I built and sold a business to HubSpot in just 17 months.

I co-founded Mindstream, an AI newsletter that scaled to 150,000+ subscribers. Today, Mindstream is part of the HubSpot Media Network, where I lead brand strategy for the AI media products. 

Along the way, I’ve grown a 200,000+ following on LinkedIn, sharing real, unfiltered lessons on AI, entrepreneurship, and business growth. The wins and the mistakes.

I believe action beats hesitation. The biggest risk? Never starting.

Adam Biddlecombe

Helping Entrepreneurs Build with AI | Founder, Mindstream (Acquired by HubSpot)

Co-Founder & CEO 

Most people think Claude is just another chatbot.

That mistake is silently costing them hours every week.

Here’s how power users actually run work on Claude.

A few months ago, I noticed a pattern.

People were blaming AI for bad outputs.
But the real issue was how they were prompting and using it.

This Ultimate Claude Guide breaks down clearly.

And once you use it, 
You stop using Claude like a chat tool.
And start using it like a workflow engine.

Here’s what stood out 👇

What actually makes prompts work:
• Context first
• Clear role definition
• Specific tasks
• Structured outputs
• Hard stop conditions

→ Random prompts fail
→ Prompts with the right framework win

Why Claude is different?
→ Built for long reasoning
→ Handles massive documents smoothly
→ Safer, cleaner, more consistent outputs
→ Strong at coding, research, and workflows 

How people really use Claude:
✓ Code and debugging
✓ Long document analysis
✓ Business plans and reports
✓ Workflow automation
✓ Structured data extraction

Models explained:
→ Opus for deep reasoning and complexity
→ Sonnet for balanced daily work
→ Haiku for speed and lightweight tasks

If you want to understand:
→ How to prompt Claude properly
→ Which model to use and when
→ What outputs you can realistically automate

Check the infographic image carefully 👇
It saves weeks of experimentation

Learn AI for free: https://lnkd.in/euYZeAdb 

What you think about using Claude to automate manual work?
Comment below 👇 
I’m curious how far you’re already taking it

I’ve seen people waste months jumping between random AI hacks.

So I’ve created this one all-in-one AI cheat sheet for you.

To help you master everything important in one go.

Let me be brutally honest.

While you were writing one-line prompts, 
AI pros were using the RTCROS framework to get better results.

While you were guessing prompts, 
They were using chain-of-thought prompting to make AI think step by step.

While you were struggling with manual work, 
They were automating entire workflows with tools you've never even heard of.

Here's what the best AI users know that you don't:

Prompting tips to get 10x better outputs:
→ Zero-Shot gets instant results with no examples
→ Few-Shot guides AI with just 2-3 samples
→ Chain-of-Thought makes AI show its reasoning
→ Persona-Based makes AI adopt expert roles
→ Iterative Refinement keeps making outputs sharper

Tools they're using daily:
✅ Google Nano Banana Pro for stunning visuals in seconds
✅ Cursor for writing code 
✅ Zapier for automating tasks while they sleep
✅ Consensus for research that used to take weeks
✅ Gamma for presentations that look professionally designed

The AI models dominating right now:
→ ChatGPT-5.2 for adaptive multimodal thinking
→ Claude Opus 4.6 for deep reasoning and complex tasks
→ Grok 4.2 for live data and stronger creativity
→ Gemini 3.1 Pro for long-context multi-step workflows
→ Kimi K2 Thinking for hard analytical problems

Some business use cases where AI helps:
→ Digital operations getting fully automated
→ Lead generation running on autopilot
→ Sales cycles being cut in half
→ Marketing campaigns launching without agencies
→ Finance management handled without analysts

The crazy part?
All of this is learnable. 
Right now. 
For free.

The gap between people who invest in learning AI daily and those who don't is growing.

In the next 12 months, 
The professionals who mastered AI prompting, tools, and workflows will be untouchable in their careers.

The ones who didn't will be wondering what happened.
Actually using it every day is where winners are made.

Learn AI for free: https://lnkd.in/euYZeAdb 

How much time per day do you invest in learning AI? 
Be honest, and comment below 👇

98% think they’re using Claude perfectly.

They open the AI chat box and start prompting.

That’s exactly why they’re leaving 80% of its power unused.

When I first started using Claude, 
I made the same mistake.

I treated it like a chatbot.
Ask question → get answer → repeat.

But now, as I’ve set up Claude properly, 
Everything changed.

It started behaving like a system that actually works with me.
I got:
- Better writing.
- Better research.
- Better coding.
- Better reasoning.

Most people never unlock this because they skip the setup.

That’s why I’ve created this simple breakdown of how you can set up Claude the best way for you.

