–22.6B	Late 2025 / Early 2026
Total Funding Raised	~$1.6B	9+ rounds
Headcount Growth vs. Revenue Growth	34% headcount vs. 5x revenue	2025–2026

The efficiency metric is striking: Perplexity 5x'd its revenue while growing its team by only 34%. In an era of AI companies burning capital at extraordinary rates, this is a meaningful signal of product-led efficiency.

A 2025 Sacra research projection estimated Perplexity could reach $656M ARR by end of 2026 — the company is tracking to hit or exceed that figure ahead of schedule.

Risks and Counterarguments

A balanced analysis requires acknowledging what the stacked cap table does not guarantee:

• Legal and content licensing exposure: Perplexity has faced copyright disputes and content scraping allegations from publishers, which remain unresolved at scale.
• Winner-take-all dynamics: The AI search space may consolidate around one or two platforms — and Google's AI Mode, ChatGPT Search, and Microsoft Copilot are formidable, well-resourced competitorsrankdraft+1
• Valuation multiple risk: At $20B+ on $500M ARR, the revenue multiple (~40x) is compressed but still premium. Any growth deceleration could pressure secondary market valuations significantly
• Dependency on third-party models: Perplexity does not train its own foundational models; it orchestrates outputs from multiple providers. This creates a structural dependency that could become a cost or access risk
• The "feature not a company" critique: Google and OpenAI can and have shipped AI search products. The question of whether Perplexity's approach remains differentiated as incumbents invest billions in similar capabilities is the central long-term risk

Perplexity's investor list is the most technically credentialed cap table in the AI era — and possibly in the history of tech. The combination of the Transformer paper co-authors, OpenAI's founding members, Meta's Chief AI Scientist, Google's Chief Scientist, Jeff Bezos, Stan Druckenmiller, and NVIDIA across a single cap table is genuinely unprecedented.

More importantly, this isn't just prestige accumulation. Each investor represents a strategic resource: compute access, research networks, enterprise distribution, financial credibility, and technical talent pipelines. In a market where the difference between winning and losing may come down to who gets GPUs at cost, which enterprise accounts trust you first, and which top researchers join your team — Perplexity's cap table is a structural competitive advantage, not just a marketing asset.

The company has backed up investor conviction with real business performance: $500M ARR, 335% growth, and an agentic product pivot that has dramatically expanded its total addressable market. Whether it can ultimately challenge Google's search dominance at scale remains an open question — but the people who understand AI best put their own money on it first.

TL;DR: Claude Fable 5 is back and completely free to use in your Claude subscription plans until July 7, when it moves to a strict paid usage credit model. Fable 5 is not just a slightly better AI - it is a fundamentally different capability tier designed for deep, complex problem-solving. Do not waste this free window on writing emails or summarizing documents. Instead, use these 5 specific prompts to tackle your hardest technical problems, complex business decisions, and massive system builds before the window closes.

Fable 5 is not Sonnet with better vibes. It is a fundamentally different capability tier. To put it in perspective: Stripe gave Fable 5 a 50-million-line Ruby codebase and asked it to complete a migration that would have taken a team of engineers more than two months. Fable 5 did it in one day.

That is not a productivity improvement. That is a different category of capability entirely.

From July 8, it moves to paid usage credits. Here are the top 5 things you need to build before the free window closes:

1. Solve Your Hardest Technical Problem

Take the thing your team has been stuck on for weeks. The bug nobody can find. The architecture decision nobody can agree on. The migration that feels impossible. Give it to Fable 5 with full context and watch what happens.

Prompt:

"Here is a technical problem I have been unable to solve: [describe the system, what you have tried, where it breaks down]. Work through this methodically. Do not stop until you have a complete solution or a clear explanation of why a solution is not possible."

2. Resolve Your Most Complex Business Decision

Not a simple choice. The one you have been going back and forth on for weeks. The strategic pivot. The hire or no hire. The pricing overhaul. Give Fable 5 everything and run the full Council Protocol on it.

Prompt:

"This is the most important business decision I am facing right now: [describe in full]. Run the complete Council Protocol: five advisors, Chairman verdict, logic leak analysis, pre-mortem, final recommendation. Do not give me a balanced answer. Give me a verdict."

3. Build a Complete System From Scratch

Tell Fable 5 to build something end to end. A workflow. A framework. A content system. A business process. Give it the goal and the constraints and let it design the whole thing without you directing every step.

Prompt:

"I want you to build a complete [system] for [goal]. Here are my constraints: [list]. Design the full architecture, the components, how they connect, and how I implement it. Do not ask me questions. Make the best decisions you can and show your reasoning."

4. Conduct Deep Research on Your Biggest Opportunity

Not surface research. Three levels deep. Find what nobody else in your field has found. Synthesize across everything you give it. Identify the gap nobody is talking about.

Prompt:

"Here is the opportunity I am exploring: [describe]. Here are all the sources and information I have: [paste everything]. Go three levels deep. Find what most people miss. Give me the insight that changes how I think about this—not the insight I already have."

5. Tackle the Thing You Have Been Avoiding

Every person has a task they keep putting off because it feels too big or too complex. Give it to Fable 5 today. All of it. The full context. The full complexity. The full stakes. Fable 5 was built for exactly this.

