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

Dr. Joerg Storm

Your success, my mission | CIO | CTO | Mercedes-Benz, (ex) Siemens | The only newsletter you need for Tech/AI🔔drstorm.substack.com🔔 Follow for posts about business & Tech/AI

I am 𝗗𝗿. 𝗝ö𝗿𝗴 𝗦𝘁𝗼𝗿𝗺, 𝗮𝘂𝘁𝗵𝗼𝗿 and 𝗳𝗼𝘂𝗻𝗱𝗲𝗿 𝗼𝗳 𝗼𝗻𝗲 𝗼𝗳 𝘁𝗵𝗲 𝘄𝗼𝗿𝗹𝗱’𝘀 𝗹𝗮𝗿𝗴𝗲𝘀𝘁 𝗔𝗜 𝗻𝗲𝘄𝘀𝗹𝗲𝘁𝘁𝗲𝗿𝘀, read by 𝟱70,𝟬𝟬𝟬+ 𝗹𝗲𝗮𝗱𝗲𝗿𝘀 𝗮𝗰𝗿𝗼𝘀𝘀 𝟭𝟵𝟳 𝗰𝗼𝘂𝗻𝘁𝗿𝗶𝗲𝘀, with a combined 𝟭.4𝗠+ 𝗳𝗼𝗹𝗹𝗼𝘄𝗲𝗿𝘀 𝗼𝗻 𝗟𝗶𝗻𝗸𝗲𝗱𝗜𝗻.

I run a 𝗲𝘅𝗲𝗰𝘂𝘁𝗶𝘃𝗲 𝗺𝗲𝗱𝗶𝗮 𝗮𝗻𝗱 𝗮𝗱𝘃𝗶𝘀𝗼𝗿𝘆 𝗽𝗹𝗮𝘁𝗳𝗼𝗿𝗺 spanning LinkedIn, a leading AI newsletter, and a C level podcast, reaching 𝗖𝗘𝗢𝘀, 𝗖𝗜𝗢𝘀, 𝗖𝗧𝗢𝘀, 𝗳𝗼𝘂𝗻𝗱𝗲𝗿𝘀, 𝗮𝗻𝗱 𝘀𝗲𝗻𝗶𝗼𝗿 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻 𝗺𝗮𝗸𝗲𝗿𝘀 worldwide.

My focus is helping leaders move from 𝗔𝗜 𝗲𝘅𝗽𝗲𝗿𝗶𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻 𝘁𝗼 𝗲𝘅𝗲𝗰𝘂𝘁𝗶𝗼𝗻, while building 𝗮𝘂𝘁𝗵𝗼𝗿𝗶𝘁𝘆, 𝘃𝗶𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝘆, 𝗮𝗻𝗱 𝗺𝗲𝗮𝘀𝘂𝗿𝗮𝗯𝗹𝗲 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗶𝗺𝗽𝗮𝗰𝘁.

What I do

𝟭. 𝗘𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲 𝗚𝗲𝗻𝗔𝗜 𝗮𝗻𝗱 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗔𝗜 𝗔𝗱𝘃𝗶𝘀𝗼𝗿𝘆
I advise enterprises and scale ups on 𝗔𝗜 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝘆, 𝘂𝘀𝗲 𝗰𝗮𝘀𝗲 𝗽𝗿𝗶𝗼𝗿𝗶𝘁𝗶𝘇𝗮𝘁𝗶𝗼𝗻, 𝗼𝗽𝗲𝗿𝗮𝘁𝗶𝗻𝗴 𝗺𝗼𝗱𝗲𝗹𝘀, 𝗴𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲, 𝗮𝗻𝗱 𝘀𝗰𝗮𝗹𝗲. The focus is execution, not theory.

𝟮. 𝗦𝗼𝗰𝗶𝗮𝗹 𝗠𝗲𝗱𝗶𝗮 𝗮𝗻𝗱 𝗟𝗶𝗻𝗸𝗲𝗱𝗜𝗻 𝗚𝗿𝗼𝘄𝘁𝗵
As Founder and CEO of 𝗗𝗿. 𝗦𝘁𝗼𝗿𝗺 𝗔𝗱𝘃𝗶𝘀𝗼𝗿𝘆 𝗚𝗺𝗯𝗛, my team runs global 𝗟𝗶𝗻𝗸𝗲𝗱𝗜𝗻 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝘆, 𝗰𝗼𝗻𝘁𝗲𝗻𝘁, 𝗮𝗱𝘀 𝗮𝗻𝗱 𝗮𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 end to end. We deliver 𝗴𝗿𝗼𝘄𝘁𝗵 from startups to 𝗙𝗼𝗿𝘁𝘂𝗻𝗲 𝟱𝟬𝟬 companies.

