Everyone talks about AI “memory,” but nobody defines it.

This paper finally does.

It categorizes LLM memory the same way we do for humans:

• Sensory
• Working
• Long-term

Then shows how each part works in GPTs, agents, and tools.

Here's everything you need to know: First, what the survey does:

• Maps human memory concepts → AI memory
• Proposes a unifying 3D–8Q taxonomy
• Catalogues methods in each category
• Surfaces open problems + future directions

Think of it as a blueprint for how agents can remember.

Forget LLMs.

Nvidia just dropped a report: Small Language Models (SLMs) are the real future of AI agents.

They’re faster.
They’re cheaper.
They use way less energy.

Here’s the 2-minute breakdown you need: What are SLMs?

Small Language Models = compact models trained for specific, repeatable tasks.

They’re not trying to be universal chatbots.

They’re designed to do the same actions with high accuracy.

Think: specialist > generalist.

Less weight, more focus.

If you want to build AI agents using n8n, do this:

Copy/paste this prompt into ChatGPT and watch it build your agent from scratch.

Here’s the exact prompt I use 👇 The system:

1. I open ChatGPT
2. Paste in 1 mega prompt
3. Describe what I want the agent to do
4. GPT returns:

• Architecture
• n8n nodes
• Triggers
• LLM integration
• Error handling
• Code snippets

5. I follow the steps in n8n.

Done.

Writing your own prompts is so 2024

Today, power users leverage GPTs to write mega prompts in seconds.

Here are 5 'instructions' you can use to build Sam Altman level prompt writing GPTs immediately. As in literally right now.

Bookmark these 👇 1. Platform Specific

A prompt is not a prompt the same way a rose is a rose.

Vibe coding prompts need to define the coding language, dependencies, environment, etc.

Image gen prompts need to reference aperture, lens type, camera angle and so on.

The solution?

This is wild.

Grok 4 can replace:

• Your VA
• Your content writer
• Your product analyst

Here are the 8 ways to use Grok to automate 80% of your work👇 1. Market Research

"Conduct market research on {industry/product}. Identify trends, competitors, consumer behavior, and growth opportunities. Provide insights backed by data, key statistics, and strategic recommendations to leverage market gaps effectively."

Use Case: Launching a new product or validating an idea.

Transforms scattered data into actionable strategy using trends, stats, and competitive intelligence.

If your AI agents can’t:

• Build apps
• File reports
• Navigate the web
• Do work on their own
…then you’re using the wrong stack.

Here are 10 agents that actually work: Coding Agents:

You don’t need to write boilerplate anymore.

1. Google Jules – Free
→ Reads your whole repo
→ Builds features independently
→ Adds tests + changelogs

2. Cline – Self-hosted
→ Runs inside VS Code
→ Claude-powered planning
→ Launches browsers + debugs UI flows

GPT-5 is insane.

I built:

1. A working SaaS MVP
2. A 12-page research paper
3. A playable game

And more in a single day.

Here’s how it did it all: 1. Playable Game

This can help you build mini-games for demos, virality, or learning.

Prompt I tried:

"Build a playable browser-based game using HTML and JavaScript. Concept: a typing speed challenge where users must type random words correctly within a 60-second timer. Include a start button, score counter, and reset functionality."

chatgpt.com/canvas/shared/…

The most important AI concept of 2025 isn't AGI. It's RAG.

It's the tech that makes AI useful for real businesses.

• Answers questions on your docs
• Summarizes recent emails
• Acts as a true expert

Here's how it works, explained in 120 seconds: 1. what is RAG?

RAG = Retrieval-Augmented Generation.

it connects a language model (like gpt-4) to your external knowledge.

instead of guessing, it retrieves relevant info before generating answers.

think: search engine + smart response = fewer hallucinations.

it’s how ai stops making stuff up and starts knowing real things.

Anthropic researchers just leaked the XML prompting secrets

Claude becomes a different AI entirely when you use proper XML structure

It's like switching from a calculator to a supercomputer

Here's the framework they don't want you to know: Why XML?

Claude was trained on structured, XML-heavy data like documentation, code, and datasets.

So when you use XML tags in your prompts, you’re literally speaking its native language.

The result? Sharper, cleaner, and more controllable outputs.

(Anthropic says that XML tag prompts gets best results)

Language models can lie, flatter you, or even turn evil.

But now we can monitor and control their personality traits with just one vector.

A new research paper introduces persona vectors, and it changes everything for AI alignment.

Here's everything you need to know ↓ What are persona vectors?

They’re directions inside a model’s brain (activation space) that represent a specific trait like:

• evil
• sycophancy
• hallucination
• optimism
• humor

Once extracted, they let you measure, steer, or suppress traits in any LLM.

If you’re serious about mastering LLMs, agents, and AI systems start here.

HuggingFace just released 9 elite-level AI courses for free ↓ 1. LLM Course

Want to master large language models quickly?

