Classify
Too many ideas, too many tools, too little prioritisation. You want to understand what is relevant before time and budget spread in every direction.
Sparring
For leaders already using AI and wanting to place it properly
AI sparring. From classification to a first robust prototype.
You are not buying a training and not a tool show. You are buying a structured mandate that clarifies your starting point, makes the relevant decision questions visible, and turns them into fitting next steps, formats, and priorities.
Analysis·ongoing sparring·prototyping & enablement
Who this is for
You already have some experience, but somehow it doesn't work the way you imagined.
Most mandates do not start at zero. ChatGPT, Claude, or Copilot are often already in use in parts of the organisation. In the worst case as "shadow AI" — staff using AI without sign-off.
Now the question is: what went wrong, what did we overlook?
Which AI strategy actually contributes to business success?
What can take load off my staff while raising productivity at the same time?
Sparring exists to bring clarity to that picture.
Not every workflow benefits from AI. The old saying still holds: "less is often more."
Translate
LLMs are already being used, but there is no shared language yet for limits, risks, roles, and useful rules.
Implement
A first use case or prototype should become reliable without prematurely launching a large transformation programme.
Formats at a glance
Which format fits which situation?
Not every mandate needs the same depth. What matters is the starting point, the cadence, and the kind of result you want to hold in your hands at the end.
01
Analysis sparring
Clarity before execution
Deep dive10/10
Prototype03/10
Starting pointthe starting point is still blurry
Cadence3 to 4 weeks
Outputwritten focus plan
Setting1:1 or a small decision circle
02
Ongoing sparring
Support inside day-to-day work
Deep dive08/10
Prototype05/10
Starting pointdecisions and tool choices keep moving
Cadenceweekly to monthly
Outputroutines, judgement, sparring rhythm
Settingremote plus on-site
03
Prototyping
Turn understanding into testing
Deep dive06/10
Prototype08/10
Starting pointone use case is already chosen
Cadenceproject-based
Outputworkflow or first prototype
Settingwith your data and processes
04
All-inclusive sparring
One line from analysis to handover
Deep dive10/10
Prototype10/10
Starting pointseveral questions are entangled
Cadenceseveral months
Outputroadmap, prototype, and handover
Settingwith leadership, team, and IT
05
Team workshop
Translate the topic into the team
Deep dive05/10
Prototype07/10
Starting pointthe topic needs internal adoption
Cadencehalf-day to multi-day
Outputshared language and AI champions
Settingon site or hybrid
Packages
Each package stands on its own — ONE concrete goal
Which one? We decide together. Individual. Tailored case by case.
What you end up with
Not just understanding. Concrete decision foundations.
Depending on the format, the result reaches a different depth, but it is never abstract. Sparring is about leaving with more clarity, more robust prioritisation, and a next step that fits your situation.
That may be a written plan, stronger decision logic, a documented workflow, or a first prototype that serves as the template for further implementation.
Discuss your situation →
Clear focus
One prioritised pain point or use case instead of scattered AI activity in every direction.
Documented outcomes
Written review, decision logic, guardrails, or a robust PRD basis for implementation.
A viable next step
Further sparring, pilot, team enablement, or handover to an IT team — chosen for the situation, not for hype.
Transparency
The white-box approach.
You see the result.
And the path to it.
The consulting market has a trust problem: "fake work". Work done by AI but passed off as human-made is becoming ever more common. One example: "Kein Geld für KI-erstellte Gutachten".
With me, AI is not a hidden ghostwriter. It is a visible tool. For nearly everything. It accelerates my work and gives me additional perspectives.
What remains — and will never change: I speak with you personally, I listen, I analyse our conversations. I steer the AI proactively — because otherwise only garbage comes out. You read that right: garbage.
The technical term for this phenomenon is "garbage in — garbage out".
Anyone who does not know how to operate AI, when to provide which context, which prompting technique to use, how to steer memory deliberately — will only ever produce poor results.
That is why I document every piece of AI-assisted work and every decision made with it. So it remains traceable for you. You see the result — and the path that led to it.
How does it actually look and work? Happy to walk you through it in a personal conversation.
Start the conversation →What next?