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 

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 👇

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.
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 

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

Stop using ChatGPT for everything.

The smartest builders use specialised AI tools instead.

Because the right AI tool can save you hours every week.

I’ve noticed something interesting.

Everyone around me kept opening the same tab.

ChatGPT.

For:
Writing.
Research.
Presentations.
Data analysis.
Video ideas.
Coding.

Everything.

But the truth is simple:

ChatGPT is powerful.
But not always the best tool for every task.

The real advantage comes from using specialised AI tools built for specific workflows.

Once I started experimenting with alternatives, 
My productivity accelerated overnight.

Here are some powerful AI tools most people should be using alongside ChatGPT:

Research → SciSpace
Presentations → Gamma
Brainstorming → Claude
Learning → NotebookLM
Data analysis → Rows
Data visualization → Julius
Video generation → Freepik
Image generation → Higgsfield
Marketing copy → Writesonic
Scriptwriting → Sandcastles AI
Content creation → Veed
Development → Replit
Website development → Webflow
Customer support AI → Expertise AI
Deep research → Perplexity Deep Research
Meeting notes → Granola

Each tool is designed for a specific problem.
Which means better outputs and faster workflows.

Instead of forcing one AI to do everything:
✔ Use the best AI for the job
✔ Combine multiple AI tools
✔ Build faster workflows

And the results compound fast.

Do’s:
✔ Use specialized tools for specialized tasks
✔ Combine multiple AI tools in one workflow
✔ Verify important outputs with reliable sources
✔ Use AI to speed up thinking, not replace it
✔ Experiment with different tools regularly

Don’ts:
✖ Do not rely on a single AI tool for every task
✖ Do not skip fact-checking for research outputs
✖ Do not assume AI-generated data is always correct
✖ Do not ignore domain-specific AI tools
✖ Do not replace human judgement with AI

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 

To see the full breakdown of tools,
Check the infographic below 👇 

And I am curious
Which other AI tool alternative do you think works better than ChatGPT for a specific task?
Drop it in the comments 👇

Stop using ChatGPT for everything.

The smartest builders use specialised AI tools instead.

Because the right AI tool can save you hours every week.

I’ve noticed something interesting.

Everyone around me kept opening the same tab.

ChatGPT.

For:
Writing.
Research.
Presentations.
Data analysis.
Video ideas.
Coding.

Everything.

But the truth is simple:

ChatGPT is powerful.
But not always the best tool for every task.

The real advantage comes from using specialised AI tools built for specific workflows.

Once I started experimenting with alternatives, 
My productivity accelerated overnight.

Here are some powerful AI tools most people should be using alongside ChatGPT:

Research → SciSpace
Presentations → Gamma
Brainstorming → Claude
Learning → NotebookLM
Data analysis → Rows
Data visualization → Julius
Video generation → Freepik
Image generation → Higgsfield
Marketing copy → Writesonic
Scriptwriting → Sandcastles AI
Content creation → Veed
Development → Replit
Website development

Quality of learning always beats quantity of content.

We live in a world where information is infinite.
But attention is not.

For a long time, I thought staying ahead meant consuming more.
More books. 
More newsletters. 
More podcasts. 
More tutorials.

It does not.
It means learning with intention.

Early on, books like Find Your Why shaped how I thought about purpose and direction. 
They gave me language for decisions I could already feel but could not yet explain.

Today, I still return to ideas like that.

Just differently.

I use Shortform.

Not to replace books.
But to understand them better.

Shortform creates book guides that go beyond summaries:

- Deep coverage of core ideas
- Smart analysis and connections across authors
- Interactive exercises that make ideas stick

It feels like your smartest friend walking you through a book.

Three categories I personally spend the most time on:

- Business and entrepreneurship
- Psychology and decision-making
- Communication and negotiation

Here are my favorite books I recommend to learn from:

1. Magic of Thinking Big.
You’ll learn
- Think bigger to unlock higher confidence, ambition, and results.
- Beliefs shape actions, and actions determine success.
- Positive thinking enables better decisions and consistent progress.

2. How to Win Friends and Influence People.
You’ll learn:
- Genuine interest in others builds trust and influence.
- Avoid criticism to maintain strong relationships.
- Make people feel valued to earn cooperation.