Here are the key ideas behind a powerful Claude setup:
→ Install Claude properly (desktop unlocks more capabilities)
→ Choose the right model for the job
→ Create a personal voice file Claude can reference
→ Define what you reject so Claude avoids bad habits
→ Give Claude real folders and context to work with
→ Enable features like artifacts and code execution
→ Add job-specific plugins for specialized work
→ Build reusable skills and workflows

When you configure Claude correctly, 
It starts acting like a reliable AI operator.

Do’s:
✅ Set profile preferences so Claude understands your writing style
✅ Give clear instructions and structured prompts
✅ Connect tools and folders for real context
✅ Create repeatable skills for frequent tasks
✅ Test different models based on the problem

Don’ts:
❌ Don’t rely on vague prompts and expect perfect outputs
❌ Don’t leave API keys or secrets in prompts or code
❌ Don’t ignore Projects when organizing complex work
❌ Don’t share sensitive data without checking security settings
❌ Don’t skip testing new Claude features and tools

If you set this up correctly, 
Claude becomes extremely powerful for:
• Writing
• Coding
• Research
• Analysis
• Workflow automation

To see the full setup breakdown, 
Check the infographic below 👇 
It will save you hours of trial and error.

Want to master how to use ChatGPT at work?
Grab my free guide here: https://lnkd.in/eJPyZ-Qe 

Curious to know something:
What do you think about setting up Claude for your workflow?
Comment below 👇

Stop using Claude just like an AI chatbot.

Most people are using only 10% of what it can actually do.

The real power of Claude starts when you understand its five modes.

I recently observed two of my friends use the same AI tool.
Same model.
Same tasks.

But their results were wildly different.

One got basic outputs.

The other generated reports, automated workflows, built tools, and even edited code repositories.

The difference was how they used Claude’s ecosystem.

And once you understand it, everything changes.

Here, I’ll break down the 5 core Claude capabilities:
→ Chat
→ Cowork
→ Projects
→ Skills
→ Code

Each one unlocks a completely different layer of AI productivity.

Here’s the simplified breakdown:
• Chat → Conversational AI for brainstorming, questions, and quick ideas
• Cowork → Desktop AI agent that can read/write local files and run workflows
• Projects → Persistent workspace with saved files, chats, and with long-term context
• Skills → Reusable instructions, templates, and automation triggers
• Code → Developer terminal agent for editing repos, debugging, and refactoring

Think of it like this:
• Chat = Texting a genius
• Cowork = An AI teammate doing real work
• Projects = Long-term memory for your tasks
• Skills = Your personal AI playbook
• Code = A senior engineer in your terminal

When used together, 
Claude becomes far more than just a chatbot.
It becomes an AI operating system for work.

Here are a few things advanced users already do with it:
→ Generate structured reports automatically
→ Analyze spreadsheets and datasets
→ Automate document workflows
→ Build internal tools and scripts
→ Debug and refactor entire codebases
→ Maintain persistent knowledge across projects

But most users still stay stuck in basic chat mode.
That’s like buying a smartphone and only using the calculator.

If you want to actually unlock Claude’s power, 
Follow these principles:

Do’s when using Claude:
✔ Define the goal clearly before prompting
✔ Use Projects for long-running work
✔ Store reusable instructions inside Skills
✔ Combine Cowork with local files for automation
✔ Use Code mode for repository-level tasks

Don’ts when using Claude:
✘ Don’t treat it like a simple Q&A bot
✘ Don’t rely only on one chat session
✘ Don’t ignore context tools like Projects
✘ Don’t skip reusable instructions and templates
✘ Don’t expect perfect results without structured prompts

Once you understand these layers, 
Claude stops being a chatbot and becomes infrastructure.

If you want to see how all five systems work together,
Check the infographic below 👇
I’ve explained the entire Claude workflow ecosystem. 

I spend hours every day researching how AI can help entrepreneurs.
If you want to know how, join here for free: https://lnkd.in/e2Jgyu5U 

I’m curious:
How are you currently using Claude?
Drop your thoughts in the comments 👇

A friend asked me yesterday how I finished 3 hours of work in just 30 minutes.

The truth is I used ChatGPT and all its best features to save hours of manual work.

I've covered all the 17 best features here for you.

1. Personalization: This feature helps you personalise how you want outputs from ChatGPT.

2. Speech Customisation: This setting helps you change the type of voice you want in ChatGPT.

3. Builder Profile Creation: This setting helps you get website visitors from your GPT.

4. Image Generation: This feature helps you create images from text prompts and reference images.

5. Web Search: It helps you search for anything on the internet with AI.

6. Canvas: It helps you work together with ChatGPT on writing and coding tasks.

7. Deep Research: It helps you create in-depth reports on any topic.

8. Search chats: You can search any chat with a keyword.

9. Library: You can check all the images you’ve generated with ChatGPT here.

10. Video Generation: You can generate videos from text prompts.

To know more features,
Check the infographic below 👇

You don't need to use all features at once.
You just need to be aware of these features and use the right ones at the right time.

