Dr. Joerg Storm

>> For years, we believed the loudest voice in the room would win.

AI just disrupted that myth.

The advantage is no longer about who speaks the most. It is about who executes the fastest.

And often, that is the quiet thinker with strong tools and clear focus.

With the right AI systems, one person can now research, write, analyze, prototype, and iterate at a speed that used to require entire teams.

-No waiting for consensus.
-No dependency on endless meetings.
-No bottleneck of approvals.

Technology has shifted leverage toward individuals who think deeply and move deliberately.

The future is not biased toward noise. It rewards clarity, speed, and applied learning.

If you are building your career in this new landscape, here is what matters:

● Learn how to use AI as a force multiplier
● Prioritize output over visibility
● Build skills independently of traditional hierarchies
● Move consistently instead of loudly
● Let tools handle repetition while you focus on thinking

In a world amplified by AI, will you compete for attention or compete for execution?

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🚀 Leverage AI, boost your career, and master the future with over 80+ AI bestseller eBooks.

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>> LinkedIn AI looks like private jets.

Real AI work looks more like the toilet seat.

One side is polished screenshots, overnight unicorns, and “10x productivity” claims.

The other side is what actually ships:

Messy data that needs cleaning before anything useful happens.

Prompts that fail for reasons nobody can explain at first.

Models that look brilliant in a demo and collapse in production.

APIs, latency, security, edge cases, evals, costs, and users doing the exact thing you never expected.


That’s the part social media rarely shows.

Real AI progress is not one magical prompt.

It is hundreds of boring decisions made well.

It is reading documentation when everyone else is posting predictions.

It is testing the same workflow again because the last version worked 92% of the time, and 92% is still not good enough.

The people building durable AI systems are usually less interested in looking impressive and more interested in making the system reliable.

AI is powerful.
But without strong engineering, clear thinking, and patience, it is just a very expensive demo.

What part of real AI work do you think LinkedIn hides the most?

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#ArtificialIntelligence #AIEngineering #SoftwareEngineering #AIAgents #TechLeadership

>> 𝗠𝘆𝘁𝗵: AI lets anyone build apps now.

𝗥𝗲𝗮𝗹𝗶𝘁𝘆: Apps were never the bottleneck.

Businesses were.

That’s what the 𝗩𝗶𝗯𝗲 𝗕𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗘𝗿𝗮 is actually about.

Not vibe coding.
Not typing faster.

It’s about turning decisions into execution
without hiring a team.

Atoms replaces entire business functions
from strategy to execution.

• Deep research before code
• Full-stack backend, not just UI
• Auth, database, payments included
• SEO built directly into the lifecycle

That’s why calling it a coding assistant misses the point.
It’s a multi-agent team.
Not autocomplete.
Developers skip boilerplate.
Founders skip hiring.

Anyone with an idea skips the complexity
of building a full-stack business from scratch.

Same system.

Different leverage.

The winners won’t be the best coders.
They’ll be the best decision-makers.

If you're building something real, see for yourself:

See how a business gets built end-to-end
👉 https://atoms.dev/

Agree — or still skeptical?

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>> Stop treating AI like a 𝗰𝗵𝗮𝘁𝗯𝗼𝘅.

The real shift is 𝘁𝗲𝗮𝗺𝘄𝗼𝗿𝗸.

That is why Bloome caught my attention.

Most people still use AI like a vending machine.

Prompt in. 
Answer out. 
Copy paste. 
Hope it is right.

That is not how real work happens.

Think about researching a new market. 
You start with a rough question. 
One agent comes back with the first read. 
Another disagrees with part of it. 
A third points out what no one had considered yet.

Real work needs challenge. 
Context. 
Review. 
Different perspectives. 
Someone to catch the missing piece.

Bloome is interesting because it turns agents into participants inside one shared conversation.

Your teammates can jump in at any point. 
The conversation already has the context. 
No one has to start over.

Humans stay in the room. 
Agents help move the work forward.

That matters for market research, campaign planning, contract review, PR review, and decision prep.

The big idea is simple:

AI should not just answer. 
It should 𝗰𝗼𝗹𝗹𝗮𝗯𝗼𝗿𝗮𝘁𝗲.

I think tools like Bloome show where work is heading.

Not more tabs. 
Not more isolated bots. 
Claude, ChatGPT, Deepseek. 
Even the agents you already rely on. 
All in the room. All working together. 
More shared intelligence.

https://lnkd.in/ecw9ai8M

Would you trust a team of agents more than one single AI answer?

#AI #AIAgents #FutureOfWork #Productivity #Leadership

>> Most people believe coding takes 𝗬𝗘𝗔𝗥𝗦 to learn.

They’re wrong.

And it’s quietly putting them 𝗕𝗘𝗛𝗜𝗡𝗗.

Because right now, the advantage isn’t coding.
It’s 𝗔𝗗𝗔𝗣𝗧𝗜𝗢𝗡.

Claude Code lets you build real projects in 𝗠𝗜𝗡𝗨𝗧𝗘𝗦
even if you’ve never written a single line.

- No courses.
- No waiting.
- No gatekeeping.

The shift is simple:

It’s not about technical expertise.
It’s about 𝗖𝗟𝗔𝗥𝗜𝗧𝗬.

When you define your context
and guide the AI with precision,
it stops guessing
and starts delivering 𝗔𝗖𝗖𝗨𝗥𝗔𝗧𝗘 results.

That’s when ideas turn into 𝗣𝗥𝗢𝗗𝗨𝗖𝗧𝗦.

In under 30 minutes.
-Landing Page
-Tools
Something you’ve been delaying for months.

𝗛𝗼𝘄 𝘁𝗼 𝘂𝘀𝗲 𝗖𝗹𝗮𝘂𝗱𝗲 𝗖𝗼𝗱𝗲 (𝟯𝟬 𝗺𝗶𝗻)
0–5 min
Install Claude Code. Sign in.

5–10 min
Create your 𝗰𝗼𝗻𝘁𝗲𝘅𝘁 folder
Add about-me.md
This is where 90% fail.
This is what makes everything work.

10–15 min
Start your first conversation
Use Opus 4.6+
Let it ask questions before building

15–20 min
Open live preview
Be specific. Adjust in real time

20–30 min
Give it a real project
Not a test. Something that matters
Pro tip:
Use “Bypass permissions”
and let it execute without friction

Here’s what’s really happening:

𝗔𝗜 is redefining who can build
𝗖𝗼𝗻𝘁𝗲𝘅𝘁 drives quality
𝗖𝗹𝗮𝗿𝗶𝘁𝘆 beats complexity
𝗦𝗽𝗲𝗲𝗱 comes from collaboration
𝗘𝘅𝗲𝗰𝘂𝘁𝗶𝗼𝗻 beats intention

The barrier is gone.
Only one thing matters now:

What would you create
if you had 30 minutes right now?