𝟯. 𝗘𝘅𝗲𝗰𝘂𝘁𝗶𝘃𝗲 𝗕𝗿𝗮𝗻𝗱𝗶𝗻𝗴 𝗮𝗻𝗱 𝗧𝗵𝗼𝘂𝗴𝗵𝘁 𝗟𝗲𝗮𝗱𝗲𝗿𝘀𝗵𝗶𝗽
We position leaders as 𝗰𝗿𝗲𝗱𝗶𝗯𝗹𝗲 𝘃𝗼𝗶𝗰𝗲𝘀 and convert visibility into 𝗰𝗼𝗺𝗺𝗲𝗿𝗰𝗶𝗮𝗹 𝗿𝗲𝗹𝗲𝘃𝗮𝗻𝗰𝗲 𝗮𝗻𝗱 𝗶𝗻𝗯𝗼𝘂𝗻𝗱 𝗱𝗲𝗺𝗮𝗻𝗱.

𝟰. 𝗣𝗼𝗱𝗰𝗮𝘀𝘁, 𝗞𝗲𝘆𝗻𝗼𝘁𝗲𝘀, 𝗮𝗻𝗱 𝗧𝗲𝗮𝗰𝗵𝗶𝗻𝗴
I host an 𝗲𝘅𝗲𝗰𝘂𝘁𝗶𝘃𝗲 𝗔𝗜 𝗽𝗼𝗱𝗰𝗮𝘀𝘁 with CEOs, CIOs, CTOs, and founders, and work globally as a 𝗸𝗲𝘆𝗻𝗼𝘁𝗲 𝘀𝗽𝗲𝗮𝗸𝗲𝗿, 𝗺𝗼𝗱𝗲𝗿𝗮𝘁𝗼𝗿, 𝗮𝗻𝗱 𝗱𝗼𝗰𝗲𝗻𝘁 for International Management.

Who we work with

Our clients include 𝗡𝗩𝗜𝗗𝗜𝗔, 𝗔𝗪𝗦, 𝗔𝗹𝗶𝗯𝗮𝗯𝗮, 𝗛𝘂𝗮𝘄𝗲𝗶, 𝗘𝗬, 𝗪ü𝗿𝘁𝗵, 𝗟𝘂𝗳𝘁𝗵𝗮𝗻𝘀𝗮, 𝗥𝗲𝗽𝗹𝗶𝘁, 𝗚𝗮𝗺𝗺𝗮, 𝗦𝘆𝗻𝘁𝗵𝗲𝘀𝗶𝗮, and leading AI driven enterprises worldwide.

If you want to 𝗳𝘂𝘁𝘂𝗿𝗲 𝗽𝗿𝗼𝗼𝗳 𝘆𝗼𝘂𝗿 𝗼𝗿𝗴𝗮𝗻𝗶𝘇𝗮𝘁𝗶𝗼𝗻, 𝘀𝗰𝗮𝗹𝗲 𝗔𝗜 𝗯𝗲𝘆𝗼𝗻𝗱 𝗽𝗶𝗹𝗼𝘁𝘀, or 𝗯𝘂𝗶𝗹𝗱 𝗲𝘅𝗲𝗰𝘂𝘁𝗶𝘃𝗲 𝗶𝗻𝗳𝗹𝘂𝗲𝗻𝗰𝗲, feel free to connect.

For collaborations and inquiries
digitalstormweekly@gmail.com

To book a conversation
https://topmate.io/dr_joerg_storm

Founder, Publisher

The "Digital STORM" weekly is one of the fastest-growing AI newsletter in the world, with thousand of readers working at companies like Apple, Meta, Google, Microsoft. 

Its all about AI, Future Trends, Digital Transformation for executives, decision makers, industry leaders and all others which want to grow

>> Would your AI team survive a chili test?

Most would fail.

In 2014 the Danish National Chamber Orchestra did something insane.

Before a performance every musician ate one of the hottest chili peppers in the world.

- Then they played.
- Eyes watering.
- Hands shaking.
-Breathing unstable.

But the music never stopped.

Why?

Because orchestras do not rely on comfort.
They rely on structure.

Watching that video made me think about the AI race happening right now.
- Everyone talks about models.
- Everyone debates tools.
- Very few talk about organizational resilience.

AI is doing to companies what that chili did to musicians.
- Pressure.
- Confusion.
- Uncertainty.

And suddenly teams that looked great in calm environments start falling apart.
- Projects stall.
- Coordination breaks.
- Leaders panic.

The real lesson from that orchestra is simple.

𝗣𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 𝘂𝗻𝗱𝗲𝗿 𝗽𝗿𝗲𝘀𝘀𝘂𝗿𝗲 𝗶𝘀 𝗻𝗼𝘁 𝘁𝗮𝗹𝗲𝗻𝘁.
𝗜𝘁 𝗶𝘀 𝗽𝗿𝗲𝗽𝗮𝗿𝗮𝘁𝗶𝗼𝗻.