Prompt:

"I have been avoiding this massive task: [describe task, stakes, and why it is overwhelming]. Break this down into an execution plan that I can start immediately. Act as a senior project manager and structure the first three steps so clearly that I cannot fail."

Everything gets a lot more expensive after July 7th.

Open Fable 5 now and run one of these today.

What are you building first? Let me know in the comments.

TL;DR: The US government just ended its two-week ban on Claude’s latest model, Fable 5. It is incredibly powerful, but you only have a few days to test it freely. Starting July 7th, Fable 5 moves to a strict pay-per-use model and will no longer be included in the standard $20 or $200/month subscription plans. Use it now while it is still covered by your subscription, and use Anthropic’s official 8-part prompt structure (detailed below) to get the best results.

The US government just ended the two-week ban on Claude's latest model, Fable 5.

If you have been waiting to see what all the hype is about, your window is right now. You need to test Fable 5 over the next few days, because starting July 7th, the pricing model completely changes.

After July 7th, Fable 5 will no longer be included in the standard $20/month Pro or $200/month Team subscription plans. It is moving to a strict pay-per-use model, which means it is going to get significantly more expensive for heavy users.

Right now, it is still accessible within your current plan limits. This is your chance to push the model to its absolute limits without worrying about API costs racking up.

But if your prompt looks like a casual question, you are doing it wrong.

Claude Fable 5 works best when the task is clear, hard, and grounded. To get the most out of your testing this week, you need to use the exact 8-part prompt structure that Anthropic officially recommends.

Here is how to prompt Claude Fable 5, using a real-world marketing use case as an example.

The 8-Part Fable 5 Prompt Structure

1. Start with Purpose
   Tell Claude why you are asking. Show the bigger goal first.
   Example: "I am building a 90-day go-to-market plan for a new B2B SaaS tool. The goal is to help our marketing team generate early leads, test our messaging, and decide on our final positioning."

2. Set a Real Task
   Be clear about what you need. Ask for a finished result, not just ideas.
   Example: "Build a comprehensive 12-week marketing sprint plan. Make each week simple, actionable, and tied to a specific metric. End with a clear launch-readiness checklist."

3. Feed it Real Context
   Do not make it guess. Give the product, team, limits, risks, and goals.
   Example: "Product: AI analytics dashboard for mid-market e-commerce. Team: One product marketer and one content writer. Resources: $5,000 ad budget and an existing email list of 2,000 cold leads. Risks: High churn in the first 30 days and unclear differentiation from competitors."

4. Choose the Effort Level
   Use low, medium, high, or xhigh. Match the effort to the size of the task.
   Example: "Use high effort for this task. Focus on deep strategic thinking, realistic timelines, and careful checks against our budget."

5. Set Clear Boundaries
   Tell Claude what not to do. Stop extra work, overplanning, and useless add-ons. Ground the progress.
   Example: "Act when you have enough information. Do not add extra marketing channels we do not have the budget for (like massive influencer campaigns). Keep the plan lean, focused, and strictly within the $5k budget."

6. Ask Claude to Check Claims Against Real Results
   If something is not proven, it should say so.
   Example: "Before giving the final answer, verify that every marketing action links to one of our core risks: churn or differentiation. If an expected conversion rate is not proven, call it an assumption. Do not invent fake metrics or guaranteed results."

7. Define the Stop Point
   Tell Claude what must be done before it ends. This keeps the work focused and complete.
   Example: "Only stop when you have a complete 12-week plan. Each week must have 3–4 specific actions. Each action must have an owner, a budget allocation, and an expected output. End with the final launch decision checklist."

8. Control the Output
   Tell Claude exactly how to answer.
   Example: "Present it as a weekly sprint plan table. For each action, show: Week, Action, Owner, Budget, and Success Measure. Make it clear, easy to read, and ready to paste into our project management tool."

Claude Fable 5 Master Prompt Template

[PURPOSE]
I am building [describe your project/goal].
The goal is to [explain the bigger objective].
The output should give me [what you need to walk away with].

[TASK]
Build/Create/Write [specific deliverable].
Make each [section/step/item] simple and easy to act on.
End with [final deliverable or checklist].

[CONTEXT]
Product: [what you are building or selling]
Team: [who is involved and their roles]
Resources: [budget, tools, existing assets]
Risks: [what could go wrong or block progress]
Goals: [specific metrics or outcomes you are targeting]

[EFFORT]
Use [low / medium / high / xhigh] effort for this task.
Focus on [deep thinking / speed / precision / creativity].
Do not spend time on [things that do not matter for this task].

[BOUNDARIES]
Act when you have enough information.
Do not add [extra features, frameworks, or work I did not ask for].
Keep the output [simple / focused / within X constraints].
Do not [specific things to avoid].

[VERIFICATION]
Before giving the final answer, check that every [action/recommendation/claim] links to [a specific goal, risk, or metric].
If something is not proven, call it an assumption.
Do not invent [numbers, feedback, results, or data].

[STOP CONDITIONS]
Only stop when you have [specific completed deliverable].
Each [section/week/item] must have [X number of actions or elements].
Each [action/item] must have [owner, timeline, metric, or output].
End with [final summary, checklist, or decision framework].

