AI Alignment — dynamic I·V·O map

Every part of the system continuously shows its current I·V·O state. Signal and decisions travel the same line a real AI system runs on — data in, objective set, behavior in the middle, guardrails and people at the edges.

Dynamic State Notation v3.5

I — Intensity (state presence)

ISteady-state

·Low signal

•Active system

*Active monitoring

!Overload

?Uncertain state

#Capacity overload

:Signal noise

V — Movement (dynamics)

.Idle / near-zero output

>Optimisation

>>Exponential optimisation

⟳Reconfiguration

↺Persistent loop

~Instability

↑Risk increasing

↓Risk decreasing

O — Context (field)

OInternally coherent node

()Sandbox

)(Bottleneck

[]Constraints / governance

~Unstable runtime

∞Unbounded search space

Example: ! >> )(
Overload, exponential optimisation, jammed against a bottleneck.

Data

Training

Behavior

Deployment

Feedback

: >> )(

Model Behavior / Alignment State

The model optimizes conflicting goals fast, jammed against a bottleneck — behavior fragments under pressure.

under pressure