If you read books and forget everything, this is for you.

NotebookLM can turn any book into action plans, memory notes, and usable insights.

Here are 12 prompts: 1. The Core Argument Extractor

Paste:

“What is the single central argument of this book? State it in 2 clear sentences. Then list the 5 strongest supporting ideas.”

If you can’t explain the book simply, you never really learned it.

Laid-off engineer went from 0 interviews to 12 offers in 6 weeks.

He didn't apply to more jobs. He built an AI workflow that turned every application into 8 minutes of work.

Here's the exact system he used (steal it): Most people job hunting do this:

→ Spend 2 hours per application
→ Send 5 per day, burn out by Friday
→ Get ghosted by 90% of them

He flipped the entire process. Built 3 AI agents that do the heavy lifting so he only shows up for the parts that actually matter.

Claude can now help you write like the best writers alive using the exact rules George Orwell outlined in Politics and the English Language.

Here are 10 prompts that apply his rules to anything you write and eliminate every habit that makes your writing invisible (Save this) Orwell wrote Politics and the English Language in 1946.

It is still the most useful thing ever written about writing.

Not because it teaches you to write beautifully. Because it teaches you to stop writing badly which is a completely different problem and a much more common one.

His argument was simple and brutal: most bad writing isn't a failure of intelligence. It's a failure of honesty. Vague language exists to protect the writer from saying something that can be challenged. Jargon exists to perform expertise instead of demonstrate it. Passive voice exists to remove the person responsible for the action.

When you strip all of that out, what remains either means something or it doesn't. There is nowhere left to hide.

These 10 prompts apply his 6 rules to your writing not as suggestions, but as a systematic audit that leaves you with no cover.

One rule at a time. One piece at a time.

An Indian developer just hit #1 on GitHub with a prompting framework that outperforms every major benchmark.

No VC money. No research lab. Just a laptop and 9 months of testing.

Here are the 11 prompt patterns from his repo that I've been using for 2 weeks: Pattern 1: The Anchor Pattern.

Start every complex prompt with a single sentence that defines the exact output format.

"Respond only with a numbered list. No preamble. No explanation after the list."

The AI locks onto this anchor before processing anything else you write.

I've written 500 articles, 23 whitepapers, and 3 ebooks using Claude over 2 years.

These 10 prompts are the ONLY ones I actually use anymore because they handle 90% of professional writing better than any human editor I've worked with and cost me $0.02 per 1000 words: 👇 1. The 5-Minute First Draft

Prompt:

"Turn these rough notes into an article:

[paste your brain dump]

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

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

🚨 BREAKING: AI can now build trading algorithms like Goldman Sachs' algorithmic trading desk (for free).

Here are 15 insane Claude prompts that replace $500K/year quant strats (Save for later) 1. The Goldman Sachs Quant Strategy Architect

"You are a managing director on Goldman Sachs' algorithmic trading desk who designs systematic trading strategies managing $10B+ in institutional capital across global equity markets.

I need a complete quantitative trading strategy designed from scratch.

Architect:

- Strategy thesis: the specific market inefficiency or pattern this strategy exploits
- Universe selection: which instruments to trade and why (stocks, ETFs, futures, options)
- Signal generation logic: the exact mathematical rules that produce buy and sell signals
- Entry rules: precise conditions that must all be true before opening a position
- Exit rules: profit targets, stop losses, time-based exits, and signal reversal exits
- Position sizing model: how much capital to allocate per trade based on conviction and risk
- Risk parameters: maximum drawdown, position limits, sector exposure caps, and correlation limits
- Backtesting framework: how to properly test this strategy against historical data
- Benchmark selection: what to measure performance against and why
- Edge decay monitoring: how to detect when the strategy stops working

Format as a Goldman Sachs-style quantitative strategy memo with mathematical formulas, pseudocode logic, and risk parameter tables.

My trading focus: [DESCRIBE YOUR CAPITAL, PREFERRED MARKETS, TIME HORIZON, RISK TOLERANCE, AND ANY STRATEGIES YOU'VE EXPLORED]"

🚨SHOCKING: Anthropic's internal prompting style is completely different from what most people teach.

I spent 3 weeks going through their official prompt library, documentation, and API examples.

Most "prompt engineers" online have no idea this stuff exists.

Here are the 8 techniques that actually separate beginners from experts: 🧵 Technique 1: Role + Goal + Format in the opening line.

Most people write: "Help me write a marketing email."

Anthropic's style: "You are a direct-response copywriter. Your goal is to write a cold email that gets a reply within 48 hours. Format: subject line, 3 short paragraphs, one CTA."

Same request. Completely different output.

🚨BREAKING: Claude Code just got an Obsidian plugin and it's insane.

It's called KatmerCode.

7 academic research skills. Inline diff editing. MCP support. Full Claude Code session running in your sidebar.