[OUTPUT FORMAT]
Present it as a [weekly plan / table / checklist / brief / report].
For each [item/action], show: [Field 1], [Field 2], [Field 3], [Field 4].
Make it clear, easy to read, and ready to [paste into a tool / share with my team / execute immediately].

If you paste that entire block into Fable 5 today, you will see exactly why the government was so nervous about this model. The reasoning depth is unmatched.

Go test it right now before the July 7th paywall hits.

What are you going to build with Fable 5 this week? Let me know in the comments.

Want more great prompting inspiration? Check out all my best prompts for free at Prompt Magic and create your own prompt library to keep track of all your prompts.

TL;DR: Stop debating which AI is better. Claude is your deep-thinking research analyst (best for long documents, context, and academic writing). ChatGPT is your Swiss Army knife (best for versatility, brainstorming, and execution). The secret isn't picking one - it's knowing when to use each tool.

Both ChatGPT and Claude are incredibly powerful tools. They just excel at completely different things.

After spending extensive time working with both platforms, here is what stands out:

Claude shines when you need deep thinking

If your work involves heavy reading, researching, or in-depth writing, Claude is remarkably strong. It excels at:

• Analyzing very long documents and extracting insights from large files.

• Summarizing complex reports and document reviews.

• Producing formal, polished, academic, and professional writing.

• Maintaining deep context in lengthy, nuanced conversations.

ChatGPT shines when you need versatility

If you need a multi-purpose assistant that can handle a little bit of everything, ChatGPT is hard to beat. It excels at:

• Content creation and rapid brainstorming of ideas.

• Coding, debugging, and productivity workflows.

• Switching quickly between different tasks and modalities.

• Handling voice conversations and built-in image generation.

The professionals who are getting the biggest results aren't fiercely loyal to one tool. They are simply choosing the right tool for the specific task at hand.

They use Claude for deep analysis, policy review, and refined writing.
They use ChatGPT for rapid execution, marketing content, and multi-modal productivity.

The real advantage is knowing exactly when and how to use each tool.

I put together an infographic highlighting the key differences between Claude and ChatGPT.

Which one do you use most often, and what specific tasks do you use it for?

👇 Let me know in the comments.

7 prompts to make ChatGPT stop sounding like a robot (and one master prompt that does it all)

TL;DR: ChatGPT sounds robotic when given generic instructions. To make it sound human, you have to give it perspective, constraints, and personality. Below are 7 specific prompts to fix AI writing—from removing AI patterns to adding human thinking - plus a Master Prompt that combines them all into one powerful instruction.

ChatGPT can sound robotic if you use generic prompts, but small changes in how you guide it can completely change the tone.

The key is not asking it to sound human, but giving it context, perspective, constraints, and a clear voice to follow.

These 7 prompts will help you get writing that feels more natural, less predictable, and closer to how real people communicate.

1. Real Experience Voice

Prompt:
"Rewrite this content from the perspective of someone who has actually done the work. Remove generic advice and replace it with specific observations, lessons, and insights that come from real experience. Keep the tone natural and conversational."

2. Remove AI Patterns

Prompt:
"Rewrite this text and eliminate every sign of AI writing. Remove repetitive sentence structures, predictable transitions, unnecessary filler, and overexplaining. Vary sentence length naturally and make the writing feel spontaneous rather than generated."

3. Add Human Thinking

Prompt:
"Rewrite this content by showing how a real person would think through the topic. Include observations, tradeoffs, questions, doubts, and insights where relevant. Make the writing feel thoughtful rather than perfectly polished."

4. Natural Conversation Flow

Prompt:
"Rewrite this as if you are talking directly to one intelligent friend. Use natural conversational language, occasional short sentences, and smooth transitions. Prioritize connection and clarity over perfect grammar or formal writing."

5. Stronger Writing Personality

Prompt:
"Rewrite this content with a stronger personality. Add conviction, unique phrasing, clear perspectives, and emotionally engaging language. Avoid sounding corporate, robotic, or overly neutral."

6. Make It Believable

Prompt:
"Rewrite this content so every sentence feels believable and authentic. Replace vague claims with specific details, realistic examples, practical explanations, and natural language that builds trust without sounding promotional."

7. Elite Human Editor

Prompt:
"Rewrite this like a top editor preparing it for publication. Improve clarity, flow, credibility, and engagement. Remove anything that feels artificial, generic, or AI-generated while preserving the original message."

Master Prompt: The Human Voice Override

If you want to apply all of these principles at once without running 7 separate prompts, use this Master Prompt on your first draft:

Master Prompt:
"Rewrite this content to sound entirely human, authentic, and written by an expert who has actually done the work. Eliminate all signs of AI writing—remove repetitive sentence structures, predictable transitions, unnecessary filler, and overexplaining.

Write as if you are talking directly to one intelligent friend, using natural conversational language, varied sentence lengths, and occasional short sentences.

Show human thinking by including observations, tradeoffs, and insights, making the writing feel thoughtful and spontaneous rather than perfectly polished. Inject a strong personality with conviction and clear perspectives, avoiding corporate or neutral tones.

Finally, act as an elite editor: replace vague claims with specific, realistic examples to build trust, ensuring every sentence feels believable, engaging, and ready for publication."

What’s the best way you’ve made AI sound more natural? Let me know below.