Learn AI for free: https://lnkd.in/euYZeAdb 

Which feature in ChatGPT is your favourite?
Comment below 👇

♻️ Repost to help your network work with the best features in ChatGPT

Are you still using AI just as a chatbot?

If yes, 
You’ll be left behind. 

It is time to level up how you work with AI.

A few months ago, 
I noticed something strange.

Teams were using Claude daily.
Yet outputs felt random.
Workflows broke.
People blamed the model.

The truth was simpler.

Claude was guessing what to do.
Because no one told it how to do the task.

That is exactly what Claude Skills fixes.

Claude Skills are not prompts.
They are reusable instructions that turn chaos into systems.

Think of it like this:
• Prompts are one-time requests
• Skills are repeatable workflows
• Systems always outperform hacks

What changes when skills are used:
→ Fewer clarifications
→ Predictable outputs
→ Faster execution
→ Lower error rates
→ Cleaner automation

What a real Claude Skill includes:
• Clear purpose
• Strict structure
• Defined triggers
• Optional scripts and assets
• Portability across surfaces

Three skill categories that actually work:

1️. Document and asset creation:
• Reports
• PDFs
• Code docs
• Design artifacts

2. Workflow automation:
• Multi-step logic
• Review loops
• Research pipelines
• Validation checks

3. MCP enhancement:
• Tool access
• Error handling
• Domain intelligence
• Multi-tool orchestration

Why most people fail with skills:
→ They overtrigger
→ They underdefine scope
→ They skip frontmatter
→ They ignore structure
→ They test nothing

Five things to do when using Claude Skills:
✅ Start with 2 to 3 real use cases
✅ Define exact trigger phrases
✅ Keep instructions concise
✅ Test for over- and under-triggering
✅ Version and refine regularly

Five things to avoid:
❌ Writing vague descriptions
❌ Overloading a single skill
❌ Naming folders incorrectly
❌ Ignoring error handling
❌ Scaling before validation

How success here actually looks:
• Users do not ask follow-ups
• Outputs stay consistent
• Tool calls reduce
• First-time success increases

This is the shift most people miss.
AI is about building better systems.

If you want Claude to work like a teammate,
You have to train it like one.

If you want to master how to use ChatGPT at work with my free guide, get it here: https://lnkd.in/ezy3-CxF 

For the full breakdown, 
Check the infographic below 👇

What do you think about using Claude Skills for work?
Comment below 👇

🔁 Repost if this helped

If you want to be ahead of everyone in 2026,

You need to build your team of AI employees.

I used to think scaling meant working more hours and doing everything myself.

But now I did something different.
I built an AI team.

Every AI tool acts as an employee.
One for marketing.
One for development.
One for design.
One for research.
One for automation.
And more.

And suddenly, 
Work that took weeks,
Started finishing in hours.

Here’s how people are using AI as employees today:
→ ChatGPT as Chief Strategy Officer
→ Perplexity as Research Assistant
→ Claude as Writer
→ Canva as Designer
→ Zapier as Automation Engineer
→ Replit as Developer
→ HubSpot as Sales Manager
→ Beehiiv as Newsletter Manager
→ Taplio and Tweet Hunter as Ghostwriters
→ Gamma and VEED as Presentation and Video Experts

Most people fail with AI because they treat tools like toys.
High performers treat them like roles.

Do’s:
✅ Do assign one clear role per tool
✅ Do give examples and standards upfront
✅ Do review outputs like a manager
✅ Do combine tools into workflows
✅ Do keep humans in the decision loop

Don’ts:
❎ Don’t expect perfection on first output
❎ Don’t overload one tool with many roles
❎ Don’t skip context and instructions
❎ Don’t blindly trust outputs without review
❎ Don’t chase every new tool without a system

AI doesn’t replace teams.
It replaces friction.

If you want to know all the tools,
Check the infographic below 👇 

It visually maps how each AI fits into a real team.

If you like this and want to get free access to our complete ChatGPT at Work bundle guide, get it here: https://lnkd.in/e6yDSf4F 

What you think about building your own team of AI employees using powerful tools?
Comment below 👇

If you want to be ahead of everyone in 2026,

You need to build your team of AI employees.

I used to think scaling meant working more hours and doing everything myself.

But now I did something different.
I built an AI team.

Every AI tool acts as an employee.
One for marketing.
One for development.
One for design.
One for research.
One for automation.
And more.

And suddenly, 
Work that took weeks,
Started finishing in hours.