3. How to Get Rich
You’ll learn:
- Persistence matters more than talent or luck.
- Wealth comes from execution, not ideas alone.
- Long term success requires resilience and self belief.

The best part is:
On Shortform, I can combine learning from these best books.
To know what I should focus on in the long term.

That is where real leverage comes from.

Shortform also releases new book and article guides every week.
And I get to vote on what gets covered next.

And when I am reading blogs or watching long YouTube videos, 
Their browser extension, Shortform AI, 
Helps me generate high-quality summaries instantly. 
Just in one click.

The result is simple:
- I spend less time skimming.
- More time thinking.
- More time connecting ideas.
- More time building judgement.

Learning compounds when the input is high quality.

If your goal is not just to consume content, 
But to sharpen how you think, 
Shortform is worth exploring.

You do not need more information.
You need better understanding.

Try here: shortform.com/biddlecombe 

Get a free trial and $50 off the annual plan from my link. 

What do you think about learning this new way?
Comment below 👇 

#shortformpartner

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 👇

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 too

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 👇

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 

Drowning in huge PDFs?

You don’t need more coffee.
You need AI assistance.

Here’s how to use AI for document analysis.

1. Go to ChatGPT
2. Click the ‘+’ icon
3. Add your document
4. Write your prompt
5. Get document analysis done
6. Follow up if you need more insights

Pros:
- Ultra-fast summarisation of long texts.
- Good at extracting key entities, relationships, and topics.
- Can handle multiple formats (text, tables) if converted appropriately.
- Provides a “first-pass” analysis so you don’t start from blank.
- Repeatable and consistent (for the same prompt & input).

Cons:
- May (rarely) hallucinate or invent details that aren’t in the document.
- Doesn’t always catch domain-specific nuance or technical subtleties.
- Performance degrades on very long documents (context window limits).
- No guarantee of source attribution or traceability.
- Biases in training data may skew interpretation.

Do’s
✅ Always give context or purpose before asking for analysis.
✅ Break large docs into smaller chunks for processing.
✅ Ask for both summary and insights/implications.
✅ Request sources or cite-backs for key claims.
✅ Iterate (ask follow-up clarifications) instead of expecting perfection on the first prompt.

Don'ts
❎ Don’t dump an enormous document in one go without context.
❎ Don’t trust the output blindly; always verify critical facts.
❎ Don’t ask vague prompts like “analyse this” without direction.
❎ Don’t ignore structure (tables, figures, sections); treat them explicitly.
❎ Don’t overload with too many goals in one prompt (summary + critique + rewrite + translate all at once).

To get a more detailed explanation,
Check the carousel below 👇 

What do you think of using AI for document analysis?
Comment below 👇 

Learn AI for FREE: https://lnkd.in/eAAacxSK  

♻️ Share this to help your network use AI for document analysis

How To Do Document Analysis For Free With ChatGPT

Marketing & AI | Brand & Business Unit Director @ P&G | Leading Teams | Growing Multi-Million $ Brands

Marketing Director - Clinique | ELC AI Leader | Helping You Accelerate Your Career with AI | ex-P&G

Brand Builder, Commercial & Online Leader with 16+ years of experience. 

AI / digital marketing expert and enthusiast.

I share content to help you on your Marketing & AI journey. 


My views / endorsements are my own and do not reflect those of my employer.

Jonathan Parsons

98% people are talking about AI tools.

The top 2% are building an AI team.

That difference is where the real leverage lives.

Recently, I watched a founder try to run everything alone.
- Writing.
- Design.
- Research.
- Sales.
- Marketing.
- Content.Automation.

He worked 16 hours a day and still felt behind.

Then he changed one thing.

And started thinking of AI tools as employees.

Today his “AI team” handles most of the manual work while he focuses on strategy.

The truth is simple:
You need the right AI stack.