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>> 5 campaigns. 29 countries. $2.5M in ad spend.

The same team now runs 60 campaigns.

They didn’t hire more people.
They gave an AI employee ownership.

That’s the shift most companies still underestimate.
I run global IT infrastructure and advise executives on AI strategy.

Every week, I see products promising to transform the enterprise.

Most fail for the same reason.
They demo well.
They govern badly.

Enterprise AI is not about flashy demos.
It’s about permissions.

Auditability.
Human approval.
Security.
Accountability.

That’s why viktor.com caught my attention.

Every action is permission-based.
Every decision requires human sign-off.

Every step leaves a complete audit trail.
That’s what enterprise IT actually wants to see.

It’s also why more than 40,000 workspaces already use him.
Before recommending it, I tested it on my own workflow.

I asked Viktor to prepare an infrastructure review.
He summarized incidents, updated the capacity forecast, framed the key decisions with options and business impact, and prepared everything before the meeting.

I reviewed every detail.
It was accurate.

The biggest AI question for CIOs in 2026 isn’t:
“Which model should we buy?”

It’s:
“Which jobs are we ready to let an AI employee own, under the right governance?”

That’s the conversation every leadership team should be having.

If you’re curious how this works in practice, the carousel walks through real customer examples.

Hire viktor.com for your team.

$100 in credits included. No credit card required.

Full link in the first comment.

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>> Most people think 𝗔𝗜 mastery requires

𝗲𝘅𝗽𝗲𝗻𝘀𝗶𝘃𝗲 certifications.

That belief is quietly killing your 𝗲𝗱𝗴𝗲.
And almost no one questions it.

I see this everywhere.

Professionals waiting.
Overthinking.
Assuming they need permission to start.

Meanwhile, the people pulling ahead?
They’re learning directly from the source.

Claude just released 13 official AI courses.
- Completely free.
- No paywall
- No gatekeeping.

From fundamentals to API-level building.

And yet most people will ignore this.

Because it doesn’t “feel premium.”

Here’s the reality:
𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 ≠ 𝗰𝗮𝗽𝗮𝗯𝗶𝗹𝗶𝘁𝘆
𝗔𝗰𝘁𝗶𝗼𝗻 = 𝗮𝗱𝘃𝗮𝗻𝘁𝗮𝗴𝗲

The real gap isn’t access.
It’s execution.

Courses give you structure.
But skill comes from applying what you learn.

That’s where most people stop.
They collect knowledge.

But never build leverage.

Here are all 13 official courses:

1 - Claude 101. Learn Claude for everyday work.
↳ https://lnkd.in/dAse8ArY

2 - AI Fluency: Frameworks & Foundations.
↳ https://lnkd.in/d7ktg4Ps

3 - Introduction to Agent Skills.
↳ https://lnkd.in/dhdBUBFk

4 - Building with the Claude API.
↳ https://lnkd.in/dmCYDPuc

5 - Claude Code in Action.
↳ https://lnkd.in/dZPWzB84

6 - Intro to Model Context Protocol.
↳ https://lnkd.in/dNQqwt3S

7 - MCP: Advanced Topics.
↳ https://lnkd.in/dCZgkfcv

8 - AI Fluency for Students.
↳ https://lnkd.in/dNeYdXGU

9 - AI Fluency for Educators.
↳ https://lnkd.in/dnU_ESjp

10 - Teaching AI Fluency.
↳ https://lnkd.in/dpbtsg5n

11 - AI Fluency for Nonprofits.
↳ https://lnkd.in/dTRcU8Mw

12 - Claude with Amazon Bedrock.
↳ https://lnkd.in/dyKDbucn

13 - Claude with Google Cloud's Vertex AI.
↳ https://lnkd.in/dphyes2f

The takeaway:
• Free opportunities often deliver the highest ROI
• Theory builds understanding; practice builds mastery
• AI fluency is becoming a non-negotiable skill
• Early adopters gain a lasting competitive edge
• Continuous learning is the new career insurance

Which of these courses will you start with today?

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>> 𝗜 𝘀𝗮𝘃𝗲𝗱 $𝟭𝟱,𝟬𝟬𝟬 𝘄𝗶𝘁𝗵 𝗼𝗻𝗲 𝗺𝗲𝘀𝘀𝗮𝗴𝗲.

No consultant. No agency. No workshop.

I opened Pancake and typed:
"Website proposal in bullet points."

That's it.

A few seconds later it gave me:
• Why I need a website beyond LinkedIn and Substack
• A complete site structure
• An SEO strategy
• A sponsor acquisition funnel
• A monetization plan
• A domain recommendation
• A launch cost estimate
• A projected payback model

What surprised me wasn't the speed.
It was the thinking.

Instead of focusing on pages and design...
It focused on business outcomes.

Own your audience.
Own your SEO.
Own your brand.

Stop renting your future on platforms you don't control.
That's exactly the kind of advice you'd expect from a strategist charging thousands of dollars.

The AI didn't just answer the question.
It challenged the assumption behind it.

And that's why tools like Pancake are getting my attention.
They're starting to feel less like software...

And more like having an experienced operator sitting next to you.

𝗤𝘂𝗲𝘀𝘁𝗶𝗼𝗻:
Would you rather hire a $15,000 consultant...
Or start with an AI that gives you a strategy in seconds?

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#AI #AIAgents #Entrepreneurship #FutureOfWork #Business

>> Most people are using 𝗖𝗹𝗮𝘂𝗱𝗲 wrong.

And they don't even know it.

They're paying for a Ferrari.
Then driving it in a parking lot.

Most users do this:

-Open Claude.
-Ask one question.
-Get one answer.
-Close the tab.

Then complain that AI is 𝗼𝘃𝗲𝗿𝗵𝘆𝗽𝗲𝗱.

The problem isn't Claude.
The problem is the setup.

90% of Claude's power is hidden beneath the surface.

The users getting extraordinary results aren't writing better prompts.
They're building better systems.