Here’s how people are using AI as employees today:
→ ChatGPT as Chief Strategy Officer
→ Perplexity as Research Assistant
→ Claude as Writer
→ Canva as Designer
→ Zapier as Automation Engineer
→ Replit as Developer
→ HubSpot as Sales Manager
→ Beehiiv as Newsletter Manager
→ Taplio and Tweet Hunter as Ghostwriters
→ Gamma and VEED as Presentation and Video Experts

Most people fail with AI because they treat tools like toys.
High performers treat them like roles.

Do’s:
✅ Do assign one clear role per tool
✅ Do give examples and standards upfront
✅ Do review out

Most people think they understand AI.

Until they realise they only recognise buzzwords.

I’ve curated the 40 important AI terms here to fix that gap.

A few months ago, I noticed something strange.

Smart professionals were using AI every day.
But struggling to explain it clearly.

They could say "LLM", "agents", or “hallucinations”.
But not understanding what those actually mean or why they matter.

That is the difference between using AI.
And thinking with AI.

So I broke it down here.

Why this matters more than people realise:
→ Clarity compounds faster than just using AI tools
→ Understanding beats memorising prompts
→ Vocabulary shapes how well you use AI

A few terms most people misuse daily:
• Bias → When training data tilts outputs
• Tokens → How models read and write text
• Inference → Using learned knowledge in real time
• Overfitting → When AI memorizes instead of generalizing
• Hallucinations → Confident answers without factual grounding

Do’s:
✅ Learn concepts before tools
✅ Connect terms to real workflows
✅ Understand limits, not just capabilities
✅ Revisit fundamentals regularly
✅ Explain ideas in your own words

Don’ts:
❎ Chasing tools without understanding basics
❎ Confusing AGI with current LLMs
❎ Ignoring training and data quality
❎ Treating prompts as everything
❎ Assuming AI is always correct

If you want leverage from AI,
You must speak its language first.

To get a quick scan of all 40 AI terms,
Check the infographic below 👇

Learn AI for free: https://lnkd.in/euYZeAdb 

How much time do you invest in learning AI every day?
Comment below 👇

You’re not getting bad AI outputs.

You’re using beginner-level prompts.

Here are the levels of prompting you must master to get better outputs from AI models/LLMs.

Level 1: Beginner
Includes:
- Task: Give ChatGPT a simple instruction.
About It:
- Only tell ChatGPT what to do without any extra details.
Prompt template:
- Do the following task: [insert the exact task clearly here].
Example prompt
- Do the following task: list 10 video ideas on productivity.

Level 2: Skilled
Includes:
- Task
- Context
About It:
- Tell ChatGPT what to do and add background details to guide direction.
Prompt template:
- Do the following task: [insert task]. Use this context while completing it: [insert background, boundaries, audience, exclusions]. Follow the task exactly using the given context.
Example prompt:
- Do the following task: list 10 productivity video ideas. Use this context: the audience is college students with short attention spans looking for simple improvements.

Level 3: Advanced
Includes:
- Task
- Context
- Output Format
About It:
- Tell ChatGPT what to do, add context, and specify the exact structure to follow.
Prompt template:
- Do the following task: [insert task]. Use this context: [insert context]. Present the final answer in this exact format: [insert output structure such as table, bullets, steps].
Example prompt:
- Do the following task: list 10 productivity video ideas. Use this context: beginners with busy schedules. Present them in a table with idea name and one line description.

To know the next levels,
Check the infographic below 👇

Learn AI for free: https://lnkd.in/euYZeAdb 

What level of prompting works best for you?
Comment below 👇

I watched an intern finish in 2 hours what took an expert 2 days.

Turns out the expert was using beginner-level AI tools. 
While the intern was using the advanced-level AI tools and was following the best practices.

Here are the novice vs expert AI tools that nobody's talking about in 2026.

Presentation creation:
- Novice-level tool: Gemini
- Expert-level tool: Gamma

Data analysis:
- Novice-level tool: ChatGPT
- Expert-level tool: Rows

LinkedIn growth:
- Novice-level tool: ChatGPT
- Expert-level tool: Taplio

Brainstorming:
- Novice-level tool: Llama
- Expert-level tool: Gemini 3 Pro

Research:
- Novice-level tool: Llama
- Expert-level tool: ChatGPT Deep Research

To know more AI tools,
Check the infographic below 👇 

How do I use AI tools?
1. Find new tool launches on Product Hunt, Twitter/X, Reddit, and LinkedIn
2. Check reviews of other leaders, creators, and builders
3. Test these tools
4. Use them in the long term if they help accelerate my work

Pros of using AI tools at work:
- Get more work done
- Take less time in getting work done
- Automate manual work
- Get more free time
- Work on things that are more valuable and don't involve only manual work

Do's of using AI tools:
✅ Do be specific and clear in your prompts to get useful results.
✅ Do fact-check outputs before using them in important work.
✅ Do maintain ethical use by avoiding bias and misinformation.
✅ Do keep a human in the loop for validation and oversight.
✅ Do protect data privacy by limiting what you share with the tool.

