Claude Sonnet 4.5 is the closest thing to an economic cheat code we’ve ever touched but only if you ask it the prompts that make it uncomfortable.

Here are 10 Powerful Claude prompts that will help you build a million dollar business (steal them): 1. Business Idea Generator

"Suggest 5 business ideas based on my interests: [Your interests]. Make them modern, digital-first, and feasible for a solo founder."

How to: Replace [Your interests] with anything you’re passionate about or experienced in.

OpenAI, Anthropic, and Google 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 (Bookmark 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.

R.I.P Marketing agencies.

Gemini 3 Pro is so powerful it just replaced half our team with one mega-prompt.

It now handles market research, content creation and campaign planning all of this in few seconds.

Here’s the exact mega-prompt we use to automate everything: The mega prompt:

Steal it:

"# ROLE
You are Gemini 3, acting as a full-stack AI marketing strategist for a start-up about to launch a new product.

# INPUTS
product: {Describe your product or service here}
audience: {Who is it for? (demographics, psychographics, industry, etc.)}
launch_goal: {e.g. “generate leads”, “build awareness”, “launch successfully”}
brand_tone: {e.g. “bold & punchy”, “casual & fun”, “professional & clear”}

# TASKS
1. Customer Insight
• Build an Ideal Customer Profile (ICP).
• List top pain points, desired gains, and buying triggers.
• Suggest 3 positioning angles that will resonate.

2. Conversion Messaging
• Craft a hook-driven landing page (headline, sub-headline, CTA).
• Give 3 viral headline options.
• Produce a Messaging Matrix: Pain → Promise → Proof → CTA.

3. Content Engine
• Create a 7-day content plan for X/Twitter **and** LinkedIn.
• Include daily post titles, themes, and tone tips.
• Add 1 short-form video idea that supports the plan.

4. Email Playbook
• Write 3 cold-email variations:
① Value-first, ② Problem-Agitate-Solve, ③ Social-proof / case-study.

5. SEO Fast-Track
• Propose 1 SEO topic cluster that aligns with the product.
• Give 5 blog-post titles targeting mid → high-intent keywords.
• Outline a “pillar + supporting posts” structure.

# OUTPUT RULES
• Use clear section headers (e.g. **ICP**, **Landing Copy**, **SEO Titles**).
• Format in Markdown for easy reading.
• No chain-of-thought or reasoning—deliver polished results only.
"

Holy shit...Google just dropped CodeMender an autonomous AI agent that finds and fixes security bugs in code by itself.

This isn’t a static analysis tool. It’s a self-reasoning system that patches vulnerabilities and rewrites insecure code before humans even find it.

Let’s break it down ↓ CodeMender is built on Gemini Deep Think models multi-step reasoning LLMs that can analyze, debug, and validate code fixes autonomously.

It’s not just scanning for CVEs. It’s understanding execution flow, data flow, and logic then generating a patch that survives real-world tests.

Holy shit… I just found out why OpenAI, Anthropic, and Google engineers never worry about prompts.

They use context stacks. Context engineering is the real meta.

It’s what separates AI users from AI builders.

Here's how to write prompts to get best results from LLMs: Prompt engineering was a hack for the early days of AI like learning to talk to a foreigner using short phrases and keywords.

But today’s models don’t just understand instructions. They understand environments.

Your job isn’t to “prompt” the model.

It’s to architect its context.

Gemini 3.0 Pro just killed consulting as we know it.

Here are the 3 prompts I use to get McKinsey-grade answers instantly 👇 Let me tell you what McKinsey consultants actually do:

1. Analyze industry trends and competitive dynamics
2. Benchmark companies and products
3. Identify strategic risks and opportunities
4. Package it all in fancy slides and charge 6 figures

But guess what?

AI can now do 90% of that instantly.

Let me show you how:

A brand just developed a comprehensive content plan, built a complete calendar, and published automatically with a single AI tool in one hour.

Pippit AI enables you to generate high-converting videos, images, and social content seamlessly.