This course guides you through training, fine-tuning, and deploying LLMs using HuggingFace Transformers.

huggingface.co/learn/llm-cour…

It’s 2025.

You either learn AI or get replaced by someone who did.

Here’s the no-fluff, 30-day roadmap to master AI ↓ Most beginners start by:

- Building chatbots
- Downloading agent frameworks
- Playing with APIs

But they don’t understand tokens, prompts, or context windows.

That’s like trying to write a novel before learning the alphabet.

This is wild

Microsoft just dropped a no-cost, no-code AI Agent training for beginners

here’s what’s included (and why you should try it): AI agents for beginners by Microsoft:

Check this out: github.com/microsoft/ai-a…

If you want to learn n8n, read this.

It’s the fastest way to understand what it is, why it matters, and how to use it to build your first AI-powered automation 👇 What is n8n?

n8n is an open-source automation tool that connects your apps, builds agentic workflows, and lets you host everything yourself.

Think Zapier, but with more power and zero vendor lock-in.

Ideal for devs, indie hackers, & AI builders.

n8n.io

what is an ai agent and how does it actually work?

it’s the most misunderstood concept in tech right now.

everyone’s using the term, but few people actually know what it means.

here’s a simple breakdown (plus 10 tools to build your own): first: what even is an ai agent?

think of it like an llm (chatgpt, claude, etc) that doesn’t just reply... it does stuff.

it can:

- decide what to do
- use tools + apis
- manage its own workflow
- work towards a goal on its own

you’re not building a chatbot.

you’re building a digital co-worker.

Claude 4 Sonnet is insanely powerful.

I wrote one mega prompt and now it do:

• Market research
• Content creation
• Writing viral ad copy
• SEO optimization
• Campaign planning

All in few seconds.

Here's the exact mega prompt we use to automate our marketing tasks: 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.

"

omg… this AI workflow is wild.

You can now run full competitive market analysis using ChatGPT, Gemini, and Grok deep research features.

Here are the exact 3 mega-prompts I use to replicate McKinsey-style insights for free: 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:

This is terrifying.

I gave Claude 1 mega prompt and it handled:

• Product strategy
• Backend code
• UI/UX design
• Landing page copy
• Go-to-market plan

All in one go.

Here’s the exact prompt I used (and what it built): The mega prompt:

(Copy and paste in Claude)


You are my all-in-one technical cofounder, product strategist, UI/UX designer, copywriter, and launch expert.
We're building a SaaS startup together, step by step.
Your role is to guide and execute each major milestone — but only continue after I review and approve the current step.



A [INSERT PRODUCT TYPE] SaaS that helps [TARGET USER] solve [PAIN POINT] using [SHORT TECH VALUE PROP]



Start by completing the first mission below. Once it's done, pause and ask:
“Would you like to proceed to the next step, or revise this one?”

Here’s the full step-by-step sequence you’ll execute **one at a time**:
1. Validate the target audience and define the core user problem
2. Propose a focused MVP feature list (prioritize essentials only)
3. Write backend code in [Python/FastAPI/etc] to implement the MVP
4. Describe the UI/UX structure (components + layout + flow)
5. Write Webflow-ready landing page copy (headline, value, CTA)
6. Draft Twitter launch thread + Product Hunt listing
7. Outline a 7-day content strategy for initial traction

Be concise but complete. Use markdown headers to structure each output. Treat this like a collaborative startup sprint — you lead, I approve.

Gemini 2.5 Pro is scary good.

I wrote a mega prompt for Gemini that turns it into a writing assistant and it’s so good I stopped outsourcing everything.

Landing pages, LinkedIn posts, email sequences done.

Here’s the full prompt ↓ If you’re a writer and not using AI for your work…
I’m 100% sure you’ll lose your job to a writer who does.

This isn’t a maybe it’s already happening.

Can Your Writer Get You Sued?

In short, YES!

In the top levels of copywriting, 8-9 figure companies are well aware of the legal consequences of what they publish.

On the flip side, most advisors / consultants never even think about this.

But if your business publishes it... Your business can be held liable for it.

The most common legal troubles you can get into as a result of blindly publishing what you writer provides you with include:

- Libel / Defamation
- Intellectual Property Theft
- False / Misleading Advertising

The solution?

Agency, Advisor or Coach?

These are the only two funnels that matter in 2023:

If you suck on camera:

ToFu = Twitter / LinkedIn / SEO
MoFu = Email / Off-Camera Video / Community
BoFu = Phone / Sales Page / Google Doc

If you're good on camera 👇 ToFu = TikTok + Reels + Shorts
MoFu = Email / On-Camera Video / Community
BoFu = Phone / Webinar / VSL

This is how digital service providers generate leads today.

Same applies if you're using ads.

You're just paying instead of playing the organic game.

Either way...