With over a decade of experience in IT, focusing on leveraging AI, automation, and cloud technologies to drive impactful digital transformation. My role involves utilizing skills in Microsoft Azure, YAML, and Open API to deliver tailored solutions that meet the needs of modern enterprises.  

Passionate about collaboration and innovation, I aim to empower organizations with cutting-edge technologies to optimize their processes and create meaningful business value. By aligning strategic vision with execution, I contribute to the successful development and adoption of advanced technical solutions that address complex challenges in the evolving tech landscape.

I've been saying this for months, and now Snowflake's CEO just confirmed it:

Stop spreading AI everywhere.

Start nailing it in ONE place.

Sridhar Ramaswamy dropped a truth bomb this week.

Companies trying to "AI-transform" everything are wasting money.

His approach? 

Snowflake focuses AI on software development. 

Not marketing. Not HR. Not every department at once.

Just their critical workflow. Deeply integrated. Measurably better.

The result? Actual competitive advantage.

Here's what I see..

Companies spending €200K on AI tools across 15 departments.
Getting 15% of the value they should.

Then they call me asking why nothing works together.

My answer is always the same:

Pick ONE high-pain workflow.
Automate it completely.
Measure the hours saved.
Then scale.

German engineering applies to automation..

Precision first, expansion second.

Manufacturing firm automated ONE workflow (in Germany)

Quality control documentation.

35 hours saved per week.
€91,000 saved annually.

That single workflow paid for their entire automation infrastructure.

Stop buying AI for everything.
Start building AI where it matters.

Your critical path is waiting.

PS: Running automation workshops in Frankfurt next month. Comment WORKSHOP and I'll send details.

Mirza Iqbal

Helping Enterprises with AI, LLM, Automations, Data, and Cloud Infrastructure | n8n Ambassador

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Technical skills don't matter like they used to.

What matters now? Three things.

First: Clarity of communication.

Your output quality depends entirely on your input clarity.

"Help me analyze this data" gets you generic charts.

"Analyze this Q4 sales data, identify the top3 underperforming regions, compare their metrics against our best performer, highlight the gap in conversion rates, and suggest2specific actions per region based on the patterns you find" gets you actionable insights.

The AI is only as good as your ability to describe what you need.

This isn't technical. It's communication.

Second: Speed of iteration.

Winners don't nail it on the first try.
They iterate faster than everyone else.

Build. Test. Adjust.
Build. Test. Adjust.

Repeat until you win.

Most people spend weeks planning the perfect prompt.
High performers ship10 versions in that same time.

They learn. They adapt. They move.

Speed beats perfection every single time.

Stop overthinking. Start shipping.

PS: The best builders I know aren't the most technical. They're the clearest communicators who move the fastest.

Most people relax on weekends.

I burned through a few hundred euros in proxy costs instead.

Worth every cent.

Spent 48 hours locked in, testing and iterating on a data extraction project.

Run a test. Find an edge case. Fix it.
Run another test. Find another edge case. Fix it.

Repeat 100 times.

The goal was simple: clean, accurate data. Zero corruption. Zero garbage values.

Every field precisely where it should be.

Those green bars in my dashboard? Each one represents hours of trial and error.

The success rate climbing while failed requests dropped?

That's the result.

Testing is expensive.

But shipping broken data? That costs more.

Sometimes you just have to grind.

PS: What did you build this weekend?

Efficiency shouldn't be a "punishment." 

Here's what's happening right now.

We deliver faster. We deliver better. We've mastered our craft.

And yet? The conversation still goes back to hourly rates.

"What's your hourly rate?"
"That's too high."
"Can you do it cheaper?"

But here's the tension we're all facing.

AI is making things faster. Capabilities are expanding. And suddenly, what used to take days now takes hours.

So are we supposed to charge less because we're more efficient?

I work both ways. Sometimes hourly makes sense. Sometimes it doesn't.

But the real question isn't about the clock.

It's about the outcome.

When we get faster at delivering results, that's not a reason to earn less. That's the entire point of getting better.

Scale without burnout.
Speed that matches business reality.
Results that move the needle.

The market is shifting under our feet. AI is reshaping expectations. Clients have more options than ever.

So how do we hold our ground?

By shifting the conversation from time to value.

Not because hourly is wrong. But because value is what actually matters.

To everyone navigating this right now, how are you handling this shift?

We are witnessing the biggest economic shift since the internet.
And most people have no idea it's happening right now.

(Save + Repost this ♻️ for later)

After spending weeks studying this..

I'm convinced that the agentic economy will reshape how we work, shop, and live within the next 3 years.

Not a trend. A complete rewiring of our economy.

What's actually changing:

For decades, we've been operators.
Click by click. Step by step.

Now? We're becoming orchestrators.

We're moving from telling computers what to do to delegating high-level goals to AI that acts independently.

The foundation is already built.

The internet boom started with 100M users in 1999.
Today? 5.6 + billion connected people.

These AI agents can now operate, collaborate, and scale instantly across this network for basically Low/zero cost.

The stage is set for an explosion.

But here's the technical puzzle we had to solve first:

How do you get millions of different AIs to work together without chaos?

The framework exists. Three core pieces:

1. Memory (Model Context Protocol)
  So agents don't forget everything every5 minutes.

2. Communication (Agent-to-Agent Protocol)
  A common language so they can actually talk.

3. Payment (Digital Wallets)
  Secure permission slips that let agents buy things on your behalf automatically.

This changes everything about business.

For 20 years, we lived in an attention economy.
Companies fought for eyeballs and clicks.

Now? We're entering a preference economy.

When your AI agent can scan the entire market instantly and find the absolute best product for you, ads become irrelevant.

The winners will be companies whose products simply meet your needs better.

This is happening now in 2026.

New roles are emerging. Entire careers built around managing fleets of AI agents.

But the risks are real.

This behavior in markets worries me most.

Imagine millions of hyper-rational AI agents reading the same data at the exact same millisecond.

If they all decide to sell at once? Flash crashes become way more intense and common.

The guardrails being built:

• Spending caps and kill switches for runaway execution
• Ethical testing to prevent emergent collusion
• Circuit breakers for synchronized market moves

Here's the timeline that should wake you up:

2027 (next year): Half of all routine knowledge work automated
2030: 75% of major companies using agents in core operations  
2035: This tech generating a third of all software revenue globally

The economic prize? 3 trillion in annual productivity gains by 2035.

That's not total market value. That's extra value created every single year.

But here's the question that keeps me up at night:

As we hand over more decisions to these autonomous systems, who's ultimately in control?

The efficiency gains are undeniable.
The personalization is incredible.

But we need to navigate this carefully.

The agentic economy is here. 

Your choice: understand it now or scramble to catch up later.

AI agents just graduated from pilots to production lines.

While everyone's still debating self-improving AI...

Manufacturers in Germany are already deploying workflows that actually work:

→ Auto-generate work orders from emails
→ Flag missing data BEFORE errors occur
→ Scale expertise without hiring a single person

The difference?

They're not waiting for perfect AI in 2028.

They're building now.

Here's the 5-step workflow saving enterprises €50K+ annually:

1. Email intake automation
2. Data validation triggers
3. Smart work order generation
4. Expert knowledge capture
5. Continuous workflow optimization

Stop waiting for AI to get better.

Start using what's already here.

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