Don'ts of using AI tools:
❎ Don’t enter sensitive, confidential, or regulated data into AI tools.
❎ Don’t assume all AI outputs are correct without verification.
❎ Don’t use AI to mislead or produce deceptive content.
❎ Don’t use unauthorised AI tools that lack security assessment.
❎ Don’t rely on AI to make critical decisions without human judgement.

Learn AI for free: https://lnkd.in/euYZeAdb 

Do you use any expert-level tools?
Comment below 👇

Ulor Michael

I watched creators burn out using the wrong AI. 

Then a few quietly replaced entire teams with tools. 

Here are the AI tools of 2025 that help you dominate 2026. 

Brainstorming: 
2025: ChatGPT 5.2 
2026: Gemini 3

Analysis:
2025: ChatGPT 5.2 
2026: Rows

Data Visualisation:
2025: ChatGPT 5.2 
2026: Julius

Writing:
2025: ChatGPT 5.2 
2026: Claude

Coding:
2025: ChatGPT 5.2
2026: Claude Code

Development:
2025: ChatGPT 5.2
2026: Replit

Image Generation:
2025: Ideogram
2026: Google Nano Banana Pro

Video Generation:
2025: OpenAI Sora 2 Pro 
2026: Google Veo 3.1 

To know more tools,
Check the infographic below 👇 

How do I use AI tools?
- I already have a fixed set of tools I use every day at work and in daily life
- I also check new YouTube tutorials on new and trending AI tools
- I test if they can help me at work 
- If I find them useful, I use them in the long term 

Do's of using AI tools:
✅ Use AI to boost productivity on repetitive tasks.
✅ Check AI outputs for accuracy before use.
✅ Follow your company’s AI policy and approved tools list.
✅ Craft clear and specific prompts for better results.
✅ Use AI as an assistant, not a replacement for your expertise.

Don'ts of using AI tools:
❎ Don’t share confidential or sensitive data with AI.
❎ Don’t rely on AI for high-stakes decisions alone.
❎ Don’t use unapproved AI tools that risk data leakage.
❎ Don’t trust AI outputs blindly without review.
❎ Don’t let AI replace your judgement or domain expertise.

Learn AI for free: https://lnkd.in/euYZeAdb 

What other AI tools do you recommend adding here? 
Comment below 👇

Jourdan Go

You’re learning AI randomly, and that’s why you’re not improving fast.

You need a structured path that removes the guesswork.

Here are the 28 levels you should go through to go from zero to the best in the world in AI.

Level 0: 
AI Awareness: Learn what AI is and what it is not, and understand basic terminology.

Level 1: 
Digital Literacy: Master computer fundamentals, file systems, basic coding concepts, and internet research skills.

Level 2: 
Programming Foundations: Learn Python, control structures, functions, data types, and basic scripting.

Level 3: 
Math for AI Foundations: Understand linear algebra basics, probability fundamentals, and essential calculus concepts.

Level 4: 
Data Handling Basics: Learn data cleaning, preprocessing, visualisation, and working with datasets using Python libraries.

Level 5: 
Machine Learning Fundamentals: Understand supervised, unsupervised, and simple model training workflows with scikit-learn.

Level 6: 
Practical ML Application: Learn model evaluation, cross validation, feature engineering, and real-world ML pipelines.

Level 7: 
Deep Learning Foundations: Understand neural networks, backpropagation, activation functions, and basic model architectures.

Level 8: 
Applied Deep Learning: Learn to build and train CNNs, RNNs, LSTMs, and transformers and run experiments with PyTorch or TensorFlow.

Level 9: 
Natural Language Processing: Understand tokenisation, embeddings, sequence models, and transformer-based NLP workflows.

Level 10: 
Large Language Models: Basics Learn how LLMs function, including attention mechanisms, pretraining, fine-tuning, and inference concepts.

To know about the next levels,
Check the infographic below 👇 

Why should you master AI?
👉 AI skills increase employability across fast-growing industries
👉 AI enables automation that saves time and boosts productivity
👉 AI mastery helps future-proof careers as workplaces adopt AI systems
👉 AI knowledge supports innovation in products, services, and solutions
👉 AI expertise provides a competitive edge and higher earning potential

Do's:
✅ Build strong fundamentals in maths, programming, and core AI concepts.
✅ Learn to interpret and validate AI outputs instead of accepting them blindly.
✅ Focus on ethical, secure, and responsible AI use and development.
✅ Practise with real projects and datasets for deeper understanding.
✅ Stay updated on new models, tools, and research in AI.