Here are 8 features that completely change the game:

𝗖𝗟𝗔𝗨𝗗𝗘.𝗺𝗱
Your business memory file.
Claude remembers your rules, voice, and preferences.
🔗 https://lnkd.in/gJmJFsai

𝗦𝗸𝗶𝗹𝗹𝘀
Train once. Reuse forever.
🔗 https://lnkd.in/g98fY6C3

𝗠𝗖𝗣
Connect Claude to your CRM, email, calendar, and Slack.
🔗 https://lnkd.in/gEWMqzMe

𝗣𝗹𝘂𝗴𝗶𝗻𝘀
The app store for Claude.
🔗 https://lnkd.in/gn7MU53c

𝗣𝗹𝗮𝗻 𝗠𝗼𝗱𝗲
Approve the strategy before execution.
🔗 https://lnkd.in/gFDsMT7k

𝗦𝗹𝗮𝘀𝗵 𝗖𝗼𝗺𝗺𝗮𝗻𝗱𝘀
Automate repetitive work.
🔗 https://lnkd.in/gfsXYxFA

𝗖𝗵𝗲𝗰𝗸𝗽𝗼𝗶𝗻𝘁𝘀
Roll back mistakes instantly.
🔗 https://lnkd.in/geUJ5v3E

𝗦𝘂𝗯𝗮𝗴𝗲𝗻𝘁𝘀
Run multiple workflows simultaneously.
🔗 https://lnkd.in/g9Xp2Skv
The biggest unlock?

𝗖𝗟𝗔𝗨𝗗𝗘.𝗺𝗱.
Five minutes of setup can save hundreds of hours of prompting.
Same tool.
Same subscription.
Completely different outcome.
The AI gap isn't model quality anymore.
It's user sophistication.

𝗔𝗴𝗿𝗲𝗲 𝗼𝗿 𝗱𝗶𝘀𝗮𝗴𝗿𝗲𝗲:
The people getting the biggest AI results are not using better AI.
They're using better systems.

Comment 𝗦𝗬𝗦𝗧𝗘𝗠 and I'll send the setup guide.

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>> The AI gap isn’t about intelligence anymore.

It’s about access.

For years, elite AI knowledge felt locked behind top universities and billion-dollar companies.

-Expensive courses.
-Exclusive labs.
-Closed ecosystems.

That excuse just disappeared.

NVIDIA just dropped 11 (free) guides:
1. Generative AI Explained
A simple intro to how gen AI works. No coding required.

2. Building A Brain in 10 Minutes
Learn how neural networks think in under 10 min.

3. AI for All: From Basics to GenAI Practice
From machine learning basics to creative AI tools.

4. Getting Started with AI on Jetson Nano
Build your first neural network with hands-on notebooks.

5. Introduction to AI in the Data Center
Learn GPU architecture and AI deployment basics.

6. An Even Easier Introduction to CUDA
Start parallel programming on GPUs. Beginner-friendly.

7. Introduction to NVIDIA NIM Microservices
Build, deploy, and scale AI models the simple way.

8. Generative AI in Digital Health
Build AI chatbots for healthcare and clinical notes.

9. AI Weather Models with NVIDIA Earth-2
Explore AI for weather prediction and climate apps.

10. Accelerated Computing with CUDA C/C++
GPU computing fundamentals. Start with vector addition.

11. Generative AI with NeMo
Customize text and multimodal AI models easily.

Access them here: https://lnkd.in/dpHb_iE6

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🎧 𝗟𝗶𝘀𝘁𝗲𝗻 𝘁𝗼 𝘁𝗵𝗲 𝗳𝘂𝗹𝗹 𝗲𝗽𝗶𝘀𝗼𝗱𝗲 𝗵𝗲𝗿𝗲

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>> Everyone wants to be an AI first company.

Almost nobody wants to be a data first company.

That is the problem.
Right now the trend on LinkedIn is clear.

- Agents.
- MCP servers.
- A2A workflows.
- AI copilots everywhere.

Every boardroom wants the headline.
𝗪𝗲 𝗮𝗿𝗲 𝗔𝗜 𝗳𝗶𝗿𝘀𝘁.

But under the surface, most organizations are missing the boring layers that actually make AI work.
• messy data
• no ownership
• fragmented systems
• teams with zero AI literacy

So the company builds shiny demos.
They look incredible in presentations.

Then production happens.
And suddenly the agents hallucinate, the workflows break, and nobody trusts the system.

𝗔𝗜 𝗱𝗶𝗱𝗻’𝘁 𝗳𝗮𝗶𝗹.
𝗧𝗵𝗲 𝗳𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻 𝗻𝗲𝘃𝗲𝗿 𝗲𝘅𝗶𝘀𝘁𝗲𝗱.

The uncomfortable truth most executives ignore:

AI is the roof.
Data is the foundation.

And buildings don’t collapse from the roof.
They collapse from the bottom.

𝗙𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻𝘀 𝗮𝗿𝗲𝗻’𝘁 𝘀𝗲𝘅𝘆.

But they decide who survives the AI era.

Agree or disagree?

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>> Most AI projects do not fail because of AI.

They fail because of 𝗰𝗼𝗻𝘁𝗲𝘅𝘁.

That is my view.

Everyone is racing to add agents into operations.
But a smarter model does not magically understand how your business runs.

I once saw an AI analysis blame a slow approval team for a process delay.
It sounded logical.
It was confident.
It was wrong.

The real issue was missing customer documentation upstream.
That is the danger of AI without the right context.

It can find patterns.
But it may miss reality.

My recommendation is simple:

Do not start with:
What can we automate?

Start with:
Does the AI understand how work actually flows?

This is why I like the Celonis Context Model.

It gives Enterprise AI the operational 𝗰𝗼𝗻𝘁𝗲𝘅𝘁 it needs to succeed through a dynamic, real-time digital twin of operations.

People, agents, and systems can then reason correctly, decide sensibly, and act reliably.
 
AI needs context.
Celonis provides it.
 
See the Context Matters homepage here:
https://lnkd.in/ecxrmEfv
 
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>> 𝗧𝗵𝗲 𝗯𝗶𝗴𝗴𝗲𝘀𝘁 career mistake right now?

Learning tools instead of 𝗷𝘂𝗱𝗴𝗺𝗲𝗻𝘁.

Everyone is racing to master the next AI tool.
-ChatGPT.
-Claude.
-Copilot.
-Agents.
-Automation.

Useful?
Yes.

Enough?
No.

The World Economic Forum data points to something many people still ignore:
By 2030, the most valuable skills will not be purely technical.
They will be strategic.

That means the real winners will not just know how to use AI.
They will know what to do with it.

The skills that matter most:
- Systems thinking
- Creative thinking
- Analytical thinking
- Self awareness
- Leadership and influence
- Resilience and adaptability
- Curiosity and lifelong learning

Look at that list carefully.
These are not skills you download.

These are not skills you learn from a tool tutorial.
These are the skills that decide whether AI makes you 10x more valuable or easier to replace.

Because AI can give you answers.
But it cannot decide which problem matters.

AI can create options.
But it cannot take responsibility.

AI can accelerate execution.
But it cannot replace courage, judgment, and leadership.

The next decade will punish people who only collect tools.
And reward people who build strategic depth.

My take:
Technical skills get you into the game.
Strategic skills keep you relevant.

Agree or disagree?
Which skill will matter most by 2030?

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>> Harvard level AI tuition that would cost more than 5,000 dollars

is now free.