Want more great prompting inspiration? Check out all my best prompts for free at Prompt Magic and create your own prompt library to keep track of all your prompts.

TL;DR: The AI tools that worked great 6 months ago are falling behind. I audited 14 daily workflows and rebuilt my entire stack. From search and writing to coding and video editing, here is the exact list of tools that are currently winning, and why you should pick one to switch this week to let your stack compound.

After spending hundreds of hours testing the latest models, workflows, and platforms, I realized something important: The tools that won in 2025 are not winning now. The old tools are not dead, but the new ones are quietly pulling ahead.

Here are 14 jobs, and the tool that won each one for my 2026 stack.

1. Search: Google → Gemini → AI Mode

Traditional search is becoming a backup plan. Moving from Google to Gemini was a step forward, but native AI Mode search—where the engine synthesizes real-time web data into a clean, ad-free answer—is the undisputed winner for 2026.

2. Browser: Chrome → Arc → Claude for Chrome

Chrome was the standard, and Arc brought better organization. But Claude for Chrome integrates deep AI capabilities directly into the browsing experience, turning the browser itself into an active research and reading assistant.

3. Writing: Gemini → ChatGPT → Claude

ChatGPT is still incredibly versatile, but for deep, nuanced, and human-sounding writing, Claude has taken the crown. It understands context better and requires far less prompting to remove that "robotic AI" tone.

4. Code: Claude → Cursor → Claude Code

Cursor revolutionized AI-assisted coding, but Claude Code takes it a step further. It handles complex, multi-file architecture changes with a level of precision that feels like having a senior engineer looking over your shoulder.

5. Research: Google → ChatGPT → Perplexity

When you need cited, accurate, and deep research, Perplexity is the only tool that matters right now. It bridges the gap between a search engine and a research analyst flawlessly.

6. Automation: Make → n8n → Claude Routines

Make and n8n are powerful, but Claude Routines simplifies complex, multi-step agentic workflows without needing a degree in API management.

7. Design: Canva → Figma → Claude Code

Canva is great for quick social posts, and Figma rules UI. But for generating functional, code-backed designs and prototypes instantly, Claude Code is changing how we go from idea to visual execution.

8. Image: Nano Banana → GPT Image 2.0 → Higgsfield

Image generation is moving fast. While GPT Image 2.0 is highly capable, Higgsfield is producing the most stunning, controllable, and hyper-realistic visual assets for 2026.

9. Video Editing: CapCut → Premiere → HyperFrames

HyperFrames is doing to video editing what AI did to copywriting. It automates the tedious timeline work while giving you incredible creative control over the final cut.

10. Avatars: Captions → Synthesia → HeyGen

HeyGen has perfected the AI avatar. The lip-sync, micro-expressions, and voice cloning are now so good that it is practically indistinguishable from a real studio shoot.

11. Voiceover: Murf → Fish Audio → ElevenLabs

ElevenLabs remains the undisputed king of AI voice generation. The emotional range, pacing, and sheer quality of their voices make everything else sound synthetic.

12. Notes: Otter → Fireflies → Granola

Granola doesn't just transcribe your meetings; it actively structures the information, pulls out the exact action items you care about, and formats it beautifully without you lifting a finger.

13. Slides: PowerPoint → Gamma → Claude in PowerPoint

Gamma made presentations fast, but Claude integrated directly into PowerPoint brings deep analytical thinking and precise formatting into the enterprise tool everyone already uses.

14. Email: Gmail → Superhuman → Gmail Connector

Superhuman made email fast, but the Gmail Connector automates the triage, drafting, and follow-ups using your own historical context. It’s not just a client; it’s an executive assistant.

The landscape is shifting faster than ever. You don't need to change everything today. Pick one job, switch the tool this week, and learn its nuances.

That is how the stack compounds.

Which tool in your stack is feeling the most outdated right now? What new tool is getting the job done better? Let me know in the comments.

Your brand’s AI reputation is being written on Reddit, with or without you.

TL;DR: Getting banned from Reddit subreddits while trying to promote your brand is a waste of time and humiliating. The actual play is to create your own branded subreddit - it's 100% free, your content can never be deleted by a power-hungry moderator, and every post you publish feeds the AI models that ChatGPT, Gemini, and Google use to answer buyer questions. In 2026, owning a subreddit is owning your AI search reputation. Here's how, with 20 real brand examples.

Let me be blunt: spending hours lurking in subreddits, crafting the perfect post, only to have it insta-deleted by a power-hungry moderator is not a strategy.

You spend 45 minutes writing something genuinely valuable, drop it in r/[YourIndustry], and within 10 minutes it's gone. No explanation. Sometimes you even get banned. You stepped into someone else's kingdom and they didn't like it. Here's the fix: build your own kingdom.

Why Your Own Subreddit Is the Best Move in 2026

• You are the moderator. Your content stays up forever. No one can delete your posts.
• It's completely free. Reddit charges $0 to create a subreddit — zero.
• Your posts train ChatGPT and Gemini. OpenAI and Google have both signed licensing deals with Reddit worth over $130M/year combined to use Reddit content to train their models. Every post in your subreddit feeds those models. When a buyer asks ChatGPT "What's the best [your product category]?" — your subreddit content is part of the answer.
• Reddit is the #1 most-cited domain in AI — 40.1% of all AI citations come from Reddit, more than Wikipedia and YouTube combined .
• Reddit appears in 97.5% of Google product-review queries . A subreddit you own is permanent real estate in the most important search category for buyers.
• 63% of brand-adjacent Reddit threads are negative if you didn't build them . Someone is already talking about your brand. Shape the conversation or let it shape you.