Don'ts: 
❎ Don’t skip fundamentals and jump straight to advanced techniques.
❎ Don’t rely solely on AI tools without understanding underlying logic.
❎ Don’t ignore ethical concerns like bias and fairness.
❎ Don’t expect AI to do all the work without human oversight.
❎ Don’t rush through learning all topics at once without clear focus.

Learn AI for free: https://lnkd.in/euYZeAdb  

Do you invest time in learning AI every day?
Comment below 👇

I still remember my first 30 days in 2023 trying to grow on LinkedIn.

I posted every day.
I followed every “growth hack."

And still… nothing moved.

But now, I don’t overthink what to post but work more on analysing posts.

That single shift changed everything.

Instead of using ChatGPT to write content, 
I use it to think like a strategist.

Here are 10 ChatGPT prompts that don’t just help you create content.
They help you reverse engineer attention, clarity, engagement, and growth.

1. LinkedIn Content Performance Diagnostic

Prompt: Act As A Senior LinkedIn Growth Strategist. Analyze My Last [X] LinkedIn Posts Pasted Below. For Each Post, Evaluate Hook Strength, Clarity Of The Core Idea, Value Density, Emotional Resonance, Scroll Stopping Potential, Structure Flow, And Likelihood Of Saves Or Comments. Identify Recurring Patterns Across High And Low Performing Posts. Highlight What’s Working, What’s Underperforming, And What Is Missing. Then Summarize 5 Specific, Actionable Insights I Should Apply To Future Content To Improve Reach, Engagement, And Follower Growth.

2. Competitor Content Pattern Analysis

Prompt: Act As A LinkedIn Competitive Intelligence Analyst. I Will Paste Content From [3–5] LinkedIn Creators In My Niche. Analyze Their Posts To Identify Repeating Patterns In Hooks, Post Length, Formatting, Narrative Style, CTA Usage, Topic Selection, And Emotional Triggers. Break Down What Makes Their Content Consistently Engaging. Identify Which Elements Are Replicable Versus Personality Dependent. Conclude With A Clear List Of Strategic Patterns I Can Ethically Adapt To Improve My Own LinkedIn Growth.

To get more prompts, 
Check the infographic below 👇 

Do’s:
✅ Use AI to outline, analyse, and structure posts before writing.
✅ Give AI clear context, goals, and examples for better outputs.
✅ Edit AI output to match your voice and audience expectations.
✅ Use AI to analyse performance patterns and engagement signals.
✅ Apply AI for strategy and thinking, not just writing posts.

Don’ts:
❎ Don’t publish AI output without human review and editing.
❎ Don’t trust AI blindly for facts, stats, or claims.
❎ Don’t rely on generic prompts that produce generic content.
❎ Don’t let AI dilute your personal perspective or experience.
❎ Don’t repeat the same AI templates across every post.

This way to win is not to just post more.
It’s about posting with intent, structure, and leverage.

AI is changing how content is created, 
But the real edge is knowing how to use it well. 

Learn AI for free: https://lnkd.in/euYZeAdb 

What’s your honest take on using AI for content creation? 
Comment below 👇

Don’t be stuck only on ChatGPT.

The real power of AI starts when you stop using one tool.
And start building a workflow with niche AI tools.

Recently, I observed something interesting.

Two people said they use AI.
Both said the same thing.

“I use ChatGPT every day.”

And both of them did not see any huge productivity boost with AI.

That is when the difference became obvious.

→ Beginners are stuck on ChatGPT.
→ Experts build a stack of niche AI tools.

And that shift changes everything.

Look at how advanced operators actually work today:
• Use n8n → Automate AI agents
• Use Zapier → Connect thousands of workflows
• Use Replit → Build software faster
• Use Cursor → AI-assisted coding
• Use ChatGPT Deep Research → Deep analysis
• Use Freepik AI → Generate visuals instantly
• Use Higgsfield →Ccreate AI videos
• Use VEED → Edit videos faster
• Use Beehiiv → Run AI powered newsletters
• Use VidIQ → Optimize YouTube growth
• Use Tweet Hunter → Accelerate X growth
• Use Supergrow → Grow on LinkedIn
• Use aiCarousels → Create viral carousel posts

This is how AI starts becoming your digital workforce.

The real unlock is simple:
• One tool → Small improvement
• Many niche tools → 10x productivity boost

The operators who win in the next decade will not just “use ChatGPT”.

They will orchestrate AI tools together.

That is the difference between experimenting with AI…
And actually compounding productivity with it.