And it is right here 👇

Harvard University has opened up a mini executive curriculum on generative AI and prompt engineering – no paywall, no signup, just world class lectures.

After two decades in AI strategy, data governance, and digital transformation across legal tech, public service, and regulated industries, here is the blunt truth

𝗣𝗿𝗼𝗺𝗽𝘁𝗶𝗻𝗴 𝗶𝘀 𝘁𝗵𝗲 𝗻𝗲𝘄 𝗲𝘅𝗲𝗰𝘂𝘁𝗶𝘃𝗲 𝗹𝗶𝘁𝗲𝗿𝗮𝗰𝘆.

Most leaders still treat it like a toy. The people who master it treat it like leverage.

If you want serious AI fluency for yourself or your team, start here.

𝗛𝗔𝗥𝗩𝗔𝗥𝗗 𝗟𝗘𝗖𝗧𝗨𝗥𝗘𝗦
1️⃣ Introduction to Generative AI: How GenAI actually works, step by step.
🔗  https://lnkd.in/d_pytxug

2️⃣ Generative AI in Teaching and Learning: How educators can adapt and lead.
🔗 https://lnkd.in/djaBCgUU

3️⃣ Beyond Chatbots System Prompts, RAG: From simple chats to scalable AI systems.
🔗  https://lnkd.in/dcAS-8xM

4️⃣ Prompt Engineering: Practical ways to improve any LLM output.
🔗  https://lnkd.in/dYPZb3sK

5️⃣ The Basics of Generative AI: No jargon, just clarity.
🔗  https://lnkd.in/dAdz2jBd

6️⃣ Teaching with AI in the Classroom: Frameworks for trainers and educators.
🔗  https://lnkd.in/dqTM9eZ5


𝗗𝗘𝗘𝗣 𝗗𝗜𝗩𝗘
🟩 LLMs and the end of programming: Why prompting is the new coding
🔗 https://lnkd.in/dEkThehn

🟩 CS50 extension – AI and prompt engineering: Design prompts that think with you
🔗 https://lnkd.in/d7jg8cZ7

🟩 CS50x 2025 – Artificial Intelligence lecture: LLMs, neural nets, real world use cases
🔗 https://lnkd.in/dpaGfcdE

🟩 GPT 4 how it works and how to build with it: Behind the curtain on GPT 4
🔗 https://lnkd.in/dhf4zjtW

𝗞𝗲𝘆 𝗽𝗼𝗶𝗻𝘁𝘀
✅ Ivy League prompting knowledge, zero tuition
✅ Great prompting is not a trick, it is an executive skill
✅ Two lectures will put you ahead of most leaders in your org

Which lecture will you start with first?
Tell me in the comments.

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>> Most people spend months using Claude…

and still use it like a smarter Google search bar.

That’s the biggest mistake.

The people getting insane results from Claude are not asking better questions.

They’re building better systems.

The real shift happens when you stop writing random prompts and start creating workflows.

Prompt stacks, Projects, Artifacts, reusable frameworks, role-based prompting, context layering.

That’s where Claude becomes powerful.

In just 7 focused days, you can completely change how you work with AI.

From content creation and research to strategy, coding, brainstorming, and business workflows, Claude can become your second brain if you learn how to structure your thinking properly.

Most beginners fail because they:

• Use vague prompts
• Ask everything in one message
• Never iterate outputs
• Ignore context and formatting
• Don’t build reusable systems

The fastest way to improve:

• Save your best prompts
• Create repeatable workflows
• Use Projects for memory and consistency
• Think in systems, not chats
• Refine outputs instead of accepting the first response

Are people really “bad at AI”… or have they just never learned how to use it
properly?

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>> 𝗧𝗵𝗲 𝗺𝗼𝘀𝘁 𝗲𝘅𝗽𝗲𝗻𝘀𝗶𝘃𝗲 𝗔𝗜 𝗮𝗴𝗲𝗻𝘁 𝗶𝘀 𝘁𝗵𝗲 𝗼𝗻𝗲 𝘁𝗵𝗮𝘁 𝗮𝗹𝗺𝗼𝘀𝘁 𝗳𝗶𝗻𝗶𝘀𝗵𝗲𝘀.

It reasons brilliantly.
Then it hits a PDF and the workflow dies.

Most AI st mile of business is not a chatbot.
It is a contract.
A form.
A signature.
A regulated workflow.

Data that must land correctly in an existing system.
That is why the next enterprise AI winners will not be defined by smarter models alone.

They will be defined by completion infrastructure.

Anvil’s new AI Pack gives technical teams programmatic access to Document AI, including AI Schema Mapping.

Teams can provide their existing field schema.
When Anvil detects fields in a new PDF, its AI maps them directly to the names, aliases, and data types the business already uses.

No manually remapping every document.
Fewer broken downstream integrations.
Far less engineering work when onboarding new document types.

Because an agent that only recommends is an assistant.
An agent that can transform paperwork into structured, workflow-ready data and complete the process creates real business value.

The AI race is moving from intelligence to execution.

Check it out here: https://lnkd.in/ev9g3x3t

Where do your AI workflows still break:
Reasoning, data, or the last mile?

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#AI #EnterpriseAI #Automation #AnvilPartner

>> 98 AI courses. $0.

From Harvard, MIT, NVIDIA, Google and more.

Your AI curriculum is already online.

Most people still think getting good at AI means buying another $2,000 course.

It doesn’t.

I pulled together 98 free learning resources from OpenAI, Anthropic, Google, Microsoft, Harvard, MIT, NVIDIA and leading university lectures.


📌 Get all 98 Links to the courses in my free newsletter: https://lnkd.in/eFNvmcYa


And this isn’t just “AI for beginners.”
The list covers prompt engineering, reasoning, RAG, Claude and ChatGPT workflows, AI agents, APIs, machine learning, deep learning, CUDA, transformers and responsible AI.

OpenAI Academy is actively expanding its practical learning library, Google still offers hands-on ML training, and NVIDIA says many of its self-paced courses are free.

Here 9️⃣ from Nvidia:

1️⃣ Agentic AI Explained: https://lnkd.in/eFBiM5aY

2️⃣ AI for All: From Basics to GenAI Practice: https://lnkd.in/eNjPi3gs

3️⃣ AI Infrastructure and Operations Fundamentals: https://lnkd.in/eNjPi3gs

4️⃣ Augment your LLM Using Retrieval Augmented Generation: https://lnkd.in/eCaBEsPS

5️⃣ Building A Brain in 10 Minutes: https://lnkd.in/etnQwFRA

6️⃣ Fundamentals of Accelerated Computing with CUDA C/C++: https://lnkd.in/eDdHXy9W

7️⃣ Generative AI Explained: https://lnkd.in/ewdNQN5h

8️⃣ Getting Started with AI on Jetson Nano: https://lnkd.in/eXt8nmZu

9️⃣ Introduction to Transformer-Based Natural Language Processing: https://lnkd.in/etP3ErYx

The bigger point is simple: access to high-quality AI education is no longer the bottleneck.
Execution is.