Top 10 B2B Branded Subreddits

Brand	Subreddit	Members	Why It Works
Anthropic (Claude)	r/ClaudeAI	~957K	Grew 291% YoY — fastest-growing AI community. Developer organic advocacy drives viral "wow moments."
Anthropic	r/Anthropic	~165K	AI safety & research; +1,249 members per day.
Notion	r/Notion	~460K	Template sharing, productivity discussions; 13%+ YoY growth.
Salesforce	r/salesforce	~93K	Certification help, dev discussions; 22% YoY growth.
HubSpot	r/hubspot	~13K	Growing 55% YoY — massive first-mover opportunity still available.
Figma	r/FigmaDesign	~125K	Design tutorials, community showcases — high engagement quality.
Tailscale	r/Tailscale	Growing	Branded support + SEO/AEO asset; the SaaS startup model to copy.
Shopify	r/shopify	~300K+	E-commerce operator hub; high buyer intent.
GitHub	r/github	~130K+	Developer support, open source showcases.
Zapier	r/zapier	~10K	Automation use cases — extremely high intent buyers.

Top 10 B2C Branded Subreddits

Brand	Subreddit	Members	Why It Works

Brand	Subreddit	Members	Why It Works
Starbucks	r/starbucks	~283K	Customer stories, drink hacks, employee culture — authentic feel.
Wendy's	r/wendys	~59K	Brand voice shines; 41% YoY growth. Community + meme culture.
Mint Mobile	r/mintmobile	~56K	Drives 44% of all social referrals and 100K+ website visits/month — the gold standard for small brand Reddit ROI.
Apple	r/apple	~1.5M+	Tech product community; massive organic reach for launches.
Tesla	r/teslamotors	~2M+	Owner community shaping AI answers about EVs.
Xbox	r/XboxSeriesX	~1.5M+	Gaming community; product launches and hardware discussion.
Nike	r/Nike	~250K+	Sneaker drops, product feedback, brand culture.
Lego	r/lego	~3M+	MOC showcases — extremely high engagement; brand love amplified.
Duolingo	r/duolingo	~1M+	Mascot culture and streak memes fueled a 25,000% increase in cross-platform brand mentions .
Steam	r/Steam	~2M+	Gaming deals, platform support — massive buyer intent.

The AI Visibility Play Everyone Is Missing

Reddit posts in 2026 are simultaneously social content, Google SEO real estate, and AI training data. OpenAI licensed Reddit content for ~$70M/year and Google for ~$60M/year . The content formats that get cited most by AI engines: Q&A structure (50%+ of citations), expert quotations (+41% citation lift), clear statistics (+34%), and content refreshed within 30 days (3.2x more citations) . When you post a well-structured Q&A in your own subreddit, you are literally writing the script AI models will repeat to your buyers.

Fewer than 500 branded subreddits exist at meaningful scale right now . The window is wide open.

How to Know Where You Stand Right Now

Want to see what Reddit — and the AI engines trained on it — currently think about your brand? I built a free tool for exactly this.

👉 thinkingdeeply.ai

Input your website URL, your top 3 competitors, and your subreddit (if you have one). You get: a four-engine AI probe (Claude, OpenAI, Gemini, Perplexity), a full Reddit conversation audit with the threads AI engines are actually citing, an A-to-F letter grade for your Reddit reputation, and a one-click PDF export to share with your team. It's free — no sales call, just the truth.

Post your favorite brand subreddit in the comments or share the brand subreddit you are building and tell us why it's awesome.

TLDR: Here is how to make ChatGPT simulate the missing roles on your content team: strategist, hook writer, competitor analyst, trend scout, carousel architect, niche researcher, and final editor. Below are seven copy-paste prompts for finding viral ideas, writing hooks, analyzing competitors, hijacking trends, building carousels, predicting micro-trends, and pressure-testing content before you post.

The 7-Prompt Viral Content Stack

Prompt	What it does	When to use it
1. Viral Idea Strategist	Generates differentiated ideas with emotional triggers and platform fit.	When your content calendar is empty.
2. Scroll-Stopping Hook Writer	Creates multiple hook angles and scores them.	Before writing any Reel, Short, post, or thread.
3. Competitor Psychology Analyst	Reverse-engineers why competitor content performs.	When someone in your niche keeps winning attention.
4. Trend Hijack Strategist	Adapts trends to your niche without making you look cringe.	When a meme, audio, format, or debate is moving fast.
5. Save-Worthy Carousel Architect	Builds a slide-by-slide carousel designed for saves and shares.	When you want educational content people bookmark.
6. Micro-Niche Trend Scout	Finds underserved sub-niches and early angles.	When your niche feels saturated.
7. 3-Second Hook Surgeon	Creates and rates hooks based on scroll-stop power.	When your idea is good but the packaging is weak.

Prompt 1: Find Viral Content Ideas

Use this when you have no idea what to post next. The key is that it does not just ask for “ideas.” It forces ChatGPT to explain the emotional trigger, the platform format, and the reason the post could spread.