Your AI team could look like this:

● Strategy
→ ChatGPT as Chief Strategy Officer
→ Perplexity as Research Assistant

● Content creation
→ Claude as Writer
→ Jasper as Marketer
→ Tweet Hunter for X ghostwriting
→ Taplio for LinkedIn content

● Design and media
→ Canva as Designer
→ Freepik for images and videos
→ VEED for video editing

● Growth and distribution
→ Sandcastles AI for Instagram growth
→ VidIQ for YouTube growth

● Website and product
→ Webflow as Website Developer
→ Replit as Developer

● Marketing and revenue
→ HubSpot as Sales and Marketing Manager
→ Beehiiv as Newsletter Manager

● Operations and automation
→ Zapier as Automation Engineer
→ Rows as Data Analyst

● Support and assistants
→ Expertise AI for customer support
→ OpenClaw as AI assistant

When these tools work together, 
Something interesting happens.
Your output multiplies.

Instead of working like a solo operator, 
You suddenly operate like a small AI-powered company.

But building an AI team the right way matters.
Here are the rules I follow.

Do’s when building an AI team:
✅ define clear roles for each AI tool
✅ connect tools through automation workflows
✅ verify outputs before publishing or executing
✅ design repeatable systems and pipelines
✅ keep humans responsible for strategy and judgement

Don’ts when building an AI team:
❌ Don’t rely on one tool for everything
❌ Don’t automate without checking accuracy
❌ Don’t overload workflows with unnecessary tools
❌ Don’t skip human review in critical decisions
❌ Don’t forget data privacy and security practices

AI is changing what teams look like.

The smartest builders today are quietly assembling their AI workforce.

And the productivity gap is growing fast.

To see how an entire AI team can be structured,
Check the infographic below 👇 

Curious to hear your thoughts.
What do you think about building your own AI team?
Comment below 👇 

If this helped you rethink AI workflows:
➕ Follow me for more insights on AI, marketing and digital leverage

♻️ Repost to help your network use AI in a better way

Marketing Director - Clinique | AI Leader | Helping You Accelerate Your Career with AI | ex-P&G

If you're not using AI for SEO,

You're falling behind.

A few months ago, 
I reviewed dozens of blog posts that were "AI-optimised".

Google did not penalise them.
Readers did.

That is when it clicked.

AI is not here to replace SEO thinking.
AI is here to amplify good SEO operators and expose lazy ones.

Use it right.
And AI becomes a force multiplier.

Use it blindly.
And it becomes a content factory with zero soul.

Here is how smart teams are using AI for SEO 👇
• Content personalisation → leads to relevance at scale
• Keyword research → helps with faster signal discovery
• Blog creation → Structure matters more than speed
• Meta descriptions → Clarity and CTR both matter
• Trend analysis → Timing the new wave 
• FAQs → Match intent
• Rewrites → Refine with more human tone

What separates winners from noise 👇
→ Role prompting matters
→ Better context beats creativity
→ Powerful strategy beats more volume

Use AI like an SEO partner.
Not a content vending machine.

Do’s:
✔ Prompt to act like an SEO expert before prompting
✔ Feed real context and constraints
✔ Use AI for ideation and structure
✔ Edit outputs with human judgment
✔ Optimize for human users

Don’ts:
✖ Don’t blindly publish raw AI content
✖ Don’t chase keywords without intent
✖ Don’t ignore Google quality guidelines
✖ Don’t overoptimise titles and headings
✖ Don’t forget originality and expertise

AI does not rank content.
People do.
And Google follows people.

If you want to win with AI + SEO, 
Stop asking: “Can AI write this for me?”

Start asking: “How can AI make this better than anything already ranking?”

To get practical prompts and tools,
Check the infographic below 👇

What do you think about using AI for SEO assistance?
Comment below 👇

➕ Follow for more no-fluff AI insights

♻️ Repost if this changed how you see AI + SEO

Most people are still stuck on using ChatGPT to write faster.

The smartest people use it to think better.

And that single shift changes the quality of every decision they make.

A few months ago, I noticed something uncomfortable.

Two of my friends had access to ChatGPT.
They both used different prompts.

One kept making average decisions.
The other made impactful decisions.

The difference was not in their intelligence.
It was how they used ChatGPT.

Most people ask AI for answers.
High performers use AI to stress test their thinking.

That is the real power.