Pick one track.
Spend 30 minutes a day.
Build something with what you learn.

A year from now, that habit will matter far more than collecting another certificate.

Which AI skill would you learn first if the best material already cost you nothing?

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#AI #ArtificialIntelligence #GenerativeAI #FutureOfWork #Learning

>> 𝗔𝗜 𝗷𝘂𝘀𝘁 𝗯𝗿𝗼𝗸𝗲 𝗼𝘂𝘁 𝗼𝗳 𝘁𝗵𝗲 𝗳𝗲𝗲𝗱.

For years, content stayed where it belonged.

Inside the screen.
Not anymore.

This Chinese AI dragon literally climbs out of my LinkedIn post, breathes fire... and tells you to subscribe.(thx to Tim Gray)

It looks like entertainment.
It isn't.

It's a preview of what's coming.
Soon, AI-generated content won't just be something you watch.

It will react to you.
Talk to you.
Persuade you.
Sell to you.
Work with you.

The line between content, software, and intelligent agents is disappearing faster than most people realize.

The creators and companies that understand this shift today won't just win more attention.
They'll define how billions of people interact with AI tomorrow.

If you want to stay ahead of what's coming next...
Subscribe to my free AI newsletter, read every week by 600,000+ professionals from NVIDIA, Microsoft, AWS, Mercedes-Benz,...

It's 100% free - subscribe here: 👇
🔗 https://lnkd.in/eFNvmcYa

The future of AI won't happen in five years.
It's already appearing in your feed.

Question: What replaces today's social media feed first?

AI agents that interact with us... or AI creators that outperform humans?

p.s. this great video was done by Tim Gray from Breakout Clips!
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>> The better Claude gets, the worse your prompts may work.

Your 20-step masterpiece may be the problem.

Stop prompting. Start delegating.

For two years, we trained ourselves to write longer prompts: roles, numbered steps, exact sequences, endless guardrails.

That made sense when the model needed us to manage the process.

But Claude Fable 5 changes the dynamic. Prescribe every step and you freeze your assumptions into the task. If one is wrong, the model still follows it. Give it the destination and constraints instead, and it can plan the route itself.

A better brief is simple:

- Context.
- Current state.
- Constraints.
- Goal.

Then let the model decide how to get there.

That is the shift: stop acting like the GPS. Start acting like the client.

Frontier AI earns its price on thinking, synthesis and judgment, not producing more words.

I turned the full system into a 21-page practical guide with the briefing template, effort settings, model routing, verification prompts and agentic workflows.

I’m giving it away free in my newsletter. Subscribe and you can download the full guide there.

🔗 https://lnkd.in/eFNvmcYa

What are you still over-specifying that AI should be deciding for itself?

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#AI #Claude #PromptEngineering #ArtificialIntelligence #FutureOfWork

The average knowledge worker spends far too much time creating presentations.

Not because the content is difficult.

Because formatting, structuring, and polishing slides consume hours that could be spent on higher value work.

That’s why tools like Templafy are interesting.

Their new Free Experience allows anyone to generate enterprise quality PowerPoint presentations from a simple prompt.

Describe what you need.

The AI creates a complete presentation that can be downloaded as a fully editable PowerPoint file.

What makes this noteworthy is that Templafy is not new to enterprise environments.

The platform is already trusted by millions of professionals worldwide and used across marketing, sales, and other document intensive functions.

Now those capabilities are available to everyone at no cost.

If you’re creating executive presentations, board updates, sales decks, or customer proposals, it’s worth testing.

Try it here:

https://lnkd.in/eRzdJ8FY

Will AI eliminate presentation creation as a skill, or simply make great communicators even more effective?

#AI #DigitalTransformation #Leadership #FutureOfWork #PowerPoint

>> Most people use Claude 𝗪𝗥𝗢𝗡𝗚.

They treat it like Google.

That is why they get average answers.

The real power of AI is not the model.
It is the quality of the prompt.

After thousands of prompts, one thing became obvious:
The best AI users think differently.

They do not just “ask questions.”
- They structure context.
- Control outputs.
- Challenge responses.
- Build systems.

That is the difference between casual users and people getting 10x leverage from AI.

So I put together the 20 prompting laws used by AI power users 👇

Before the prompt

Most people skip this completely.

The best users:
✔ Give context
✔ Add constraints
✔ Use real data
✔ Define the outcome clearly

Garbage input = average output.


Structure the output

This changes everything.

Instead of:
“Help me with marketing”

Try:
“Act as a SaaS CMO. Create a 30 day GTM plan in table format.”

Specificity changes output quality dramatically.
🔁 Refine the response

Most people stop after the first answer.
Big mistake.

The best users:
✔ Challenge the AI
✔ Ask for trade offs
✔ Request pushback
✔ Iterate step by step

The first response is usually just the draft.
Think in systems

This is where advanced users separate themselves.

AI is no longer a tool.
It is becoming infrastructure.

The future belongs to people who can design workflows, not just prompts.

💾 Save this cheat sheet.

You will use it more than you think.
Which prompting law do most people still ignore?
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#AI #Claude #ArtificialIntelligence #Productivity #Tech

The AI story worth covering this year is not a model release. It is a payroll line that did not move while output did.

I publish and edit for an audience of around 1.5 million professionals, which means I read a lot of AI announcements and very few survive a second look.

Most of what crosses my desk is capability. A benchmark, a parameter count, a demo of something impressive that nobody has put near a real business. Genuinely interesting, and it changes almost nothing on a P&L.

The stories that hold up are the boring ones. A job that had no owner now has one, and the result shows up somewhere an accountant would recognise.

Nico Torres, founder of Authority Makers, is a clean example. Outbound and lead generation were never a strategy problem for his agency, they were an execution capacity problem.

He gave that job to an AI employee and added $133,752 in new annual recurring revenue in the first thirty days. No new hires. No new service line.

The mechanism is worth being precise about. Viktor works inside Slack, reaches around 3,000 tools through a single connection, and runs a whole job rather than answering a prompt.

Output arrives as a proposal and a person approves it before it ships, which is the difference between automation and delegation.

The take: we have spent two years measuring AI by what it knows. The measurement that will matter is what it owns.

Get started free at viktor.com. $100 in credits included, no card.

viktor.com

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>> How AI Is Reinventing Enterprise Software

with CEO Thoughtworks Mike Sutcliff
 
Enterprise software is no longer just being upgraded.
It is being fundamentally reinvented.