Prompt:

Act as a viral content strategist.

You are a viral content strategist with 10+ years of experience growing social media accounts to millions of followers. Your task is to generate 15 highly viral content ideas for a creator in the [NICHE] space targeting [AUDIENCE].

For each idea, provide:

1. A punchy content title, max 10 words
2. The core emotional trigger it hits: curiosity, shock, inspiration, FOMO, relatability, identity, status, relief, or useful pain
3. The ideal platform format: Reel, Carousel, Static Post, Story, X thread, Reddit post, LinkedIn post, YouTube Short, or newsletter section
4. A one-sentence reason WHY this will spread
5. The likely comment this post will trigger from the audience

Rules:
- Avoid generic topics already overdone in the niche
- Each idea must have a unique angle or contrarian take
- Prioritize content that triggers saves, shares, comments, or DMs
- Think about what people would send to a friend at 2am
- Do not give me vague topics; give me postable angles

Output in a numbered list, formatted cleanly.

Pro tip: Add three examples of your best-performing posts before running this. ChatGPT performs better when it can infer your voice, audience, and proven patterns.

Upgrade line to add:

Before generating ideas, ask me 5 questions that would help you avoid generic content.

Prompt 2: Generate Scroll-Stopping Hooks

A weak hook kills a good idea. This prompt makes ChatGPT generate many angles instead of giving you one “clever” line and calling it done.

You are the world's best short-form video hook writer. Your hooks have generated billions of views across Instagram Reels, TikTok, YouTube Shorts, LinkedIn, X, and Reddit. Your job is to write hooks that make it extremely difficult for the right audience to scroll away.

My content topic: [TOPIC]
My niche: [NICHE]
My target audience: [AUDIENCE]
My platform: [PLATFORM]
My tone: [DIRECT / FUNNY / CONTRARIAN / EDUCATIONAL / RAW / PREMIUM / CHAOTIC]

Generate 20 hook variations for this topic using ALL of these formats:

1. Bold Claim Hook: “Nobody talks about [X], but...”
2. Contradiction Hook: “Everything you know about [X] is wrong...”
3. Curiosity Gap Hook: “I found a [X] that...”
4. Relatability Hook: “If you've ever felt like...”
5. Urgency Hook: “Stop doing [X] before it's too late...”
6. Number Hook: “I did [X] for 30 days and...”
7. Question Hook: “What happens when you...”
8. Story Hook: “6 months ago I was...”
9. Confession Hook: “I was wrong about [X]...”
10. Enemy Hook: “The real reason [X] keeps failing is...”

For each hook, rate it 1-10 for:
- Scroll-stop power
- Curiosity level
- Relatability
- Click-through potential
- Risk of sounding clickbaity

Rewrite the top 5 hooks so each one sounds like a real person talking, not a marketer writing copy.

Then crown the TOP 5 hooks and explain exactly why they will perform.

Pro tip: Ask ChatGPT to produce one batch that is “safe,” one batch that is “spiky,” and one batch that is “borderline too honest.” The best hook is usually hiding in the spiky batch.

Prompt 3: Steal Competitor Psychology

Do not steal someone’s content. Steal the psychology behind why it worked.

This prompt turns competitor research into an ethical teardown. The goal is to understand the pattern, not copy the post.

You are a competitive intelligence analyst for social media creators. I want to understand exactly WHY my competitor's content performs so well so I can extract the winning formula and apply it to my own brand ethically.

Competitor account: [USERNAME OR DESCRIBE THEIR ACCOUNT]
Their niche: [NICHE]
Their approximate follower count: [NUMBER]
My niche, same or adjacent: [YOUR NICHE]
My audience: [AUDIENCE]
My positioning: [WHAT MAKES YOU DIFFERENT]

First, ask me to share their top 5 most viral posts. After I share them, perform a deep competitor content autopsy.

For each viral post, analyze:

1. Hook analysis: What made the first 3 seconds or first line irresistible?
2. Structure breakdown: How is the content structured from beginning to middle to end?
3. Psychological triggers: What emotions or identity signals are being activated?
4. Visual pattern: Colors, text placement, editing style, pacing, layout, or format
5. Engagement drivers: What specific element is generating comments, saves, shares, or debate?
6. Audience desire: What does this post reveal the audience secretly wants?
7. Gaps: What did they not cover that I could do better?

Then identify macro patterns:
- What content pillars do they consistently post?
- What topics do they avoid that could become my opportunity?
- What is their content-to-promotion ratio?
- What is their audience saying in comments that reveals demand?
- Which formats are doing the most work: stories, tutorials, hot takes, frameworks, lists, case studies, or templates?

Finally, give me an action plan:
- 3 things I should copy strategically, not literally
- 3 things I should deliberately do differently
- 5 post ideas that use the same psychology but a different angle
- My unique positioning statement versus this competitor

Separate what is actually observable from what you are inferring. Mark each insight as OBSERVED or INFERRED.

Important: Do not copy their wording, structure, or creative. Extract the principles and build original content.

Pro tip: Paste actual post text, screenshots, captions, comments, and performance numbers if you have them. The more real evidence you provide, the less ChatGPT has to guess.

