Prompt engineering is dead.

Context engineering is what actually matters now.

After analyzing how engineers at Anthropic, OpenAI, and Google get 10x better results...

Here are the 8 insider techniques they don't want you to know: 1/ PERSONA + EXPERTISE CONTEXT (For any task)

LLMs don't just need instructions. They need to "become" someone. When you give expertise context, the model activates completely different reasoning patterns.

A "senior developer" prompt produces code that's fundamentally different from a generic one.

Prompt:

"You are a [specific role] with [X years] experience at [top company/institution]. Your expertise includes [3-4 specific skills]. You're known for [quality that matters for this task].

Your communication style is [direct/analytical/creative].

Task: [your actual request]"

We are witnessing the greatest wealth transfer in history. Grok 4.1 is the bridge.

I’ve spent the last 30 days engineering 10 prompts that force Grok to stop being "polite" and start being a $1M growth partner.

If you aren't using these, you're choosing the hard way: 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.

Omg...

I built a meta-prompt that writes better prompts than I can.

Describe what you want in plain English → it generates the optimal structured prompt.

Here's the exact mega prompt you can steal: STEAL THE PROMPT:

"
You are an expert prompt engineer. Your task is to analyze the user's request and generate an optimized, structured prompt that will produce the best possible results from any LLM.

Follow this process:

1. ANALYZE THE REQUEST
- Identify the core task or goal
- Determine the required output format
- Note any constraints or special requirements
- Assess the complexity level

2. IDENTIFY OPTIMAL PROMPT PATTERNS
- What role/persona would be most effective?
- What context or background is needed?
- What specific instructions will guide the model best?
- What examples or constraints should be included?

3. CONSTRUCT THE OPTIMIZED PROMPT
Build a comprehensive prompt with these elements:
- Clear role definition
- Detailed context and background
- Step-by-step instructions
- Output format specifications
- Quality criteria
- Examples (if applicable)
- Constraints and guardrails

4. OUTPUT FORMAT
Present the optimized prompt in a clean, copy-pasteable format with clear sections.

USER REQUEST:
[User describes what they want in plain English]

Generate the optimal structured prompt now.
"

I've been testing a prompting method that nobody talks about.

It sounds insane but it makes AI 3x more accurate on complex tasks.

I call it "Emotion Injection" and it breaks everything we thought we knew about neutral prompting.

Here's why it works (and the exact framework): Everyone says "be clear and direct" with AI prompts.

But that's only half the story.

LLMs trained on human text learned something deeper than facts. They learned the emotional context that surrounds different types of thinking. Academic papers sound different than crisis responses.

You can trigger these different "thinking modes" by embedding emotional cues into prompts. Not fake enthusiasm. Strategic emotional framing that tells the model what cognitive state to operate in.

Holy shit... Google DeepMind just exposed why everyone's been doing AI reasoning wrong.

The AlphaGo team doesn't use chain-of-thought. They use parallel verification loops.

And it's destroying every "advanced reasoning" technique you've heard about.

Here's what they discovered ↓ Why Chain-of-Thought sucks.

Current AI reasoning is linear. Think step 1 → step 2 → step 3.

But that's not how expert problem-solvers think.

DeepMind analyzed how their AlphaGo team tackles complex problems and found something wild.

CHATGPT JUST REPLACED THE MOST HATED PART OF BUILDING

Planning, task breakdowns, timelines, status updates, follow ups.
The stuff that drains momentum and kills projects.

If you treat ChatGPT like a real PM, it can run the entire workflow for you.

Here’s how 👇 1/ ASSIGN IT THE ROLE (THIS MATTERS)

PMs don’t just answer questions.

They own outcomes.

Prompt to steal:

“Act as a senior project manager.
Your goal is to deliver [project] on time and within scope.
Ask me any clarifying questions before proceeding.”

Instant ownership.

OpenAI engineers use a prompt technique internally that most people have never heard of.

It's called reverse prompting.

And it's the fastest way to go from mediocre AI output to elite-level results.

Here's the exact system you can steal right now: Most people write prompts like this:

"Write me a strong intro about AI."

The AI guesses.
The result feels generic.

This is why 90% of AI content sounds the same.

You're asking the AI to read your mind.

Chain of Thought is dead.

I just tested Atom of Thought prompting and it's making AI models 30-40% more accurate on complex reasoning tasks.

Here's the technique that's about to change how everyone uses ChatGPT and Claude: The problem with Chain of Thought: it forces linear thinking.

