AI makes building faster. It does not make understanding optional.

Most AI projects don't fail because the technology is wrong. They fail because nobody understood the work before choosing the technology.

I help companies figure out where AI creates genuine value, then build it with them. Not from a slide deck. From inside the team, writing code.

Faster delivery Deutsche Telekom
Fewer production bugs Mercedes-Benz
Build cycle time Siemens

How I work

I start by spending time with the people who do the work. I map workflows, identify where things break down, and figure out where AI creates genuine value and where it adds cost without return. Then I build it: code, architecture, data pipelines, governance.

I plan my own exit from the first conversation. The test: can the team continue at the same quality without me? For specialized needs or continuity, I bring in senior technical peers from my professional network.

This way of working was shaped by formative years at frog and Intuity Media Lab, where understanding the problem came before the technology decision, and refined through 15 years of enterprise delivery at Siemens, Deutsche Telekom, and Mercedes-Benz.

What I Don't Do

  • Slide decks and steering committees
  • Staff augmentation or body-shopping
  • Open-ended retainers with no exit plan
  • Technology recommendations without implementation
  • Engagements where I can't write code
  • AI workshops that end with a report nobody acts on

How to start

The first step is a conversation. 30 minutes, no cost, no pitch. Tell me what you're dealing with and I'll tell you honestly whether I can help.

If there's a fit, I typically propose an AI Opportunity Diagnostic: two days with your team, three deliverables, a clear picture of where AI helps and where it doesn't. Starting at EUR 9,500, fixed price. But that's a decision you make after we've talked, not before.

Who this is for

  • Companies with real operational complexity, whether that is a 10-person team scaling to 200 or an established organization with 1,000 employees
  • Leadership teams under pressure to "do something with AI" but unclear on what
  • Organizations that have tried an AI pilot that stalled, or spent money on a strategy deck that went nowhere
  • CTOs and product leaders who want senior technical judgment, not a team of juniors

This is not for companies that want a chatbot demo in two weeks. It is for companies that want to know where AI will still be creating value in two years.

How engagements progress

Every engagement starts the same way: a conversation. 30 minutes, free, no pitch. If there's a fit, here's how the work typically progresses:

1

Understand

The AI Opportunity Diagnostic. Two days. Understand who the users are, what pain points they face, where workflows break down. Identify which problems AI can solve and which it cannot, including where EU AI Act requirements apply. Deliverables you can act on, with or without me. Starting at EUR 9,500.

2

Validate

A focused PoC Sprint. Two to four weeks. Build a working proof of concept with real data and real constraints. Not a demo. Evidence for a go/no-go decision. EUR 12,000 to 25,000.

3

Build

Embedded delivery. Weeks to months. I join the team, write code, make architectural decisions, set up governance. EU AI Act considerations from day one. EUR 1,600 per day.

4

Exit

I plan my exit from the first conversation. Documentation, knowledge transfer, ownership mapping. The test: can the team continue at the same quality without me?

Let's start with a conversation.

30 minutes. No cost. No pitch. Just an honest take on whether I can help.

Tell me what's going on