We don’t have a meeting problem.

We have a learning-from-meetings problem.

Sure, meetings could be less and shorter. But the real issue? We don’t learn from them.

What we get instead:

  • Soulless AI summaries (“The team discussed various topics”)
  • Half-baked notes from colleagues (only what they found interesting)
  • Transcription theater (“John mentioned the deadline”)

Nobody learns from this.

Full Guide: Meeting Intelligence →

What I Create Instead

Three outputs from every meeting:

OutputAudienceContains
Meeting DebriefTeamTopics, Insights, Decisions, Actions
Effectiveness ReviewTeamFormat fit, time efficiency, patterns
Personal SubtextJust meManöverkritik, patterns, political awareness

See a real example →

The Real Differentiator: Effectiveness Review

AI tells me:

“This Daily ran 45 minutes. Topic X should have been a workshop.”

“Third time this month the same decision got deferred.”

When a neutral tool says “this meeting drifted”—that’s different than a colleague saying it.

Insight
The AI is a glorified statistics machine. When the statistics say your meeting was ineffective, it’s data—not blame.

We don’t have a meeting problem. We have a wrong-format-for-content problem.

And that’s something AI can actually see—because it’s not emotionally invested in the meeting.

Deep Dive: Meeting Effectiveness Review →

Personal Subtext

The official debrief is for the team. The subtext is for me:

  • What could I have done better?
  • Patterns I’m repeating (Firefighter Mode, Desk-Vortex)
  • Political dynamics to be aware of

It’s okay if AI tells me I talked too much. Just not in the official record.

Deep Dive: Personal Subtext & Manöverkritik →

PS: DSGVO

Of course, all of this needs to be DSGVO-compliant. We evaluate the meeting, not the people. Deep Dive: DSGVO Compliance →

Your Turn

How do you document meetings today?

Part of my AI as Operational Partner series.