Principle
AI-native means intelligence is designed into the system, not added as a late feature.
Framework
GENOME™ AI Framework
GENOME™ defines a practical way to assess whether a system merely uses AI or is truly organized around learning.
DNA question
If intelligence is removed, does the system still have value? If yes, it is not native yet.
Unipole role
Unipole turns GENOME™ into diagnosis, export files, audits and implementation paths.
GENOME AI Framework structure
A progressive reading of AI-native systems
GENOME does not assess maturity by the presence of an AI feature. It examines design order, signal quality, living representation and the loops that make the system improve.
Central DNA Test
If I remove intelligence, does a usable product remain, or does its core value disappear?
DNA
The 4 genomic properties
These properties distinguish added AI from intelligence that is constitutive of the system.
1
Omnipresence
Intelligence runs through functions, data and interactions.
2
Expression
Users can see that the system understands and improves.
3
Heredity
What is learned persists, is transmitted and enriches what follows.
4
Evolution
The system improves through feedback loops and useful selection.
Doctrine
The 7 design principles
The principles test whether the architecture truly thinks through learning or merely adds visible AI features.
Principle 1
Data for learning
Data is not merely stored; it is structured to create meaning.
1
Principle 2
A signal at every interaction
Clicks, rejections, hesitation, feedback and outcomes become usable.
2
Principle 3
Visible learning
Users must be able to perceive the system’s progress.
3
Principle 4
Living representation
The profile evolves with use instead of remaining a static record.
4
Principle 5
Global learning
Collective patterns improve each individual experience.
5
Principle 6
Critical path
Intelligence carries the core value rather than sitting beside it.
6
Principle 7
Evolution through AI
Every product change must identify the signal and learning it creates.
7
Sensors
Sensors: the sensory organ of the system
GENOME distinguishes data, signals and sensors. Without sensors, a system accumulates data but does not understand what is happening.
01
Engagement
Attention, return, focus and depth of consultation.
02
Preference
Explored attributes, implicit rejection and filter changes.
03
Context
Time, place, channel, device and usage situation.
04
Feedback
Explicit opinion, post-action behavior, sharing and support.
05
Outcome
Completion, recurrence and value obtained after use.
06
Collective
Peer behavior and social validation.
Diagnostic
The test grid: 40 points, 5 axes
The DNA Test assesses design. A sensor instrumentation audit then measures what truly exists in the system.
8 pts
Intelligence architecture
Was intelligence designed before experience and data architecture?
8 pts
Signal capture
Do positive and negative interactions become structured signals?
8 pts
Living representation
Does the observed entity evolve between day 1 and month 6?
8 pts
Improvement loops
Does the system learn individually, globally and continuously?
8 pts
Defensibility and value
Does the advantage strengthen with time and use?
Application
The application method
1
Identify core intelligence
State what the system does better after every use.
2
Design data around learning
Model operational and intelligence schemas together.
3
Map signals
List every interaction, including rejection and friction.
4
Design the living representation
Define what evolves, what is inferred and what remains correctable.
5
Close the loops
Connect usage, feedback, global learning and active evolution.