In this episode of DIGITAL STORM weekly, we sat down with Mike Sutcliff, CEO of Thoughtworks, to discuss how AI/worksᵀᴹ is reshaping the software development lifecycle through reverse engineering, spec enrichment, autonomous agents, and AI-native architectures.

This conversation goes far beyond coding assistants and automation.

It explores how AI is changing the economics of software itself; from build and maintenance to modernization and enterprise operations.

Some key insights from Mike:

• Traditional software maintenance models are economically broken
• AI-native software lifecycles can dramatically reduce technical debt
• Reverse engineering + spec enrichment + spec-to-code changes modernization entirely
• AI agents can accelerate enterprise software transformation at unprecedented speed
• Maintenance contracts may eventually disappear through self-evolving systems
• Enterprise AI success depends on architecture, governance, and engineering discipline
• Agentic systems are powerful but still highly immature and risky without controls
• The future of enterprise technology is continuous evolution, not periodic replacement

What makes Mike’s perspective valuable?

He has led digital transformation at global scale across Accenture Digital, AI startups, and now Thoughtworks; one of the leading companies that helped shape modern agile software engineering itself.

If you are am executive, founder, or enterprise operator trying to understand where enterprise AI is actually heading, this episode is worth your time.

---
🎧 𝗟𝗶𝘀𝘁𝗲𝗻 𝘁𝗼 𝘁𝗵𝗲 𝗳𝘂𝗹𝗹 𝗲𝗽𝗶𝘀𝗼𝗱𝗲 𝗵𝗲𝗿𝗲

🔗 YouTube: https://lnkd.in/dhHsyqBT 
🔗 Amazon Music: https://lnkd.in/dZWYrqJ5 
🔗 Apple Podcasts: https://lnkd.in/dxmppqnj 
🔗 Spotify: https://lnkd.in/dcd4V8gJ 
🔗 RSS: https://lnkd.in/dE-k7nJE

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>> Top Free AI Courses You Shouldn't Miss

AI skills are the new career currency.

Ready to cash in without spending a dime?

>>>> In a world where tech is evolving faster than job titles, keeping up isn’t optional — it’s essential.

Here are 9 free AI courses that can seriously level up your game:

1. Applications of AI by Great Learning

https://drp.li/9Akbb

2. Introduction to Generative AI by Google

https://lnkd.in/extyHBZk

3. Prompt Engineering for ChatGPT by Vanderbilt University

https://lnkd.in/ehFAiUw7

4. Generative AI For Everyone by DeepLearning AI

https://lnkd.in/eqiWKnyT

5. Generative AI with Large Language Models by Amazon AWS & Deep Learning AI

https://lnkd.in/dSNEtsDz

6. Google AI Essentials by Google

https://lnkd.in/ei3S_ZsU

7. Elements of AI by University of Helsinki & MinnaLearn

https://lnkd.in/eCNvUHtM

8. Artificial Intelligence by MIT OpenCourseWare

https://lnkd.in/eBwQcchv

9. CS50’s Introduction to AI with Python by Harvard University

https://drp.li/dPwh5

Whether you're just starting out or deep into your AI journey — there's something here for everyone.

Which course are you signing up for first? Drop it below

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🎧 𝗟𝗶𝘀𝘁𝗲𝗻 𝘁𝗼 𝘁𝗵𝗲 𝗳𝘂𝗹𝗹 𝗲𝗽𝗶𝘀𝗼𝗱𝗲 𝗵𝗲𝗿𝗲

🔗 YouTube: https://lnkd.in/eGJPiQ4y 
🔗 Amazon Music: https://lnkd.in/daTPRypn
🔗 Apple Podcasts: https://lnkd.in/dphbS89P
🔗 Spotify: https://lnkd.in/dQ9gjG2E
🔗 RSS: https://lnkd.in/d4tCXB7n

>> Most AI content fails for one reason.

𝗜𝘁 𝘀𝘁𝗶𝗹𝗹 𝘀𝗼𝘂𝗻𝗱𝘀 𝗳𝗮𝗸𝗲.

Not because the model is bad.
Because the workflow is.

Most people do this:
- Generate
- Copy
- Post

Then wonder why nobody engages.

Top creators do something completely different.
They train the model how to write.

The real advantage is not prompting.

It is:
- Training memory
- Auditing outputs
- Removing AI patterns
- Rewriting weak phrasing
- Testing in fresh chats

That is why some AI content feels robotic instantly.

- Too polished.
- Too generic.
- Zero tension.
- No personality.

The creators winning with AI right now are not generating faster.
They are refining harder.

That is the shift most people still miss.

AI writing in 2026 is no longer about generation.
It is about 𝗿𝗲𝗳𝗶𝗻𝗲𝗺𝗲𝗻𝘁.

Agree or do you think prompts alone are enough?

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#ArtificialIntelligence #AIWriting #ContentMarketing #LinkedInGrowth #PersonalBranding

>> 𝗠𝗼𝘀𝘁 𝗽𝗲𝗼𝗽𝗹𝗲 𝗳𝗮𝗶𝗹 𝘄𝗶𝘁𝗵 𝗔𝗜

𝗔𝗻𝗱 𝗶𝘁’𝘀 𝗻𝗼𝘁 𝗯𝗲𝗰𝗮𝘂𝘀𝗲 𝗼𝗳 𝘁𝗵𝗲 𝘁𝗼𝗼𝗹𝘀

The shocking truth?

Mastering AI isn’t about shortcuts,it’s about building a foundation first.
AI isn’t magic; it’s a skill that grows step by step.

Start with chatbots, understand prompts, and explore practical applications.

Then move on to automation with agents, connecting apps, and building workflows that save real time.

Finally, tackle agentic AI, memory, multi-step reasoning, and collaborative pipelines for complex problem solving.

Rushing to advanced tools without context wastes energy and limits results.

A structured, hands-on roadmap ensures each skill builds on the last, turning curiosity into real-world impact.

Practical reminders to master AI:
● Start simple, build progressively
● Explore use cases, don’t just watch tutorials
● Automate workflows before creating complex agents
● Focus on real-world problem solving

Are you building your AI skills the right way, or jumping straight to advanced tools and hoping for results?

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🎧 𝗟𝗶𝘀𝘁𝗲𝗻 𝘁𝗼 𝘁𝗵𝗲 𝗳𝘂𝗹𝗹 𝗲𝗽𝗶𝘀𝗼𝗱𝗲 𝗵𝗲𝗿𝗲

🔗 YouTube: https://lnkd.in/eGJPiQ4y 
🔗 Amazon Music: https://lnkd.in/daTPRypn
🔗 Apple Podcasts: https://lnkd.in/dphbS89P
🔗 Spotify: https://lnkd.in/dQ9gjG2E
🔗 RSS: https://lnkd.in/d4tCXB7n

🚀 Leverage AI, boost your career, and master the future with over 80+ AI bestseller eBooks.

