Training on AI and automation for business professionals: workshops, online courses, live sessions, all the way down to custom company training programs

Co-Founder

Circula

Advisor

Circula.com

Head of Operations

On Deck

Fellow

solarisBank AG

Senior Business Development Manager

payleven Global Mobile Payments

IT Team Lead

Fundraising - Internship

Helping startup operators move faster with automation

I train business professionals on AI and automation: workshops, online courses, live sessions, all the way down to custom company training programs

Alexandre Kantjas

What training 5,000+ operators on AI taught me: it's not about 𝘴𝘬𝘪𝘭𝘭𝘴, it's about new 𝘳𝘰𝘭𝘦𝘴. Here they are:

AI means new tools → new tools require new skills → new skills create new 𝘳𝘰𝘭𝘦𝘴.

Skills training without role clarity will lead you nowhere. 

The companies moving fast aren't only hiring people with AI skills or running better training programs: they also understood the importance of 𝘳𝘦𝘥𝘦𝘧𝘪𝘯𝘪𝘯𝘨 𝘳𝘰𝘭𝘦𝘴.

Here are the top 3 every company will hire for:

𝐀𝐈 𝐎𝐩𝐞𝐫𝐚𝐭𝐨𝐫𝐬. 
→ 𝘞𝘩𝘢𝘵 𝘵𝘩𝘦𝘺 𝘥𝘰: Use AI tools to do their current job faster. Sales managers. Customer service reps. Marketers: all will be expected to lift their individual productivity with AI.
→ 𝘛𝘰𝘰𝘭𝘴 𝘵𝘩𝘦𝘺 𝘶𝘴𝘦: AI chat solutions (ChatGPT, Claude, Gemini), AI in SaaS applications that support their workflows.

Prediction: This role will become the baseline. Use AI or get squared.

𝐀𝐈 𝐁𝐮𝐢𝐥𝐝𝐞𝐫𝐬 
→ 𝘞𝘩𝘢𝘵 𝘵𝘩𝘦𝘺 𝘥𝘰: Automate team processes using AI and no-code platforms. RevOps managers. BizOps leads. Operations analysts. They thought systems and processes in the past. The expectation in the future will be to turn them into  workflows and systems.
→ 𝘛𝘰𝘰𝘭𝘴 𝘵𝘩𝘦𝘺 𝘶𝘴𝘦: No-code automation platforms like Zapier, Airtable, n8n, Make and all the good stuff I won't list here.

Prediction: Every business function will hire at least one AI Builder to automate the team's work.

𝐀𝐈 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐬 
→ 𝘞𝘩𝘢𝘵 𝘵𝘩𝘦𝘺 𝘥𝘰: Build apps and scalable systems. They're today's engineers, but the way they ship solution is about to entirely change.
→ 𝘛𝘰𝘰𝘭𝘴 𝘵𝘩𝘦𝘺 𝘶𝘴𝘦: Cursor, Replit, v0, Bolt - AI-native IDEs and vibe coding platforms that let them ship 10x faster by pair-programming with AI.

Prediction: in less than 18 months, every engineer will be an AI engineer.

This time is different: your role too will change. 

Which role do you see for yourself?

It's one thing to see potential in AI. It's another to have identified 𝘨𝘳𝘦𝘢𝘵 𝘈𝘐 𝘶𝘴𝘦 𝘤𝘢𝘴𝘦𝘴 that move the needle for 𝘺𝘰𝘶𝘳 business.

Join me and Jan for our upcoming workshop where we'll reveal the 15 𝐜𝐨𝐫𝐞 𝐀𝐈 𝐛𝐮𝐢𝐥𝐝𝐢𝐧𝐠 𝐛𝐥𝐨𝐜𝐤𝐬 that power virtually every business automation. Whether you're in sales, operations, marketing, or finance, these patterns repeat across industries and functions.

𝐇𝐨𝐰 𝐭𝐨 𝐟𝐢𝐧𝐝 𝐀𝐈 𝐮𝐬𝐞 𝐜𝐚𝐬𝐞𝐬 𝐟𝐨𝐫 𝐲𝐨𝐮𝐫 𝐛𝐮𝐬𝐢𝐧𝐞𝐬𝐬
👤 𝐆𝐮𝐞𝐬𝐭: yours truly and Jan Meinecke
🕒 𝐓𝐢𝐦𝐞: Thursday, November 27th, 2025, 5:00pm CET
📍 𝐋𝐨𝐜𝐚𝐭𝐢𝐨𝐧: Online

You'll learn:
- 5 frameworks for evaluating and prioritizing AI use cases
- How to recognize which patterns apply to your specific challenges
- The 15 fundamental AI building blocks that solve real business problems
- Live examples showing each building block in action

Want to join? Let me know in the comments.

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AI transformation is in every board meeting's agenda. Yet most initiatives will fall short. Here's why:

Most companies have started initiatives to transform with AI this year. 

They're picking between ChatGPT Enterprise and Claude for Teams. 
They're running workshops on prompting. 
They're setting up AI councils to "figure out strategy."

Most of it is going to fail. 

It won't build the necessary momentum.

The reason: AI transformation requires six interconnected dimensions moving together:

𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐲: How you respond to AI's business implications (market shifts, product opportunities, operational redesign)

𝐂𝐮𝐥𝐭𝐮𝐫𝐞: The behaviors that define whether people experiment or wait for permission

𝐏𝐞𝐨𝐩𝐥𝐞: Building skills, allowing experimentation, rethinking roles as AI becomes part of every job

𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐲: The platforms, tools, and governance that enable AI across the org

𝐃𝐚𝐭𝐚: Not just structured data, but unstructured information and tacit knowledge trapped in people's heads

𝐏𝐫𝐨𝐜𝐞𝐬𝐬𝐞𝐬: Redesigning workflows with AI at the core, not just automating what exists

These aren't sequential: you can't perfect Strategy, then move to Culture, then People.

They're concurrent. 

Interconnected. 

Each dimension affecting the others.

Here's what we see working:
→ Assess where you stand in each dimension 
→ Identify your biggest bottleneck 
→ Fix that constraint first 
→ Move to the next

AI transformation won't happen all at once. It happens by removing bottlenecks systematically until momentum builds.

We'll be breaking down the full framework in a series of articles. 

First article published, link in the comments.

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