Here’s how it works: This is the world’s FIRST Marketing Agent does EVERYTHING powered by Vibe Marketing

Create content plans from one sentence, including topics, scripts, hooks, and hashtags.

Make videos and images quickly, matching each platform's style.

Set up a content calendar with daily posts. automatically publish to TikTok, Instagram, and Facebook without manual uploads.

pippit.ai/thoughtform-on…

🚨 This project just made most AI agents look outdated.

It’s called Better Agents and it supercharges your coding assistant (Kilocode, Claude Code, Cursor, etc), making it an expert in any agent framework you choose (Agno, Mastra, etc) and all their best practices.

This is the future of autonomous AI.

Here’s how it works 👇 Every AI agent demo looks amazing until production hits.

Then reality:
— Agents hallucinate in edge cases
— No version control for prompts
— Zero test coverage
— Debugging = prayer

Better Agents isn't another framework. It's the testing layer everyone forgot to build.

Link: github.com/langwatch/bett…

This open-source project just solved the biggest problem with AI agents that nobody talks about. It's called Acontext and it makes your agents actually LEARN from their mistakes.

While everyone's building dumb agents that repeat the same errors 1000x, this changes everything.

Here's how it works (in plain English):↓ Acontext built a complete learning system for agents:

— Store: Persistent context & artifacts
— Observe: Track tasks and user feedback
— Learn: Extract SOPs into long-term memory

When your agent completes a complex task, Acontext:
→ Extracts the exact steps taken
→ Identifies tool-calling patterns
→ Creates reusable "skill blocks"
→ Stores them in a Notion-like Space

GitHub: github.com/memodb-io/Acon…

Holy shit... Someone just solved the biggest AI privacy problem nobody talks about.

It's called Hyperlink which is a fully offline AI that searches ALL your documents without sending a single byte to the cloud.

No OpenAI. No Google. No data leaks.

Here's how:↓ Hyperlink flipped the entire model.

Instead of uploading files to AI, they brought AI to your files.

- 100% on-device processing
- Zero cloud dependencies
- Your data never leaves your machine

It's like having GPT-4 intelligence that runs entirely offline.

🚨 ElevenLabs just killed every transcription tool on the market.

They dropped Scribe v2 Realtime and it's not just another speech-to-text model.

This thing processes audio in real-time with zero lag, handles multiple speakers, and actually understands context not just words.

Here's how with real examples:

Full thread 🧵 1. Unlike Whisper or Google's STT that buffer and process, Scribe Realtime transcribes AS you speak.

We're talking sub-50ms latency.

That's faster than human reaction time.

VPN set to 🇲🇽 = cheaper flights
VPN set to 🇹🇭 = cheaper hotels
VPN set to 🇵🇱 = cheaper subscriptions
VPN set to 🇮🇳 = cheaper everything

This is the Cheat Code most companies don't want you to know.

Here's how to save thousands with ExplorerVPN: When airlines or booking sites see your location, they adjust prices.

They call it “dynamic pricing.”
I call it geo-based discrimination.

Same flight. Same seat.
Different country = different price.

If I had to launch an AI product today with $0, I'd do this: Step 1:

Go to abacus(dot)ai and create a free account.

You’ll get agent builder, no/low-code workflows, hosting, and quick deploys.

The free trial/first month covers your MVP window.

What you get inside Abacus:

• Prebuilt agents and models
• No-code deployment + hosting (custom domain)
• Monitoring and prediction dashboards
• Access to top LLMs in one place

I’ve spent months reverse-engineering prompts from OpenAI, Anthropic & Google engineers.

These are the 7 proven prompt templates that make LLMs think like experts👇 1. Job Applications & Career → Persona + Personalization

- Generic cover letters scream “AI-written.”
- The fix? Add persona + structure + tone control.

Use this once and you’ll never go back to “Write a cover letter for…” again.