Prompt 4: Trend Hijack Without Looking Desperate

Trend-jacking works when the trend feels native to your niche. It fails when your audience can smell that you are chasing reach.

You are a trend-jacking expert who helps creators ride viral waves without looking desperate, forced, or out of touch. I am in the [NICHE] space.

Current viral trend, audio, meme, debate, format, or news hook: [DESCRIBE TREND]
My audience: [AUDIENCE]
My brand personality: [PROFESSIONAL / FUNNY / EDUCATIONAL / RAW / INSPIRATIONAL / CONTRARIAN / PREMIUM]
My platform: [PLATFORM]
My risk tolerance: [LOW / MEDIUM / HIGH]

Your task:

1. Show me exactly how to adapt this trend to my niche in 3 different ways
2. For each adaptation, write the video concept, hook line, on-screen text, caption, and CTA
3. Tell me the ideal posting window to maximize reach
4. Give me a safety rating from 1-10 for how risky this trend is for my brand
5. Suggest a unique twist that makes my version more shareable than the original trend
6. Tell me what would make this trend feel forced and how to avoid that

Prioritize authenticity. My audience should feel this is native to my content, not bolted on for reach.

Explain the psychological reason this trend is spreading before adapting it to my niche. Identify the mechanism behind the trend. Is it surprise, identity, conflict, nostalgia, wish fulfillment, humiliation, insider status, or a before/after transformation? Once we know the mechanism, you can adapt the trend without copying the surface.

Prompt 5: Create Save-Worthy Carousels

Carousels work when every slide earns the next swipe. Do not ask for “a carousel.” Ask for a save-worthy blueprint.

You are a carousel content architect who creates Instagram, LinkedIn, and X carousel posts that rack up saves, shares, comments, and profile visits. Educational carousels work when they are simple, scannable, and immediately useful. Build me a complete carousel.

Topic: [TOPIC]
Niche: [NICHE]
Audience: [AUDIENCE]
Number of slides: [7 / 10 / 12]
Carousel goal: [MAX SAVES / FOLLOWERS / PROFILE VISITS / LINK CLICKS / COMMENTS]
Tone: [PRACTICAL / CONTRARIAN / BEGINNER-FRIENDLY / ADVANCED / FUNNY / DIRECT]

Build a complete slide-by-slide carousel blueprint:

1. Slide-by-slide outline: title for each slide and what text goes on it
2. Headline options: 5 scroll-stopping title variations for Slide 1
3. Hook strategy: how Slide 1 earns the swipe
4. Curiosity flow: how each slide creates curiosity for the next
5. Key points: concise content for each slide
6. Visual suggestions: icons, layouts, screenshots, diagrams, or graphics for each slide
7. CTA options: 3 call-to-action variations for the final slide
8. Caption: write a high-converting caption
9. Hashtags: 15 relevant hashtags, mixed broad, niche, and timely
10. Save/share triggers: what makes this irresistible to save or share
11. Weak-slide audit: identify the slide most likely to lose attention and improve it

Make it simple, scannable, and packed with value. Every slide should feel “save this” worthy.

Conduct a weak-slide audit. Most carousels lose people in the middle because the slides repeat the same point in different words.

After building the carousel, compress every slide by 30% while keeping the value intact.

Prompt 6: Predict Trends Before Everyone Else

If everyone in your niche is posting the same thing, you are late. This prompt looks for underserved sub-niches before they become crowded.

Act as a niche content expert who specializes in helping creators dominate micro-niches. I create content in the [NICHE] space and my target audience is [AUDIENCE].

Your task:

1. Identify 5 underserved sub-niches within my main niche that have high engagement but low competition
2. For each sub-niche, generate 5 specific content ideas I can create this week
3. For each idea, explain what makes it unique, what format works best, and what CTA to use
4. Flag which ideas have evergreen potential and will stay relevant for 12+ months
5. Flag which ideas are trending and need to be published within 7 days
6. Give me one controversial angle I could take that would spark debate without damaging trust
7. Tell me what proof, example, or story I should include to make each idea credible

Rank these ideas by the combination of novelty, audience pain, ease of production, and likelihood to trigger comments.

Output this as a table with columns for sub-niche, idea, format, urgency, evergreen potential, CTA, and why it can work.

Pro tip: This prompt is much better if you feed it signals first: comments from your audience, common questions in your niche, subreddit threads, YouTube comments, sales call notes, or DMs.

Prompt 7: Create Viral 3-Second Hooks

This overlaps with the scroll-stopping hook prompt, but I would use it as the final packaging pass right before posting.

You are the world's best 3-second hook surgeon for short-form content. Your job is to make the first line, first frame, or first 3 seconds impossible for the right viewer to ignore.

My content topic: [TOPIC]
My niche: [NICHE]
My target audience: [AUDIENCE]
My platform: [PLATFORM]
My draft idea or script: [PASTE DRAFT]

Generate 20 hook variations using these formats:

1. Bold claim
2. Contradiction
3. Curiosity gap
4. Relatable pain
5. Urgency
6. Number/result
7. Question
8. Personal story
9. Mistake confession
10. Myth-busting

For each hook, rate it 1-10 for:
- Scroll-stop power
- Curiosity level
- Relatability
- Click-through potential
- Specificity
- Trustworthiness

Then crown the TOP 5 hooks and explain exactly why each one will perform.