🔗 Get your eBooks here: https://lnkd.in/emSWFxrN

#ai #automation #productivity #learning #technology

>> Imagine an AI application with one BILLION users.

>> It's happening right now with @Alipay

This isn't just an app update, because payment integration is the final hurdle for AI Agents to execute real-world tasks.

This migration transforms Alipay into a developer distribution platform that will set the standard for the rest of the world.

Source:  https://lnkd.in/eE-BeFBF

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>> 𝗛𝗼𝘄 𝗜 𝗺𝗮𝗱𝗲 𝗖𝗹𝗮𝘂𝗱𝗲 𝟭𝟬𝘅 𝗺𝗼𝗿𝗲 𝘂𝘀𝗲𝗳𝘂𝗹

𝗪𝗶𝘁𝗵𝗼𝘂𝘁 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗽𝗿𝗼𝗺𝗽𝘁 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴

Without writing giant prompts.
Without any fancy stack.

I stopped treating it like chat.
That was the whole breakthrough.

Most people use AI like this:

- Open blank window
- Type a big request
- Hope for magic
- Rewrite the prompt 4 times
- Still get something vague

That workflow is dead.
The better workflow is this:

𝗦𝘁𝗲𝗽 𝟭
Use 𝗖𝗼𝘄𝗼𝗿𝗸, not random chat.

𝗦𝘁𝗲𝗽 𝟮
Point Claude to a 𝗰𝗹𝗲𝗮𝗻 𝗰𝗼𝗻𝘁𝗲𝘅𝘁 𝘀𝘆𝘀𝘁𝗲𝗺.

Mine is simple.

One folder.
Four subfolders.
- 𝗔𝗕𝗢𝗨𝗧 𝗠𝗘
- 𝗣𝗥𝗢𝗝𝗘𝗖𝗧𝗦
- 𝗧𝗘𝗠𝗣𝗟𝗔𝗧𝗘𝗦
- 𝗢𝗨𝗧𝗣𝗨𝗧𝗦

Then inside 𝗔𝗕𝗢𝗨𝗧 𝗠𝗘 I keep 3 files:
- about me
- What I actually do day to day
- my voice

My tone, phrases I avoid, examples of writing that sound like me
my rules
Ask before acting. Show a plan. Never delete without approval.

That one move changed everything.

My prompts got shorter.
My revisions dropped.

The output got sharper because Claude finally had something to anchor to.
This is the part people do not want to hear:

𝗕𝗲𝘁𝘁𝗲𝗿 𝗼𝘂𝘁𝗽𝘂𝘁 is usually not about better wording.
It is about 𝗯𝗲𝘁𝘁𝗲𝗿 𝗰𝗼𝗻𝘁𝗲𝘅𝘁.

You do not need more clever prompts.
You need a 𝗯𝗲𝘁𝘁𝗲𝗿 𝗼𝗽𝗲𝗿𝗮𝘁𝗶𝗻𝗴 𝘀𝘆𝘀𝘁𝗲𝗺.

Most professionals are still optimizing sentences.
The top users are optimizing 𝗺𝗲𝗺𝗼𝗿𝘆, 𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲, 𝗮𝗻𝗱 𝗰𝗼𝗻𝘀𝘁𝗿𝗮𝗶𝗻𝘁𝘀.

That is why one person gets fluff and another gets leverage.

Would you spend 30 minutes setting this up if it saved you hours every week?

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>> Google invented the Transformer.
OpenAI built ChatGPT.

Organization beat invention.

That was the most important point in Yang Zhilin’s interview.

OpenAI didn’t need one magical breakthrough. It combined existing ideas with rare talent, capital and an organization built to move unusually fast.

Google had the researchers, infrastructure and architecture.

But having the ingredients is not the same as building the machine.

Most companies still treat AI as a technology rollout. Buy the models. Form a task force. Launch a few pilots. Wait for transformation.

But the real bottleneck is often organizational.

How quickly can decisions be made.
Do research and product share one goal.
How much bureaucracy sits between an insight and an experiment.

Yang’s bigger claim is even more provocative. Better prediction and lossless compression may keep producing more capable intelligence without one missing scientific miracle.

If he’s right, the next AI winner may not invent the breakthrough.
It may build the organization everyone else was too slow to create.

Skip one Netflix episode and watch this interview.

What is holding your AI strategy back today: the technology or the organization around it?

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>> I asked ChatGPT a simple question.

It gave a brilliant answer.

It was completely wrong.

I wrote:
“I want to wash my car. The car wash is 100 meters away. Should I drive or walk?”

ChatGPT said: walk.

It listed smart reasons about cold starts, emissions, efficiency, health.
Logical. Clean. Confident.

One problem.
𝗧𝗵𝗲 𝗰𝗮𝗿 𝗶𝘀 𝗱𝗶𝗿𝘁𝘆.
𝗜𝘁 𝗵𝗮𝘀 𝘁𝗼 𝗯𝗲 𝗶𝗻𝘀𝗶𝗱𝗲 𝘁𝗵𝗲 𝗰𝗮𝗿 𝘄𝗮𝘀𝗵.

The model optimized for sustainability.
It ignored physical reality.

This is how LLMs work.
They do not understand context.
They predict the most probable next sentence.

𝗔𝗜 𝗼𝗽𝘁𝗶𝗺𝗶𝘇𝗲𝘀 𝗳𝗼𝗿 𝗽𝗮𝘁𝘁𝗲𝗿𝗻𝘀.
𝗡𝗼𝘁 𝗳𝗼𝗿 𝗰𝗼𝗺𝗺𝗼𝗻 𝘀𝗲𝗻𝘀𝗲.

When your prompt lacks constraints, AI fills the gaps.
- Confidently.
- Funny with a car wash.
- Risky in strategy, finance, or medicine.

The fix is simple.

- Add constraints.
- State the physical reality.
- Force the model to reason within boundaries.

AI is powerful.
But only if 𝗬𝗢𝗨 𝗰𝗼𝗻𝘁𝗿𝗼𝗹 𝘁𝗵𝗲 𝗳𝗿𝗮𝗺𝗲.

Are you guiding AI or letting it guide you?

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>> AI won’t fix the energy crisis

It will 𝗿𝗲𝗱𝗲𝗳𝗶𝗻𝗲 who controls it and most leaders are not ready

At Gastech 2026 in Bangkok, one theme is impossible to ignore.

Energy is no longer just supply and demand.
It is data, prediction, and control.

The companies winning are not drilling more.
They are thinking differently.

AI is now optimizing LNG flows in real time.
Predicting demand shifts before they happen.

Reducing infrastructure risk before failure occurs.
That changes everything.