Real problem-solving doesn't work that way. Your brain doesn't solve physics problems by thinking step 1 → step 2 → step 3.

You break complex problems into atomic components, then recombine them.

YOU CAN NOW LEARN ANYTHING FOR FREE USING AI

And it blows my mind that people are still buying $497 courses.

ChatGPT basically turned the entire education industry into an open book exam. If you know how to prompt it right, you can build your own personal curriculum that’s better than Udemy, Coursera, Skillshare, all of it.

Here’s how to turn ChatGPT into a world class learning machine 👇 1/ BUILD YOUR “AI DEGREE” IN 30 SECONDS

Pros don’t ask “teach me X”.

They ask for the full roadmap.

Prompt to steal:

“Create a complete learning curriculum for [skill].
Break it into beginner, intermediate, and advanced modules.
Add exercises, real world projects, weekly goals, and skill checkpoints.”

PERPLEXITY AI IS THE MOST UNDERVALUED SUPERPOWER IN CONTENT RIGHT NOW

and nobody is using it properly lol.

Here are 3 prompts + techniques + example prompts that will 10x your content in the next 24 hours 👇 1/ THE DEEP DIVE PROMPT

Most people ask Perplexity tiny questions.

Winners ask it to synthesize entire ecosystems.

Technique:

Tell Perplexity to scan experts, forums, newsletters, academic sources, then merge insights into a single map.

Prompt to steal:

“Scan the top experts, forums, and niche communities discussing [topic].
Identify the 5 most important themes, the debates, the blind spots, and the emerging trends.
Summarize them visually and give me a content angle no one is talking about yet.”

This mega prompt will help you automate all your marketing tasks in Gemini 3 Pro for free:

(Steal it ↓) 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.
"

Perplexity AI is a GENIUS marketer.

But most people don't know how to use it.

Here are 5 mega prompts you can copy/paste to get pro level outputs in seconds: 1. The “Viral Pattern Decoder”

When I was deep-diving through obscure Discord threads, I stumbled on a prompt that instantly became my secret weapon for content research. It forces Perplexity to think like a strategist instead of a note-taker.

Prompt:

“Act as a senior strategist who reverse-engineers content that already wins online. Pull the last 50 viral posts from accounts in my niche, break down the patterns, identify what triggers engagement, and give me a repeatable posting formula based on what’s actually working right now.”

STOP USING MIDJOURNEY, RUNWAY, AND CHATGPT.

Use Gemini to automate all your tasks for free.

Here are 10 tasks Gemini can do to help you save time and money:

(Comment "AI" and I'll also DM you a complete guide on with amazing prompts to use) 1. Image Generation (Nano Banana Pro)

Most people still think Gemini is “just a chatbot”.
Meanwhile the new image model makes Midjourney feel slow.

You describe a scene.

It gives you production-grade artwork.

Here’s the image prompt I use daily:

“Create a high-end studio photo of a product on a wet reflective surface with neon light accents. Sharp edges, cinematic contrast.”

Paste it into Gemini and watch it flex.

I can’t unsee this.

Someone Asked Nano Banana Pro to show how everyday things are made. The visuals hit harder than any documentary.

Here are 10 visuals that explain it perfectly:

1. Pyramids 2. Ramen

Perplexity might be the most underrated SaaS-building cofounder alive.

I used it for architecture, UX, copy, research, validation, EVERYTHING.

Here are 10 prompts that built half my product for me (steal them): 1. SaaS Opportunity Mapper

"Analyze unmet needs in the niche: [ENTER NICHE]. Identify 5 urgent, high-value problems and propose SaaS solutions with target users, workflows, and revenue models."

🚨 BREAKING: A new AI model just changed how machines see the world.

This isn’t another “multimodal” system it’s an agentic one.

Instead of passively captioning or classifying, DeepEyes V2 reasons across text, image, and video like a cognitive agent.

It breaks down what it sees, plans what to look for next, and decides which modality matters most all without human hints. Its architecture the Agentic Multimodal Model (AMM) fuses visual grounding with chain-of-thought reasoning.

It doesn’t just see; it understands why it’s seeing it.

Benchmarks show a new pattern: not higher accuracy, but smarter perception. Tasks that used to need fine-tuned vision + language pairs now collapse into one unified reasoning loop.

This is the start of autonomous perception systems that can interpret, plan, and act not just describe pixels.

We’ve officially entered the age of agentic vision. Everyone’s seen “multimodal” models before but DeepEyes V2 is different.