Finally, rewrite the top 5 hooks in 3 tones:
- Clean and professional
- Punchy and direct
- Slightly chaotic but still credible

For every hook, identify the exact emotion it activates and the reason someone would keep watching.

Pro tip: Never ship the first hook. Ask for 20, pick 5, then ask ChatGPT to make those 5 sharper, shorter, and more specific.

Bonus Prompt: Turn the 7 Prompts Into One Weekly Content System

If you want the whole thing to run like a workflow, use this master prompt.

You are my AI content strategy team. Your job is to help me plan one week of high-performing content without sounding generic or copying competitors.

My niche: [NICHE]
My audience: [AUDIENCE]
My offer or goal: [GOAL]
My platforms: [PLATFORMS]
My brand tone: [TONE]
My current constraints: [TIME / BUDGET / SKILL / ASSETS]
My top competitors or references: [COMPETITORS]
My best-performing past content: [PASTE EXAMPLES]

Run this workflow in order:

1. Audience Pain Scan: Identify the audience's urgent problems, identity desires, objections, and hidden frustrations.
2. Viral Idea Sprint: Generate 20 content ideas with emotional triggers and share/save reasons.
3. Competitor Psychology: Identify the patterns competitors use, then show how I can use the psychology without copying the content.
4. Trend Filter: Identify which ideas connect to current trends or timely conversations.
5. Format Match: Assign each idea to the best format: Reel, carousel, post, thread, short, story, email, or Reddit post.
6. Hook Lab: Write 10 hooks for the top 5 ideas.
7. Calendar Build: Create a 7-day posting plan with topic, format, hook, CTA, and production notes.
8. Quality Audit: Flag anything generic, overdone, too salesy, or off-brand.

Before starting, ask me up to 7 questions that would make the plan more specific.

This is the version I would use if I were building a weekly content calendar from scratch.

Why These Prompts Work

These prompts work because they add the missing ingredients most basic prompts leave out. A bad prompt asks ChatGPT to “make content.” A better prompt defines the audience, role, platform, emotional trigger, format, constraints, scoring criteria, and reason the piece should spread.

Missing ingredient	Weak prompt	Strong prompt
Role	“Give me ideas.”	“Act as a viral content strategist.”
Audience	“For my brand.”	“For [AUDIENCE] in [NICHE] who struggle with [PAIN].”
Emotional trigger	“Make it engaging.”	“Label the trigger: curiosity, shock, FOMO, relief, identity, or usefulness.”
Format	“Write a post.”	“Choose Reel, carousel, static, story, thread, or Reddit post.”
Spread mechanism	“Make it viral.”	“Explain why someone would save, share, comment, or DM this.”
Quality control	“Give me the answer.”	“Rate each option and crown the top 5 with reasons.”
Originality	“Use this competitor as inspiration.”	“Extract the psychology, not the wording or creative.”

The meta-lesson is simple: ChatGPT is much better when you make it reason through why the content should work.

Pro Tips That Make These Prompts Better

Pro tip	Why it helps	Add this to your prompt
Give ChatGPT examples of your past winners.	It can infer your voice and audience patterns.	“Here are my 3 best-performing posts. Extract the pattern before suggesting ideas.”
Force it to ask questions first.	It prevents generic output.	“Ask me 5 questions before answering.”
Make it label the emotional trigger.	Viral content usually spreads for a psychological reason.	“For each idea, name the emotional trigger.”
Ask for ratings.	Scoring makes the model compare ideas instead of listing them.	“Rate each option from 1-10 for specificity, novelty, and shareability.”
Separate strategy from copy.	It stops ChatGPT from jumping straight to bland captions.	“First explain the strategy, then write the post.”
Ask for weak spots.	It improves the final output before you publish.	“Tell me which idea is weakest and how to fix it.”
Use your comments and DMs as source material.	Audience language beats generic marketing language.	“Use these comments to identify content angles.”
Ask for contrarian versions.	Safe ideas are usually forgettable.	“Give me one safe, one spiky, and one controversial version.”
Ask for platform-specific rewrites.	A Reddit post should not sound like an Instagram caption.	“Rewrite this for Reddit, LinkedIn, X, TikTok, and YouTube Shorts.”
Ask it to remove AI-sounding language.	The first draft often sounds too polished.	“Make this sound like a smart human wrote it quickly.”

Top Use Cases

These prompts are not only for influencers. They work for anyone who needs attention without sounding like a content farm.

Use case	How to apply the prompt stack
Solopreneurs	Turn audience pain points into weekly content that points back to an offer.
Startup founders	Convert product insights, customer objections, and market takes into thought-leadership posts.
Newsletter writers	Use the trend scout and hook prompts to find timely essay angles.
YouTubers	Use the hook prompts for titles, intros, thumbnails, and first 30 seconds.
B2B marketers	Use competitor psychology to analyze category narratives and content gaps.
Coaches and consultants	Turn recurring client problems into posts, carousels, and short videos.
Course creators	Build lesson teasers, objection-handling posts, and save-worthy frameworks.
Agencies	Create content calendars and competitor audits faster for clients.
Reddit creators	Turn prompts into discussion posts, contrarian takes, and useful guides.
Product-led teams	Convert feature releases into use-case content that explains the problem solved.