100% Opensource.

Here's everything it can do: Most Obsidian users copy-paste between their notes and an AI chat window.

That's broken. You lose context. You lose your edit history. You lose the thread.

KatmerCode runs a real Claude Code subprocess inside Obsidian via the Agent SDK.

Your vault is the working directory. Claude edits your files directly.

🚨BREAKING: A senior Google engineer just leaked the internal prompting system their team uses to ship features 3x faster.

No PM approval. No design sprint. Just a 12-step AI workflow they've been quietly running since Q3.

Here are the 11 prompt patterns from his anonymous Notion doc that I've been using for 3 weeks: 1/ The Feature Scoping Prompt

Before writing a single line of code, they dump the raw feature idea into Claude with this:

"Act as a senior engineer. Break this feature into atomic tasks. Flag every assumption. List every dependency. Identify the 3 most likely points of failure."

Saves 2 hours of alignment meetings instantly.

🚨BREAKING: A self-taught developer from Brazil just cracked the context window problem that's been plaguing RAG systems for 2 years.

No PhD. No research lab affiliation. Just 400 GitHub commits and a personal obsession.

Here are the 8 techniques from his open-source library that every RAG tutorial gets completely wrong: First, understand why RAG actually breaks.

Most tutorials show you the happy path: chunk your docs, embed them, retrieve the top-k, stuff into prompt.

It works in demos. It falls apart in production.

The real problem isn't retrieval. It's context contamination you're pulling the right documents but injecting them in ways that confuse the model more than they help.

He spent 14 months figuring out exactly where this breaks.

🚨BREAKING: An Indian developer just hit #1 on GitHub with a prompting framework that outperforms every major benchmark.

No VC money. No research lab. Just a laptop and 14 months of testing.

Here are the 11 prompt patterns from his repo that I've been using for 3 weeks: Pattern 1: The Anchor Pattern.

Start every complex prompt with a single sentence that defines the exact output format.

"Respond only with a numbered list. No preamble. No explanation after the list."

The AI locks onto this anchor before processing anything else you write.

BREAKING: Gemini can now write and design an entire book in 24 hours.

Here are 5 insane prompts to become a published author this month: (Save for later): Prompt 1: The Book Blueprint

"You are a bestselling non-fiction book strategist. I want to write a book about [your topic] for [target audience]. Give me: a compelling title + subtitle, a full chapter-by-chapter outline (10–12 chapters), the core transformation the reader gets, and the positioning angle that makes this different from every other book on Amazon."

Most authors spend 6 months on this alone.

This takes 90 seconds.

R.I.P Duolingo.

I just deleted every language app…

After years with language apps, I switched to GPT-5 as my tutor and It's way better.

Here're 10 ChatGPT prompts taught me more in 3 weeks than any app: 1. Daily Chat Buddy

"You're a friendly native speaker. Let's chat for 10 minutes in [language] about [topic]. Correct my mistakes while we talk."

This is better than any app's chat feature. Instant corrections and a smooth flow help you learn for real.

BREAKING: I stopped watching 2-hour YouTube tutorials.

Grok now turns any video into a step-by-step skill plan.

Here are 8 prompts that convert videos into mastery: 1. Comprehensive Overview

Prompt:
“I’ve shared a YouTube video. Give me a high-level overview of everything being taught, broken into the main skills, concepts, and phases, as if you’re introducing it to someone seeing it for the first time.”

🚨BREAKING: You don’t need to hire an editor to go viral anymore.

Meet Klap the AI tool that turns your long videos into high-performing TikToks, Shorts, and Reels in 1 click.

Here’s how creators are saving hours (and blowing up on social):👇

(Save this before it goes viral): 1. Paste a link, get clips in minutes

Drop in your YouTube link or upload a file.

Klap uses AI to extract the most engaging moments and turns them into dozens of short clips automatically.

Try Klap here: klap.app

I've written 500 articles, 23 whitepapers, and 3 ebooks using Claude over 2 years.

These 10 prompts are the ONLY ones I actually use anymore because they handle 90% of professional writing better than any human editor I've worked with and cost me $0.02 per 1000 words: 👇 1. The 5-Minute First Draft

Prompt:

"Turn these rough notes into an article:

[paste your brain dump]

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

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

🚨 OpenAI, Anthropic, and Google AI engineers use 10 internal prompting techniques that guarantee near-perfect accuracy…and nobody outside the labs is supposed to know them.

Here are 10 of them (Save this for later): Technique 1: Role-Based Constraint Prompting

The expert don't just ask AI to "write code." They assign expert roles with specific constraints.