Take a look at the infographic below 👇 
It perfectly visualises how beginners and experts perceive AI.
You might recognise yourself somewhere on that iceberg.

Do's when using niche AI tools:
✅ Use specialized tools for specific tasks
✅ Connect tools together using automation platforms
✅ Build repeatable workflows instead of one off prompts
✅ Evaluate tools based on real productivity gains
✅ Combine AI tools to create leverage systems

Don'ts when using niche AI tools:
❌ Do not rely on one AI tool for everything
❌ Do not chase every new tool without a workflow
❌ Do not ignore automation opportunities
❌ Do not skip testing tools in real use cases
❌ Do not replace thinking with blind automation

AI power comes from how many tools you can orchestrate together.

If you want to master how to use ChatGPT at work with my free guide, get it here: https://lnkd.in/ezy3-CxF 

Curious to hear your thoughts.
What do you think about using niche AI tools instead of relying on one AI platform?
Comment below 👇

"I need to be in tech to learn and work with AI" is a lie.

And I get to hear this lie every day.

Here are 20 YouTube channels that will help you master new AI skills.

1. Simply Digital
Get to know how to build your side hustle with AI.

2. Nick Ponte
He helps you learn how to be a better marketer with AI.

3. AI Andy
You get to learn how to use new AI tools.

4. Unseen Tech
Get to know AI updates, tools, and tutorials to level up your workflows.

5. Nick Saraev
He makes money with automation & teaches others how they can too.

6. Ethan Nelson
He builds AI agents for his clients and shows you how to do the same.

7. Greg Isenberg
Startup ideas & tutorials on how to use AI to build & grow your startup.

8. The AI Advantage
Get practical tutorials and weekly AI updates that you’ll actually use at work.

9. Yannic Kilcher
Analyses and explains AI research papers in detail, ideal for intermediate and advanced learners.

10. Matt Wolfe
Get AI News Breakdowns every Saturday and other cool nerdy tech and AI stuff in between.

Learn AI for free: https://lnkd.in/euYZeAdb 

Do you invest time in learning AI every day?
Comment below 👇

Stop using Perplexity in beginner mode. 

I’ve seen many people use the wrong prompts on it.
And that is why they get average outputs.

Last week, 
I was researching a topic for a project.

I opened Perplexity.
Typed a simple search query.
And got a decent answer.

But then I tried something different.
I used structured prompts instead of the basic one.

Suddenly the quality of research changed completely.

Instead of surface-level summaries, I got:
→ deeper insights
→ better sources
→ clearer comparisons
→ structured thinking

That is when it clicked.
AI search is just about prompting smarter.

I’ve created 10 powerful Perplexity prompts that can turn basic searches into deep research outputs.

Here are a few ways people actually use Perplexity effectively:
• Deep research briefs for complex topics
• Fast fact-checking before publishing content
• Trend research across industries
• Competitive landscape analysis
• Market research and industry mapping
• Product comparisons before buying
• Software discovery and tool evaluation
• Monitoring news and developments
• Structured decision-making
• Learning new skills faster

Think of Perplexity as a research assistant.
Use it correctly and it becomes incredibly powerful.

Here are a few smart ways to use Perplexity better:
✅ Ask structured prompts instead of simple questions
✅ Request multiple sources and citations
✅ Ask for comparisons and trade-offs
✅ Ask for trends across time periods
✅ Request summarized insights with key takeaways

But there are also mistakes many people make.

Here are things you should NOT do when using Perplexity:
• Don't rely on a single answer without checking sources
• Don't ask vague questions without context
• Don't ignore conflicting viewpoints
• Don't treat summaries as complete research
• Don't skip verifying important claims

Remember this:
AI search tools are powerful.
But the quality of the output depends heavily on the quality of the prompt.

A good prompt can turn a basic search into a strategic research briefing.

To get all the 10 prompts for smart web search with Perplexity,
Check the infographic below 👇 

To master how to use ChatGPT at work, get my free guide here: https://lnkd.in/efMwyWq8 

I am curious about something.
What do you think about using Perplexity for web search?
Comment below 👇

In 2019, knowing development made you valuable.

In 2021, knowing growth made you visible.

In 2030, these skills will decide if you are replaceable or irreplaceable.

Core skills:
These skills are a high priority now and rising further.

These skills are:
- Analytical thinking
- Creative thinking
- AI and big data
- Technological literacy
- Leadership and social influence
- Curiosity and lifelong learning
- Resilience, flexibility, and agility
- Systems thinking
- Motivation and self-awareness
- Empathy and active listening
- Service orientation and customer service

Strategic implication:
These are non-negotiable skills. Organizations should hire for them, train continuously, and design roles around them.

