My Most Advanced CV Is No Longer a Page
It is the Life-X / Ajinomatrix Sensory Intelligence Constellation
A normal CV lists positions, companies, projects, dates and responsibilities.
That is no longer sufficient for the work I am doing.
The most accurate version of my current CV is not a document. It is a living constellation of operational systems: Ajinomatrix, Life-X, MP6, JRF, Ajinoverse, FEELLLM, BSPG, ISPCR, TasteTuner-o, SensoryOS, BioSensei, Chef Paradous, and the emerging SpaceStation Triptych PoC.
Together, these projects form something more interesting than a group of websites.
They form a proof-of-work map.
They show how research, software, sensory science, food intelligence, public self-report, traffic generation, AI-era governance and commercial productization can be developed in parallel — and then connected into one coherent architecture.
I call it:
the Life-X / Ajinomatrix Sensory Intelligence Constellation.
Image: The Life-X.tech constellation.
Why this matters as a CV
A conventional CV says:
“I have experience.”
This constellation says:
“I built a system that demonstrates the experience.”
It shows:
sensory standards released publicly;
blog ecosystems generating traffic;
public PoCs deployed;
AI-era self-report tools tested;
food and sensory applications structured;
B2B commercial workflows emerging;
living-system experiments documented;
deployment infrastructure being prepared;
philosophical and governance questions published;
industrial use cases forming around cocoa, recipes, MP6 and sensory intelligence.
That is a different kind of professional identity.
Not résumé as biography.
Résumé as operating system.
The core company: Ajinomatrix
Ajinomatrix remains the industrial and scientific center.
Its work is focused on sensory digitization: taste, smell, texture, recipe intelligence, sensory profiles, ingredient modelling, AI-assisted product development and machine-readable representations of perception.
In earlier language, Ajinomatrix was a foodtech / sensory AI company.
That is still true, but incomplete.
Today, Ajinomatrix is becoming a platform company: a company that creates tools, standards, data structures, public interfaces, and workflows through which sensory intelligence can be captured, exchanged, interpreted and deployed.
The important development is not one single product.
It is the stack.
The standard layer: MP6
MP6 is the public sensory-data standardization effort.
It asks a deceptively simple question:
How can a sensory experience become portable?
Food, beverage, fragrance, consumer research and product development generate enormous amounts of sensory information, but much of it remains fragmented: spreadsheets, panel notes, PDF reports, lab templates, tasting memories, qualitative language, disconnected datasets.
MP6 proposes a compatibility layer.
Not merely taste.
Not merely aroma.
A multi-perception file logic: sight, smell, taste, texture, sound and contextual or psychosensory response.
MP6.org and MP6.studio now provide the public anchors for this work.
The MP6 Studio blog contains the current public explanation surface, including:
Beyond Taste: Affective Self-Report as an Extended Sensory Signal
Transforming Taste: Benefits of MP6 Sensory Standard
How MP6 Enhances Sensory Experiences in Food Industry
Understanding MP6: The Future of Sensory File Sharing
These posts are not only content. They are acquisition surfaces.
They help explain the standard, attract readers, test SEO, and route people toward tools.
The recipe layer: JRF and Ajinoverse
If MP6 is the sensory layer, JRF is the recipe/process layer.
JRF.recipes and Ajinoverse Studio represent the effort to structure recipes as interoperable objects rather than static text.
This matters because recipes are not only instructions. They are processes, transformations, ingredients, timings, temperatures, substitutions, cultural memories and sensory intentions.
When JRF and MP6 connect, a recipe can begin to answer:
what was made;
how it was made;
what changed;
how it was perceived;
which sensory dimensions shifted;
what should be adjusted next.
That is the basis of recipe intelligence.
The public human layer: FEELLLM
FEELLLM.org is the public self-report surface.
It helps a person translate a feeling, situation or sensory-affective experience into structured language.
For some people, that may mean emotional self-report.For food and sensory applications, it may mean: How did it taste? What did I experience? How do I tell my AI?
FEELLLM is not therapy, not diagnosis, not crisis support and not a medical device.
It is a public PoC in structured self-report.
It has now been explained through several public surfaces:
ISPCR, through the question of affective self-report without medicalizing experience;
Ajinomatrix, through sensory-affective modelling;
BSPG, through structured early-signal work;
MP6 Studio, through affective self-report as an extended sensory signal.
This is important because it shows the constellation regulating its own meaning across contexts.
The same tool is not described in the same way everywhere.
On ISPCR, it is a socio-philosophical experiment.On BSPG, it is an early-signal entry surface.On Ajinomatrix, it is sensory-affective modelling.On MP6 Studio, it is a possible extension of sensory profiles.
That is not fragmentation.
That is contextual intelligence.
The professional signal layer: BSPG
BlackSwanPreCog is the structured early-signal layer.
It deals with weak signals, risk, ambiguity, intuition, pre-crisis patterns, emotional contradictions and complex situations that should not be reduced too quickly.
FEELLLM acts as a public entry surface into this layer.
A user may begin with a feeling.FEELLLM helps translate it.BSPG can help structure it further.
This is also part of my work: building systems that respect ambiguity without surrendering to confusion.
The socio-philosophical layer: ISPCR
ISPCR provides the reflective and public-interest layer.
It is where the constellation asks:
What does it mean for AI to structure self-report?
How can tools help without medicalizing?
What is the boundary between reflection and diagnosis?