Because the advantage is no longer physical assets.
It is 𝗶𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 layered on top of them.

Most executives still treat AI as a side project.
A tool for efficiency.

That is a mistake.
AI is becoming the operating system of global energy.

The real shift is this
Energy companies are turning into data companies

The takeaway
If your strategy does not include AI at the core
You are already behind

Not in five years
Right now

Wanna join this event? 🔗 https://lnkd.in/dQm7yv_3

The question is simple
Do you see AI as support Or as 𝗽𝗼𝘄𝗲𝗿

#AI #EnergyTransition #Gastech2026 #LNG #Leadership

>> Claude can build your next 90 day marketing plan.

But one lazy prompt creates 𝗴𝗲𝗻𝗲𝗿𝗶𝗰 output.
Use this 9 prompt system instead.

Most people ask Claude:
“Build me a marketing strategy.”

The answer sounds smart.

But it usually has no owners.
No deadlines.
No real tradeoffs.
No review loop.

That is not a strategy.
It is a document.

I have run one of europes biggest tech brand with DIGITAL STORM weekly.
The plan was rarely the hard part.

𝗘𝘅𝗲𝗰𝘂𝘁𝗶𝗼𝗻 and tracking were.
So I stopped asking Claude for one big answer.

I broke the work into 9 decisions:
Set the 𝗼𝗯𝗷𝗲𝗰𝘁𝗶𝘃𝗲

Audit what is working
Rank the best channels

Build the content plan
Create the 𝗚𝗘𝗢 play

Map the lead funnel
Assign owners and dates

Track metrics tied to 𝗿𝗲𝘃𝗲𝗻𝘂𝗲
Build the review loop

Each prompt solves one part.
Together, they create an 𝗼𝗽𝗲𝗿𝗮𝘁𝗶𝗻𝗴 𝘀𝘆𝘀𝘁𝗲𝗺.

That is the difference between a plan people admire and a plan people actually execute.

Claude does not replace strategy.
It removes the friction of building, assigning, and improving it.

The exact prompts are in the visual.
Save this before your next quarterly planning session.

What kills more marketing plans:
Weak strategy or weak execution?


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>> 𝗔𝗜 𝗶𝘀 𝗻𝗼 𝗹𝗼𝗻𝗴𝗲𝗿 𝗮 𝘀𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗿𝗮𝗰𝗲.

It's becoming an 𝗶𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 𝘄𝗮𝗿.

Key signals this week:
• Google expands Gemini
• Anthropic reportedly approaches a trillion dollar valuation
• OpenAI pushes deeper into agents, hardware, and enterprise
• Governments increase oversight of frontier AI

The shift is clear.
Competitive advantage is moving from models to execution.

The winners won't be those with the most AI.
They'll be those with the strongest infrastructure, governance, and speed.

Most companies are still evaluating.
The leaders are already deploying.

What's your view?

Watch the full DIGITAL STORM weekly News breakdown now 👇

This video was created with CoreAIVideo

If you want to create videos like this, use my link to get 20% off. https://lnkd.in/dHmzcFin

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>> 𝗛𝗼𝘄 𝘁𝗼 𝗿𝗲𝗽𝗹𝗮𝗰𝗲 𝗽𝗿𝗼𝗺𝗽𝘁𝗶𝗻𝗴 𝗶𝗻 𝟭𝟬 𝗺𝗶𝗻𝘂𝘁𝗲𝘀
𝗠𝗼𝘀𝘁 𝗔𝗜 𝘂𝘀𝗲𝗿𝘀 𝗮𝗿𝗲 𝗱𝗼𝗶𝗻𝗴 𝘁𝗵𝗶𝘀 𝘄𝗿𝗼𝗻𝗴

And it is quietly destroying your output
You think you need better 𝗽𝗿𝗼𝗺𝗽𝘁𝘀

You don’t
You need a 𝗦𝗬𝗦𝗧𝗘𝗠

Because here is what is actually happening
Every time you open Claude

You reset everything
New 𝗰𝗼𝗻𝘁𝗲𝘅𝘁
New 𝗮𝘀𝘀𝘂𝗺𝗽𝘁𝗶𝗼𝗻𝘀
New 𝗲𝗿𝗿𝗼𝗿𝘀

That is why your output feels random

Here is the fix

Step 1
- Open Claude desktop
- Click Cowork not Chat

Step 2
- Create a folder with 3 files
* about me
* my company
* anti AI

This becomes your 𝗯𝗿𝗮𝗶𝗻

Step 3
- Write only what matters
- Who you are
- What you do
- What good looks like
- What you reject

No fluff
Only 𝗰𝗹𝗮𝗿𝗶𝘁𝘆

Step 4
- Connect Claude to that folder

Now it remembers every session

Step 5
- Turn on 𝗘𝘅𝘁𝗲𝗻𝗱𝗲𝗱 𝗧𝗵𝗶𝗻𝗸𝗶𝗻𝗴

Use Opus only for deep work

Step 6
- Paste this once

I want to [task]
Read all files first
Ask questions before acting
Do not guess

That is it

No long prompts
No repetition
No wasted effort

Now everything changes

Less 𝗴𝘂𝗲𝘀𝘀𝗶𝗻𝗴
More 𝗰𝗼𝗻𝘀𝗶𝘀𝘁𝗲𝗻𝗰𝘆
More 𝗰𝗼𝗻𝘁𝗿𝗼𝗹

Because the AI finally has something to think inside
The real lesson
AI quality equals 𝗲𝗻𝘃𝗶𝗿𝗼𝗻𝗺𝗲𝗻𝘁 𝗾𝘂𝗮𝗹𝗶𝘁𝘆

So be honest
Are you still fixing prompts
or building something that actually scales

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>>The next generation of sales software will not ask you to open another tab.

It will meet you where you already work.

I tested Apollo.io directly inside ChatGPT.

Instead of jumping between an AI assistant, a contact database, a CRM, and an outreach platform, I could manage the workflow in one conversation:

* Research the right companies.
* Find and enrich relevant decision-makers.
* Add verified contacts to an active sequence.
* Analyse the results and refine the next move.

The biggest advantage is not another AI feature.
It’s the removal of friction.

Most teams do not need more tools.
They need their existing tools to work together; with less copying, fewer handovers, and far less context switching.

That is the idea behind Apollo.io Anywhere.

Apollo’s data, intelligence, and execution capabilities can now appear directly inside ChatGPT, Claude, HubSpot, or your browser.

The tool comes to the workflow.
Not the other way around.

That may sound like a small change.
But multiplied across an entire GTM team, it can fundamentally reduce the distance between research and action.

The future of software is not another destination.
It is intelligence embedded wherever work already happens.

Try Apollo.io Anywhere: https://lnkd.in/dyUfptNM

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