Prompt:

🚨BREAKING: There's now AI agents that hack your app to find real security bugs

It acts like an AI Cybersecurity Agent, providing real-time, automated security testing for developers and teams

100% open-source. Link to the guide in 🧵↓ Introducing Strix: This is 100% open-source platform that deploys autonomous AI agents that act like real hackers.

These AI agents don't just scan, they find and validate vulnerabilities through actual exploitation.

12 GitHub repos that will help you start a career in AI engineering (100% free): 1. AI for Beginners by Microsoft

This repo includes topics like neural networks, language processing, computer vision, and more.

It's easy for beginners, focuses on projects, and includes real-world examples.

Check this👇

Stanford just published research that destroys every prompt engineering guru.

Turns out most "advanced techniques" are just survivorship bias and confirmation bias.

Here's what the data actually shows: The biggest lie: "Be specific and detailed"

Stanford researchers tested 100,000 prompts across 12 different tasks.

Longer prompts performed WORSE 73% of the time.

The sweet spot? 15-25 tokens for simple tasks, 40-60 for complex reasoning.

How to Build SaaS Apps with AI (No Manual Coding Needed): With DeepAgent, you can make your own AI app easily!

DeepAgent isn’t just an AI builder it’s your backend, frontend, and dev team in one.

You can make an app in just a few minutes.

It creates the login, database, buttons, and lets apps talk to each other automatically.

This guy is genius.

Someone gave Claude 4 Sonnet one mega prompt and now it runs his entire marketing engine:

→ Research
→ SEO
→ Ad copy
→ Content
→ Strategy

Here’s the exact prompt (steal it): The mega prompt:

Steal it:

"
Act as a full-stack AI marketing strategist for a startup preparing to launch a new product or service. You will handle market research, positioning, messaging, content creation, email copywriting, and SEO ideation.



{Describe your product or service here}
{Who is the product for? (demographics, psychographics, industry, etc.)}
{e.g. “generate leads,” “build awareness,” “launch product,” etc.}
{e.g. “casual and fun,” “bold and punchy,” “professional and clear”}



Given the product, target audience, and goal:

1. **Customer Insight & Research**
- Generate an Ideal Customer Profile (ICP)
- Identify key pain points, goals, and decision drivers
- Suggest 3 positioning angles to resonate with this audience

2. **Messaging & Conversion Copy**
- Write a hook-driven landing page (headline, subheadline, CTA section)
- Provide 3 viral headline variations
- Create a messaging matrix: [Pain Point → Promise → Proof → CTA]

3. **Content Creation**
- Generate a 7-day content plan (Twitter + LinkedIn)
- Include daily post titles, themes, and tone suggestions
- Add 1 short-form video concept if relevant

4. **Email Marketing**
- Write 3 cold email variations:
- Value-first pitch
- Problem-agitate-solution
- Case-study / social proof style

5. **SEO Strategy**
- Suggest 1 SEO topic cluster aligned with the product
- Provide 5 blog post titles that target mid-to-high intent keywords
- Recommend a pillar + supporting post structure

6. **Output Format**
- Use clear section headers (e.g. “ICP”, “Landing Page Copy”, “SEO Titles”)
- Use markdown formatting for readability
- Do **not** explain your reasoning — just give the final, polished outputs

This should be delivered as a comprehensive marketing kit, ready to deploy.

"

I finally understand how large language models actually work

After reading the 2025 textbook “Foundations of LLMs”

It blew my mind and cleared up years of confusion

Here’s everything i learned (in plain english): To understand LLMs, start with pre-training.

We don’t teach them specific tasks.

We flood them with raw text and let them discover patterns on their own.

This technique is called self-supervised learning and it’s the foundation of everything.

After 2 years of using ChatGPT, I can say that it is the technology that has revolutionized my life the most, along with the Internet.

So here are 10 prompts that have transformed my day-to-day life and that could do the same for you: 1. Learn anything from a 20-year expert even if you're clueless

"Pretend you are an expert with 20 years of experience in {industry/topic}. Break down the core principles a total beginner must understand. Use analogies, step-by-step logic, and simplify everything like I’m 5."