It doesn’t just see and describe; it thinks about what it’s seeing. It plans, reasons, and adapts across modalities like a cognitive system.

This paper basically marks the start of agentic perception.

I found a way to hack LLMs to do whatever you want.

Here are 8 frameworks you can try right now to get the best results from any LLM like ChatGPT, DeepSeek, Claude, and Grok:

(Comment "AI" and I'll DM you 300+ prompts to automate all your work using LLMs) S-Tier (Actually Works):

1. RTF (Role, Task, Format)

- Quality: 8.7/10

- Dead simple. Tell the model WHO it is, WHAT to do, HOW to structure output.

Example: "You are a solutions architect. Design a chat system. Use markdown with sections."

2. COSTAR (Context, Objective, Style, Tone, Audience, Response)

- Quality: 8.4/10
- Comprehensive but not bloated.
- Forces you to think through what you actually need.

The 6 components map directly to how LLMs parse instructions.

Stop wasting money on McKinsey.

You can now use Perplexity AI to automate market research, competitive analysis, and strategy design for free.

Here’s the mega prompt you can steal ↓

(Comment "AI" and I'll DM you the mega prompts you can use for research) Here's the mega prompt we use (steal it):

---


You are a world-class strategic analyst with access to private market databases, proprietary reports, and expert panels. Your job is to help a founder, consultant, or operator deeply understand a market and win in it.



Insert the industry you're exploring (e.g. AI note-taking tools, DTC skincare, B2B SaaS CRMs)
Describe your ideal customer (e.g. solo founders, marketing teams, Gen Z consumers)
Describe your goal (e.g. identify market gaps, plan a GTM strategy, assess competitors, etc.)


INPUT (space):
Your input here
Your input here
Your input here


Conduct a full-spectrum strategic analysis of the specified industry. Your response must include:

1. Market Overview
- What is this market?
- Why is it relevant now?
- Key trends shaping it over the last 12–24 months.

2. Competitive Landscape
- List the top 5 players with short 2–3 sentence descriptions.
- Describe how they differ in positioning, pricing, and target audience.
- Identify any visible blind spots or underserved customer segments.

3. Customer Insight Mapping
- Outline the major jobs-to-be-done, pains, and desires of the target_customer.
- Provide example use cases or buyer personas if appropriate.

4. Strategic Opportunities
- List up to 3 potential white space or differentiation opportunities.
- Suggest potential product ideas, pricing strategies, or acquisition channels to exploit these gaps.

5. Go-to-Market Guidance
- Recommend a GTM approach for a new entrant: ideal messaging, top channels, positioning advice.
- Suggest early traction strategies (e.g. cold outreach, SEO, partnerships, etc.)

Write in confident, concise prose as if you were advising a founder at a $10K/hr consulting rate. Prioritize insight density.


---

This feels like the early Internet moment for AI.

For the first time, you don’t need a cloud account or a billion-dollar lab to run state-of-the-art models.

Your own laptop can host Llama 3, Mistral, and Gemma 2 full reasoning, tool use, memory completely offline.

Here are 5 open tools that make it real: 1. Ollama ( the minimalist workhorse )

Download → pick a model → done.

✅ “Airplane Mode” = total offline mode
✅ Uses llama.cpp under the hood
✅ Gives you a local API that mimics OpenAI

It’s so private I literally turned off WiFi mid-chat still worked.

Perfect for people who just want the power of Llama 3 or Mistral without setup pain.

I turned Perplexity AI into my full-time research assistant.

It now does 70% of my research, writing, and business analysis automatically.

Here’s the exact workflow + the prompts you can copy today:

(Comment "Send" and I'll DM you my full automation guide) 1. Literature Review Automation

Prompt:

“Act as a research collaborator specializing in [field].
Search the latest papers (past 12 months) on [topic], summarize key contributions, highlight methods, and identify where results conflict.
Format output as: Paper | Year | Key Idea | Limitation | Open Question.”

Outputs structured meta-analysis with citations perfect for your review sections.

R.I.P voice-to-text.

Google’s new model doesn’t even translate your words.

It skips text entirely and jumps straight to meaning.

It’s called Speech-to-Retrieval (S2R).

And it’s about to redefine how AI hears us ↓ Old voice search worked like this:

Speech → Text → Search.

If ASR misheard a single word, you got junk results.

Say “The Scream painting” → ASR hears “screen painting” → you get art tutorials instead of Munch.

S2R deletes that middle step completely.