How can human experience be translated without being distorted?
What kind of institutions or systems are needed in the AI era?
This is where Life-X becomes more than a technology portfolio.
It becomes a governance question.
The ingredient-origin layer: TasteTuner-o
TasteTuner-o is the emerging ingredient-origin-process intelligence layer.
Its first serious test case is cocoa.
The cocoa / bean-to-bar use case is ideal because it combines:
terroir;
harvest;
fermentation;
drying;
roasting;
sensory evolution;
millésime;
luxury positioning;
authenticity;
ethical sourcing.
The question is not:
“How do we make chocolate taste better with AI?”
The better question is:
How do we preserve, reveal and guide the authentic sensory identity of cocoa through time?
That is why TasteTuner-o may become one of the most commercially understandable entries into the entire system.
It turns the abstract platform into one elegant use case:
a cocoa lot as a sensory-intelligent ingredient object.
The culinary and consumer layer: Chef Paradous
Chef Paradous, at paradous.fr, represents another part of the constellation: culinary intelligence, consumer validation, recipe-facing experience and the public testing of food-related intelligence.
Its role is important because no sensory-intelligence platform should remain trapped in expert systems only.
Food lives with people.
Chef Paradous helps keep that reality close.
The operational layer: SensoryOS and BioSensei
SensoryOS is the operational sensing layer.
BioSensei and the BioSphere extend the work into living environments: biotopes, aquaria, plant systems, energy autonomy experiments, device logging, incident recording, and environmental context.
This matters because sensory intelligence should not be limited to digital surfaces.
A living system has conditions, constraints, cycles, failures, rhythms and feedback.
BioSensei brings those realities into the constellation.
The extreme-environment layer: SpaceStation Triptych PoC
The SpaceStation Triptych PoC does not yet have a dedicated home.
It should.
Its role is to test the system in an extreme imaginary-operational context: food, perception, life-support, biotope, operations, autonomy and human experience in closed habitats or space-station-like scenarios.
A constellation that can model taste, environment, operations and human state in a space-station demonstrator is not only a foodtech stack.
It becomes a framework for inhabited intelligence.
The group layer: Life-X
Life-X is where the constellation becomes self-aware.
Not sentient. Not mystical. Organizationally aware.
It asks:
which public surfaces generate attention?
which tools produce interaction?
which articles create traffic?
which CTAs convert?
which domains explain which layer?
which PoCs are commercially useful?
which systems need governance?
which narratives should remain separate?
which parts of the group should talk to each other?
This is why Life-X may be described as:
a self-regulating high-tech constellation for the AI era.
It is not just a holding company.
It is a traffic-aware, research-aware, tool-aware, governance-aware structure.
That is the point.
What was recently created
In the recent constellation-building phase, we created and/or consolidated public explanation across multiple sites.
Documented entries include:
FEELLLM / self-report wave
Can Self-Report Tools Help People Translate Affective Signals Without Medicalizing Them? — ISPCR
FEELLLM: An Experimental Self-Report Surface for Sensory-Affective Modelling — Ajinomatrix
FEELLLM Public PoC: A Self-Report Entry Surface for Structured Early-Signal Work — BSPG
Beyond Taste: Affective Self-Report as an Extended Sensory Signal — MP6 Studio
MP6 public explanation wave
Transforming Taste: Benefits of MP6 Sensory Standard
How MP6 Enhances Sensory Experiences in Food Industry
Understanding MP6: The Future of Sensory File Sharing
This is not merely blogging.
It is multi-surface positioning.
The same ecosystem is explained differently depending on whether the visitor arrives through philosophy, sensory science, professional risk work, food technology, public self-report or AI experimentation.
Why this is advanced work
The advanced part is not that many websites exist.
The advanced part is that each website now has a role.
Ajinomatrix proves the B2B sensory intelligence platform.
Life-X frames the self-regulating group architecture.
MP6 standardizes sensory data.
JRF standardizes recipe/process data.
Ajinoverse federates the tools.
FEELLLM translates self-report.
BSPG structures early signals.
ISPCR provides socio-philosophical framing.
TasteTuner-o tests ingredient-origin intelligence.
Chef Paradous opens culinary and consumer surfaces.
SensoryOS / BioSensei connect to living and operational systems.
SpaceStation Triptych tests extreme-environment integration.
That is why this belongs in an advanced CV.
It shows the ability to create not only a product, but a living architecture of products.
The next professional threshold
The next threshold is not more invention.
It is readability, measurability and monetization.
The constellation now needs:
clearer dashboards;
stronger attribution;
cleaner CTAs;
fewer but sharper product paths;
one deployable pilot stack;
one strong ingredient-origin demo through TasteTuner-o;
one dedicated home for the SpaceStation Triptych PoC;
Chandra-style monetization review;
industrial packaging through Decision Sprint → Pilot → Deploy;
Life-X as the explicit coordination layer.
Conclusion
This is my most advanced CV because it is not asking the reader to believe a claim.
It shows the work.
A sensory standard.A recipe standard.A public self-report instrument.A structured early-signal layer.A socio-philosophical institute.A food AI company.A cocoa millésime PoC.A living-systems lab.A space-station demonstrator.A traffic-aware group architecture.
Together, they form a new kind of professional artifact:
a working constellation.
That is what Life-X is becoming.
And that is the best current proof that Ajinomatrix has crossed from startup claim into platform reality.
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