Here is what elite decision-makers quietly do differently with AI 👇
• They slow down before deciding
• They expose hidden assumptions
• They simulate failure before it happens
• They zoom out before locking in
• They treat AI like a thinking partner, not an oracle

Use ChatGPT to:
→ Identify the real problem, not the visible one
→ Challenge assumptions you did not know you had
→ Simplify complex decisions into one clear sentence
→ Run pre-mortems before reality does it for you
→ Compare options beyond gut feeling
→ Map risks before they surprise you
→ Spot second-order effects early
→ Define success before execution
→ Sequence steps instead of improvising

You’ll get:
✅ Better clarity
✅ Fewer emotional decisions
✅ Less regret
✅ Faster learning
✅ Stronger long-term outcomes

Do’s:
✅ Do define the decision clearly
✅ Do ask AI to argue against you
✅ Do request best-case and worst-case outcomes
✅ Do use pre mortem analysis
✅ Do combine AI insight with human judgement

Don’ts: 
❎ Do not outsource responsibility
❎ Do not accept the first answer
❎ Do not ignore context and constraints
❎ Do not skip risk analysis
❎ Do not treat AI as a replacement for thinking

To get powerful ChatGPT prompts for better decision-making,
Check the infographic below 👇 

What do you think about using AI to accelerate decision-making?
Comment below 👇 

 ➕ Follow for more practical AI insights

 ♻️ Repost if this changed how you see ChatGPT

Google is no longer your best online organic growth source.

AI platforms are quietly replacing it.

Here’s the AI platform search optimisation shift marketers (and you too) can’t ignore.

What used to be:
→ Search
→ Scroll
→ Click
→ Browse
→ Buy

Is now:
→ Ask AI
→ Get answer
→ Visit the site
→ Buy

Organic traffic is not slowly declining.

In many categories, 
It is being cut out of the loop entirely.

AI search platforms can provide content similar to these:
• Media sites.
• How-to blogs.
• Product reviews.
• Educational content.

AI is answering the question before your regular blog post ever loads.

Google knows this.
That’s why you’re seeing defensive moves everywhere.

ChatGPT knows this too.
That’s why product discovery, recommendations, ads, and even purchasing are happening inside the chat.

SEO is no longer just about ranking pages on Google and traditional search platforms.

It is about being citable, trusted, and selected by AI search platforms along with traditional search platforms like Google.

If you care about:
• Future growth
• Brand visibility
• More discoverability
Check the infographic attached to learn about this shift 

I’ve broken down exactly what is changing and how AI SEO actually works now.

I’m curious. 
Do you think AI platforms will fully replace traditional search, or will Google adapt fast enough?
Comment below 👇

If this made you rethink SEO,
Follow for more AI and marketing breakdowns

♻️ Repost so your network sees where search is heading

The search game has been revolutionised.
The question is who adapts first to this new game.

Marketing Director - Clinique | UK ELC AI Leader | Helping You Accelerate Your Career with AI | ex-P&G

Most small businesses don’t fail because of bad ideas.

They fail because owners are doing everything themselves.

- Admin.
- Finance.
- Support.
- Marketing.
- Sales.

At some point, hard work stops scaling.

That’s where AI quietly changes the game.

I saw a small founder last year juggling invoices at midnight, 
Replying to customer emails at 6 AM, 
And designing posts on weekends.

Today?
AI helps with 75% of that work.

Here’s what stood out to me 👇

● Operations stop being chaos
→ Use Chatgpt for clarity
→ Use Notion to build systems
→ Use Motion for focus 

● Finance stops being scary
→ Try Quickbooks for bookkeeping
→ Use Numeral AI for forecasting
→ Test Tally for faster invoicing

● Customer support runs 24/7 with:
→ Zendesk AI
→ Tidio AI
→ Crisp AI

● Marketing becomes consistent with:
→ Canva magic studio for design
→ Jasper for copy
→ OpusClip for repurposing

● Sales no longer slip through cracks:
→ Hubspot AI for pipeline management
→ Apollo AI for lead management
→ Claude for proposal refinement

● Productivity actually improves
→ Use Perplexity for research
→ Try Zapier AI for automation
→ Test Loom AI for async clarity 

Dots connect fast when tools work together.