The best AI organizations today have five things in place.
- 𝗖𝗹𝗲𝗮𝗿 𝗿𝗼𝗹𝗲𝘀
- 𝗦𝗵𝗮𝗿𝗲𝗱 𝗿𝗵𝘆𝘁𝗵𝗺
- 𝗠𝘂𝘀𝗰𝗹𝗲 𝗺𝗲𝗺𝗼𝗿𝘆
- 𝗧𝗿𝘂𝘀𝘁
- 𝗘𝗺𝗼𝘁𝗶𝗼𝗻𝗮𝗹 𝗰𝗼𝗻𝘁𝗿𝗼𝗹

When chaos hits they do not improvise.
They execute.

The AI wave will not reward the smartest teams.
It will reward the most coordinated ones.

So here is the real question.
If your organization had to eat the chili tomorrow

Would the music continue?
Or would everything collapse?

🎥: @clasicalmusicreel 

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>> How I built a working website in 10 minutes

Without a developer.

2 years ago this sounded ridiculous.
Launching a site meant weeks of work.

- Design.
- Frontend.
- Hosting.
- Deployment.

And if you were a solo founder, it was even worse.
You either learned everything yourself or paid thousands.

Then tools like Claude Code arrived.
And suddenly the entire workflow changed.

𝗖𝗹𝗮𝘂𝗱𝗲 𝗖𝗼𝗱𝗲 𝗱𝗼𝗲𝘀𝗻’𝘁 𝗷𝘂𝘀𝘁 𝗴𝗲𝗻𝗲𝗿𝗮𝘁𝗲 𝗰𝗼𝗱𝗲.
It builds the whole system.

It can:
- Build the full website
- Structure the pages
- Write the code
- Set up hosting
- Deploy it live

All from a clear prompt.
The real secret though is not the tool.

It is the brief.

If your brief is vague, the result is mediocre.
If your brief is precise, the result is shockingly good.

𝗧𝗵𝗲 𝗻𝗲𝘄 𝗳𝗼𝘂𝗻𝗱𝗲𝗿 𝘀𝗸𝗶𝗹𝗹 𝗶𝘀𝗻’𝘁 𝗰𝗼𝗱𝗶𝗻𝗴.

It is thinking clearly.
AI just executes.

Founders now move at the speed of their ideas.

The question is no longer “Can I build this?”
It is “How fast can I describe it?”

Have you built anything with Claude Code yet?

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🎧 𝗟𝗶𝘀𝘁𝗲𝗻 𝘁𝗼 𝘁𝗵𝗲 𝗳𝘂𝗹𝗹 𝗲𝗽𝗶𝘀𝗼𝗱𝗲 𝗵𝗲𝗿𝗲 

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>> Robots doing Kung Fu on live TV is not a gimmick.

It is a manufacturing readiness signal.

In this CCTV+ (Video News Agency) Gala clip you can see the jump from 2025 to 2026.

2025 was novelty.
2026 is 𝗯𝗮𝗹𝗮𝗻𝗰𝗲, 𝗳𝗮𝘂𝗹𝘁 𝗿𝗲𝗰𝗼𝘃𝗲𝗿𝘆, 𝗽𝗿𝗲𝗰𝗶𝘀𝗲 𝗮𝗰𝘁𝘂𝗮𝘁𝗶𝗼𝗻, and 𝗵𝘂𝗺𝗮𝗻 𝗶𝗻𝘁𝗲𝗿𝗮𝗰𝘁𝗶𝗼𝗻 with kids.

Drunken boxing and nunchaku are not “cute”.
They are stress tests for control under chaos.

The next frontier is not dancing.
It is 𝗰𝗼𝗺𝗺𝗲𝗿𝗰𝗶𝗮𝗹 𝗿𝗲𝗹𝗶𝗮𝗯𝗶𝗹𝗶𝘁𝘆 in messy environments.

By 2028, the winners will not be the best demos.
They will be the teams that nail:
• safe work next to humans
• rapid recovery from slips and collisions
• cheap serviceability and uptime

China is already pushing this at scale.

Reuters reports four major startups featured on the 2026 Gala, including Unitree, as part of a broader push into AI driven manufacturing. 

The IFR reports 4.28 million industrial robots operating in factories worldwide. 
McKinsey & Company’s framing is blunt: work becomes a partnership of people, agents, and robots. 

So the real jobs question is not “Will robots replace us”.
 It is “Which workflows get redesigned first, and who captures the value”.

𝗔𝗴𝗿𝗲𝗲 𝗼𝗿 𝗱𝗶𝘀𝗮𝗴𝗿𝗲𝗲: 𝗯𝘆 𝟮𝟬𝟮𝟴 𝗵𝘂𝗺𝗮𝗻𝗼𝗶𝗱𝘀 𝘄𝗶𝗹𝗹 𝗯𝗲 𝗮 𝗻𝗼𝗿𝗺𝗮𝗹 𝗰𝗼𝘀𝘁 𝗹𝗶𝗻𝗲 𝗶𝗻 𝗼𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝘀.

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