To know more skills that matter,
Check the infographic below 👇 

Pros of learning high-value skills:
👉 Higher employability as jobs change rapidly due to ai and automation trends
👉 Ability to move into newly created roles and industries
👉 Stronger resilience to job obsolescence and market shifts
👉 Improved earning potential through in-demand skill sets
👉 Enhanced adaptability for continuous learning and future challenges

Dos:
✅ Learn continuously to stay relevant as roles evolve
✅ Build AI and digital literacy as a core skill
✅ Strengthen critical thinking and emotional intelligence
✅ Practice adaptability and fast relearning
✅ Prioritize problem solving and creativity

Don’ts:
❎ Don’t depend only on degrees for future value
❎ Don’t neglect communication and collaboration skills
❎ Don’t learn without real-world application
❎ Don’t resist new tools and technologies
❎ Don’t postpone learning until forced to

Learn AI for free: https://lnkd.in/euYZeAdb 

How much time do you spend every day learning new skills?
Comment below 👇

You’re using ChatGPT wrong.

It’s not the model; it’s your prompts.

Here are 20 prompting techniques to unlock its real power.

✅ Zero-Shot Prompting
Ask the model to perform a task without providing any examples.

✅ Few-Shot Prompting
Provide a few examples to guide the model’s output.

✅ One-Shot Prompting
Give exactly one example before the main task.

✅ Self-Refine Prompting
Instruct the model to critique and improve its own answer.

✅ Comparative Prompting
Ask the model to compare two or more items using specific criteria.

What prompting techniques will you try?
Comment below 👇 

Learn AI for free: https://lnkd.in/euYZeAdb 

♻️ Share this to help your network use the best ChatGPT prompting techniques

The AI gold rush is already here.

But very few people know where the gold actually is.

I and my team mapped more than 200 ways to make money with AI after 100 hours of experimenting and research.

In this detailed guide, we cover:
- 200+ strategies tailored for creators, entrepreneurs, and forward-thinking professionals
- Profitable ideas in industries such as content creation, e-commerce, gaming, and more
- Insights into cutting-edge AI applications for sustainable growth
- Easy-to-start strategies
- Future-proofing your skills
And a lot more

To get it for free,

1. Like
2. Comment 'AI'

And I'll send it to you ASAP

Most people use Excel like it is 2022.

Your spreadsheets have an AI brain now.
.
And it might save you 100+ hours of work.

Last week I was helping someone debug a broken Excel model.

You know the situation.

• Random REF errors
• Formulas stacked inside formulas
• 20 sheets connected together
• Nobody knows where the numbers come from

He told me he spent almost an hour tracing one formula.

Then something interesting happened.

I helped him use Claude inside Excel and AI explained the entire spreadsheet logic in seconds.

That is when it clicked.

Excel is becoming an AI-assisted tool.

And the capabilities are honestly wild.

Here is what Claude inside Excel can actually do:

→ Work directly with your workbook
• Reads sheets, formulas, and cell ranges
• Understands cross-sheet dependencies
• References exact cells when answering questions

→ Debug spreadsheets faster
• Find why a formula returns errors
• Trace references across sheets
• Suggest safe fixes before applying changes

→ Explain spreadsheet logic
• Translate complex formulas into plain English
• Show where numbers come from
• Reveal hidden calculation chains

→ Build spreadsheet structures
• Create formulas automatically
• Generate multi-sheet models
• Build financial projections or scenario analysis

→ Extract data into Excel
• Convert structured PDFs into tables
• Organize imported information cleanly

→ Analyze data instantly
• Surface patterns and trends
• Rank top-performing rows
• Generate insights without writing formulas

But there are a few important rules if you want to use it well.

Do's when using Claude in Excel:
✅ Ask it to explain formulas before editing
✅ Review every suggested change carefully
✅ Use it for debugging and analysis
✅ Let it generate structures and formulas
✅ Validate results for sensitive decisions

Don'ts when using Claude in Excel:
❌ Do not treat it as perfect automation
❌ Do not skip reviewing its changes
❌ Do not assume it replaces Excel expertise
❌ Do not rely on it for macros or Power Query tasks
❌ Do not use outputs blindly for financial decisions

Real shift here is bigger than Excel.

Workflows are changing.

Before: 
Idea → Build formulas → Debug → Analyze → Present

Now: 
Idea → Ask AI → Review → Ship 

If you use spreadsheets regularly, 
This might become one of the most powerful productivity upgrades this year.

To see how Claude actually works inside Excel,
Check the infographic below 👇 

Want to master how to use ChatGPT at work?
Grab my free guide here: https://lnkd.in/eJPyZ-Qe 

Curious to hear your perspective.
What do you think about using Claude inside Excel for data analysis?
Comment below 👇

taplio

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