To know all the tools in detail,
Check the infographic below 👇 

👉 Follow for more practical AI for business

♻️ Repost if this helped you rethink your workflow

What do you think about small businesses using AI?
Comment below 👇

98% are using Google Gemini Pro wrong.

Not because the model is weak, but because their prompt is.

Gemini 3.1 Pro rewards depth in prompts

A few months ago, 
I thought “AI reasoning” was just a buzzword.

Then I tested Google Gemini 3.1 Pro on problems that usually break models.
Abstract reasoning.
Logic chains.
Multimodal tasks.
System-level thinking.

That’s when it clicked.

The model is built for people who actually think.

Gemini 3.1 Pro is what happens when AI stops guessing and starts reasoning.

Here’s what makes it different 👇
• 77.1% on ARC AGI 2
• Massive leap in core reasoning
• Handles abstract logic far better
• Strong multimodal understanding
• Built for complex systems

Where it shines most:
→ Deep problem solving
→ Logical reasoning puzzles
→ Multistep decision-making
→ Developer and API workflows
→ Visual, text, and video inputs

Where people mess it up:
• Treating it like a quick answer bot
• Giving vague prompts
• Expecting magic without context
• Skipping structure
• Ignoring its strengths

Do’s:
✔ Use clear, specific prompts
✔ Provide rich context
✔ Ask for step by step reasoning
✔ Use multimodal inputs when relevant
✔ Deploy it on Vertex AI or AI Studio for serious workflows

Don’ts:
✖ Don’t expect perfect answers without details
✖ Don’t use it for trivial queries
✖ Don’t overload one prompt with unrelated tasks
✖ Don’t ignore safety constraints
✖ Don’t treat outputs as unquestionable truth

This AI model is a thinking engine.

If you want the full breakdown, 
Check the infographic below 👇

And tell me, 
What do you think about using Google Gemini 3.1 Pro for problem-solving?
Comment below 👇 

 ➕ Follow for more AI model explainers 

♻️ Repost to help your network work with Google’s best AI model

High performer… but you’re still not getting promoted?

Every time a mentee or someone on my team asks how to progress their career, I give them the framework I have stood by for years:

PIE.

Performance.
Image.
Exposure.

Performance is doing great work.
Image is how people perceive your leadership.
Exposure is ensuring key stakeholders see both.

Most people think if they perform long enough, the promotion will come.

Unfortunately, it won’t. It’s a combination of all 3 working in tandem that makes you stand out from your peers.

I had to learn this in my career and hopefully it helps you too.

So how do you apply this model you ask?

When is that model tested the most?

When are career-defining, make-or-break moments decided?

Well the answer is almost always… in a presentation.

The strategy update.
The board review.
The quarterly results.
The big pitch.

That’s when your performance becomes visible.
That’s when your image is formed at scale.
That’s when exposure compounds - or stalls.

And yet, this is where most high performers lose leverage...

Let’s say you’ve spent weeks building the strategy.
You’ve pressure-tested the thinking in Claude.
The logic is tight. The insights are strong.

But now it’s 10pm the night before.

You’re rebuilding slides.
Fixing formatting.
Adjusting fonts.
Moving boxes around.

Instead of preparing for the room.
Instead of sharpening the narrative.
Instead of rehearsing for the questions that will actually determine the outcome.

That’s the trade-off you’re accepting:

Great AI for thinking.
Manual work for presenting.

What’s interesting is that gap doesn’t need to exist anymore.

Gamma now works directly inside Claude.

So the strategy you build in Claude can turn into a structured, beautifully designed presentation instantly - in the same flow of thinking.

No exporting.
No rebuilding.
No breaking context.
Your thinking evolves.

Your deck evolves with it.

Which means the night before the big presentation…

You’re not adjusting fonts.
You’re preparing to win the room.
Performance gets you in the room.
Exposure gets you promoted.

Make sure your next presentation is driving your career forward - not slowing it down.

#GammaPartner

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Jonathan Parsons

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The Battle

Adam Biddlecombe

Jonathan Parsons

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Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Adam Biddlecombe's LinkedIn Performance

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