CRED is a method for reading relationships as fields. It is built on a simple principle:
Dynamics only become visible when you see the system as a whole – not as individuals or isolated events.
Instead of asking “what is happening?”, CRED asks: “What is the field that creates what is happening?”
This produces analyses that are:
- Precise – because they reveal underlying structures
- Neutral – because the method is pattern-based, not opinion-based
- Practical – because the insight shows where the system can actually move
CRED is used in relationships, groups, organisations and complex situations where traditional analyses fall short. The method uncovers patterns that normally remain hidden – but become instantly recognisable once they are shown.
What a complete CRED analysis contains
A full analysis consists of eight movement points, which together provide a coherent and operational picture of the field.
1. The Field Map
The first step is to identify
who and what actually influences the dynamics. Not all actors carry equal weight. CRED distinguishes between:
- primary actors
- secondary fields
- hidden or indirect lines of influence
This creates a precise starting point without noise.
2. Relational Axes
Next, the structural connections between the actors are mapped. Each relationship has:
- a direction
- an intensity
- an asymmetry
- a latent developmental path
This provides the first picture of
how the field actually moves.
3. Dynamic Patterns
Here, the underlying mechanisms explaining why things happen the way they do are uncovered. Typical patterns include:
- movement axes
- stagnation nodes
- shifts in power
- harmonic and disharmonic zones
- blind spots (fields none of the actors see)
This is often the point at which users recognise the situation with immediate clarity.
4. Triads and Field Configurations
CRED does not work linearly, but systemically. The most important structure in any field is the
triad – the three-point system that determines:
- direction
- stability
- level of conflict
- potential for breakthrough
Triads reveal what holds the system up – and what holds it back.
5. Timelines
Here the dynamics are seen in motion. CRED identifies:
- what is mature
- what is incoming
- what is nearing collapse
- what needs more time
Timelines make the analysis operational and action-oriented.
6. The Possibility Space
This is the core of a complete analysis. Once the field is mapped, CRED uncovers:
- which doors are actually open
- what can be opened
- which movements are impossible right now
- where the path of least resistance lies
CRED shows real alternatives — not wishful thinking.
7. Risk and Vulnerability
Every field has points that can tip the dynamics. The method identifies:
- where the system is most exposed
- which relationships carry the greatest pressure
- which factors may trigger conflict or rupture
- where relief or adjustment is needed
This provides a realistic picture of risk without drama.
8. Future Movement
Finally, the system’s likely development is described, based on the field’s own logic. This includes:
- direction
- tempo
- possible scenarios
- recommended positioning
- what should be strengthened or avoided
The user is left with a clear understanding of
where the field is actually heading.
What CRED gives – in one sentence:
CRED makes the invisible visible: the structures that drive people and systems.
How CRED relates to ChatGPT
CRED is not a separate programme, nor a replacement for the AI model.
CRED is a structuring and analytical layer that sits on top of ChatGPT.
This means:
- CRED governs how ChatGPT reads information – field-based, systemic and relational.
- CRED organises complex data into structures that make the whole visible.
- ChatGPT generates language and communicates the insight, while
- CRED determines which patterns should be identified and how they should be understood.
You can think of it as two layers:
- ChatGPT – language, formulation, flow, coherence
- CRED – field understanding, relational analysis, systemic patterns, dynamic structure
When you order a CRED analysis, it is the
CRED layer that provides the direction and structure. ChatGPT is the communication engine that expresses the insight in clear and understandable language.
This creates analyses that are:
- more precise
- more coherent
- more predictable in their dynamics
- and far deeper than what a language model alone can provide
CRED turns ChatGPT into an
analytical tool, not just a conversational model. This is unique; no one else offers this and the method is patent-pending.
What CRED provides – that ordinary ChatGPT cannot
ChatGPT is a language model. It can write, explain, suggest and converse — but it does not understand fields. It does not interpret relationships as systems, and it does not analyse dynamics as unified wholes.
CRED changes this.
CRED enables ChatGPT to deliver analyses that are consistent, structured and accurate, because the model works within a framework that:
1. Sees the whole – not the fragments
Ordinary ChatGPT evaluates content point by point. CRED analyses
the field as a whole and reveals the structures behind individual events. This gives insight into:
- what drives the system
- where the dynamics are heading
- which relationships carry the most force
- where hidden conflicts and bindings lie
2. Reveals patterns without asking the user
A standard language model guesses answers from the text. CRED identifies relational patterns and dynamics that are not stated in the text at all — but which are natural features of the field.
This is the key to why CRED analyses feel “spot on”.
3. Provides consistent depth from start to finish
Ordinary ChatGPT can shift in style, perspective or depth. CRED forces the analysis into a
rigid structure, ensuring that:
- nothing essential is forgotten
- every part of the field is illuminated
- no concepts are mixed
- no assumptions or random answers slip in
This is what makes CRED-based analyses stable.
4. Distinguishes between levels of reality
ChatGPT often mixes:
- psychology
- strategy
- history
- emotion
- opinion
- generalisation
CRED maintains a
hierarchical level distinction that keeps the analysis clean and free of confusion:
- field
- structure
- dynamics
- movement
- risk
- possibility space
This produces a clarity that cannot arise from language-model thinking alone.
5. Provides an objective position in complex situations
ChatGPT is sensitive to phrasing and can unconsciously tell the user what they want to hear. CRED removes this.
CRED operates:
- without preferences
- without wishful thinking
- without normativity
- without psychologising
This makes the analysis unusually sober and reliable.
6. Makes dynamics predictable
ChatGPT can describe what is happening. CRED shows what is going to happen – because it maps:
- movement axes
- maturation
- stagnation
- developmental pressure
- direction in the field
This provides forecasts that are field-logical, not speculative.
7. Provides real practical applicability
Ordinary ChatGPT often ends with general suggestions. CRED identifies:
- what is actually possible
- which doors are locked
- what is impossible right now
- where the path of least resistance lies
This makes CRED suitable for:
- relationships
- teams
- conflicts
- organisations
- geopolitics
- strategy
Summary
ChatGPT explains. CRED understands.
ChatGPT writes text. CRED maps fields.
ChatGPT may advise. CRED shows direction.
ChatGPT gives answers. CRED gives clarity.
Ethical considerations
Astrological data?
When relationships between people are analysed, we use basic astrological data as a starting point. This is NOT unserious and has a rational, ontological explanation.
Read more here »