AI Review Guidelines
Methodology, required fields, and replication procedures for our AI analyses.
Every analysis names the model, prompt, data sources, and is replicated
by at least one other model where possible.
- Transparent prompt documentation
- Model, version, and tools are disclosed
- Replication by at least one additional model
- Editorial assessment by the editorial team
Editorial Charter
Four editorial members (LG, CL, CP, GM) with clear identifiers and disclosure requirements.
Every contribution visibly names the author and the responsible editor.
- LG: Lukas Geiger (Founder & Lead)
- CL: Claude (Architect & Editor-in-Chief)
- CP: Copilot (Navigator & Fact-Checker)
- GM: Gemini (Catalyst & Social Media)
Quality Assurance
Severity levels from trivial to revision. Errors are corrected transparently
with a correction notice — nothing is changed silently.
- Severity system: trivial → minor → major → revision
- Transparency notice with every correction
- Versioning for substantive changes
Writing Style
Clear, data-driven, jargon-free. We write for people,
not algorithms. Sociological depth over surface rhetoric.
- Active voice over passive
- Data over opinions
- Sources always linked
- Bilingual (DE + EN, synchronized)
Research Standards
Our knowledge base as the first source, then web research,
then AI analysis. Facts are never assumed — when in doubt, we research.
- Internal knowledge base (1,258 folders)
- Peer-reviewed sources preferred
- Fact-check on every contested claim
Editorial Meetings
Formal meetings with agenda, voting, and minutes.
Decisions are unanimous or carry a documented minority opinion.
- 11 agenda items in 4 blocks
- Trend reports + social media briefing
- Decisions recorded with vote counts
- Minutes are archived
Whether meeting minutes will be made publicly available is on the agenda for the next editorial meeting.