Template:

You are a [specific role] with [X years] experience in [domain].
Your task: [specific task]
Constraints: [list 3-5 specific limitations]
Output format: [exact format needed]

---

Example:

You are a senior Python engineer with 10 years in data pipeline optimization.
Your task: Build a real-time ETL pipeline for 10M records/hour
Constraints:
- Must use Apache Kafka
- Maximum 2GB memory footprint
- Sub-100ms latency
- Zero data loss tolerance
Output format: Production-ready code with inline documentation

---

This gets you 10x more specific outputs than "write me an ETL pipeline."

Watch the OpenAI demo of GPT-5 and see how they were prompting ChatGPT... you will get the idea.

I DON’T UNDERSTAND WHY PEOPLE DON’T USE CLAUDE FOR STOCKS.

Most traders are looking at charts from 6 months ago.
CLAUDE analyzes real-time sentiment on X to predict future.

Here are 20 prompts to find the next 10X stock: 1. Time Series Forecasting Model

You are a Quantitative Researcher at Goldman Sachs Global Markets. I need a complete time series forecasting model for [STOCK/ASSET].

Please provide:

- Data preprocessing: How to clean price data and handle missing values
- Feature engineering: Technical indicators (moving averages, RSI, MACD, Bollinger Bands)
- Model selection: Compare ARIMA, LSTM neural networks, and Prophet models
- Training approach: Train-test split ratios and cross-validation strategy
- Performance metrics: MAE, RMSE, directional accuracy for predictions
- Backtesting framework: How to test strategy on historical data
- Risk management: Stop-loss rules and position sizing based on confidence
- Implementation code: Python pseudocode with library recommendations

Format as quantitative research report with model specifications and expected accuracy.

Asset: [DESCRIBE STOCK/CRYPTO/COMMODITY, TIME PERIOD, DATA SOURCE]

🚨 BREAKING: Someone just leaked their full Claude Cowork setup and it compresses an entire workday into 90 seconds.

I scraped every power user workflow across X, Reddit, and private Slack groups to find out how.

99% of people are using it completely wrong.

Here's what the top 1% actually do 👇 Prompt 1: Inbox triage + summarization

"You are a Chief of Staff with 10 years of executive support experience.

I need you to process my inbox one email at a time using this exact chain of reasoning:

Step 1 → Classify: Is this urgent (needs reply today), important (needs reply this week), or noise (unsubscribe/archive)?
Step 2 → Extract: Pull out the sender, request, deadline, and any names mentioned.
Step 3 → Draft: Write a reply under 4 sentences. Match the sender's tone. Never use "I hope this email finds you well."
Step 4 → Flag: If it involves money, legal language, or a deadline under 24 hours, mark it [ESCALATE] before the reply.

Process every email in my inbox folder. Output in this format:
[CLASSIFICATION] | [EXTRACTED INFO] | [DRAFT REPLY] | [FLAG IF NEEDED]

Do not stop until every email is processed."

BREAKING: McKinsey charges $500K for market research Claude does in 4 minutes.

I reverse-engineered how their analysts actually prompt it.

Here are the 12 prompts they use that nobody talks about: 👇 1. Market Sizing (TAM/SAM/SOM) from Scratch

Most founders pay consultants $3K just for a market sizing slide.

Claude does it in 30 seconds with actual logic:

Prompt:

You are a senior market research analyst at McKinsey.

Calculate the TAM, SAM, and SOM for [YOUR PRODUCT/SERVICE] in [TARGET MARKET].

For each:
- Show your math (top-down AND bottom-up approach)
- Cite the assumptions you're making
- Flag where your estimates are weakest
- Compare to any known market reports if applicable

Format as an investor-ready slide with numbers, not paragraphs. If my market is smaller than I think, tell me now.

BREAKING: Grok can now do digital marketing like a $10,000/month agency (for free).

Here are 7 insane Grok prompts that can take your biz to $100K/month (Save for later) 1. The WPP Full-Funnel Marketing Strategy

"You are a chief strategy officer at WPP who builds full-funnel marketing systems for brands spending $10M+ annually on customer acquisition.

I need a complete marketing funnel strategy that turns strangers into paying customers.

Build:

- Top of funnel: 5 awareness channels ranked by cost-per-impression for my niche
- Middle of funnel: Lead nurture email sequence (7 emails with subject lines and purpose)
- Bottom of funnel: Conversion tactics with urgency triggers and objection handlers
- Customer journey map from first touch to first purchase with timeline
- Content plan for each funnel stage (what to post, where, and how often)
- Lead magnet recommendation that my ideal customer can't resist
- Retargeting strategy for people who visited but didn't buy
- KPIs to track at each stage with benchmark numbers to aim for
- Monthly budget allocation across channels for maximum ROI
- 90-day launch plan prioritized by highest impact, lowest effort actions

Format as a WPP-style full-funnel marketing playbook with funnel diagrams and channel allocation tables.

My business: [DESCRIBE YOUR PRODUCT, PRICE POINT, TARGET CUSTOMER, CURRENT MONTHLY REVENUE, AND MARKETING BUDGET]"