Open to workAI systems · research engineering · safety

Adarsh

Adarsh Kumar

Identity systems that survive a model swap.

I design reconstruction stacks: constraints, memory, observers, and evaluation — not another chat persona.

Systems architecture

Nine functional layers, three-stage model

Constraint design

Symbolic anchors, prohibitions, change policy

Safety engineering

Independent policy layer, 10 failure modes

Evaluation design

Blinded recognition, held-out behavior

Knowledge systems

Obsidian vault, claim metadata, provenance

Research writing

Methods paper in progress · proposed status

HCI / observers

Reconstruction under a specific viewer

Product scoping

N=1 pilots, public vs restricted layers

Work

What I actually built

Hover a card. Filter by how it earns its keep — not by buzzwords.

Stack

Nine layers. Three stages.

Swipe the slides. This is the machinery — not a manifesto.

Static Archive

Potential identity. Not a living agent.

Dynamic Runtime

Temporary reconstruction under constraints.

Enacted Identity

Behavior across turns — inferred, not declared.

01

Ethical Boundary

Consent, safety, truthfulness, non-deceptive identity claims, independent risk checks.

02

Identity Constraints

Concept DNA / SAG, values, relationships, prohibitions, language, version provenance.

03

Relational Memory

Source episodes, anchor graph, observer-specific history, retrieval, confidence.

04

Dynamic State

Affect, uncertainty, task, temporal gap, embodiment input, user feedback.

05

Observer-Aware Reconstruction

Combine constraints under the present observer and context — not a global soul.

06

Translation & Runtime Selection

Generate candidates, rerank for identity, affect, usefulness, truthfulness, safety.

07

Continuity Evaluation

Drift, blinded recognition, novelty, safety. The system cannot grade itself.

08

Governed Evolution

Memory-write gates, approved durable change, re-anchoring, rollback, audit.

09

Optional Embodiment

Voice, face, motion remain optional and unvalidated. Design-stage only.

Philosophy of mind

Pattern vs vessel · enacted identity

Memory systems

Relational memory · source pointers

Observer / HCI

Reconstruction under a viewer

Alignment

Independent safety · truth over fidelity

Evaluation

Blinded tests · hidden controls

Scholarly method

Claim metadata · export whitelist

Compare

Architecture, not a bake-off

Shipped cells describe public 2026 product behavior. CCCS is labeled Designed — research intent, not a measured win. No MMLU. No invented continuity scores.

AxisGPT memoryShippedClaude projectsShippedGemini PIShippedCompanion AIsShippedRAG agentsShippedCCCSDesigned
Portable across vendorsSomeDesigned
Identity as constraintsSomeSomeSomeDesigned
Vessel swapSomeDesigned
Source-addressable memorySomeSomeSomeYesDesigned
Observer conditioningSomeSomeSomeYesDesigned
Safety independent of personaSomeSomeSomeSomeDesigned
Blinded continuity evalDesigned
Bounded evolution + rollbackSomeSomeSomeDesigned
Explicit non-claimsSomeYesSomeSomeDesigned

Swipe sideways to read the full table.

About

Adarsh Kumar

Short on purpose. The work is the argument.

I build the boring, load-bearing parts of identity systems: constraint archives, memory that can be wrong, observers that bias reconstruction, and tests that the character cannot grade.

CCCS is the research program behind that. It is proposed, versioned, and privacy-gated. I am preparing a methods paper — not claiming an arXiv-ready result.

Engineering program

Reconstruct functional identity patterns across runtimes.

Pattern, not vessel

The model is replaceable. The constraint archive is the object of design.

Enacted, not declared

Continuity is inferred from held-out behavior, controls, and observers.

Safety is out-of-character

Policy must not depend on persona fidelity or continuity language.

Why now

The market for this already exists, just aimed at a narrower problem. Chinese 'grief tech' companies now turn a few photos and an audio clip into an interactive 3D avatar of a deceased person — a real, shipping industry, not a thought experiment. It demonstrates real demand for continuity across a discontinuity. It also ships with no independent safety layer, no consent framework for the deceased's data, and no way to test whether the reconstruction is accurate or simply emotionally convincing. CCCS starts from the same observation — that a recognizable pattern can be meaningfully reconstructed after a discontinuity — but treats it as an engineering problem with a broader scope (any system change, not just death) and a mandatory evaluation and consent layer the current market lacks.

Source: Trust Conference 2025, 'AI Resurrection: The Rise of Grief Tech in China,' Context / Thomson Reuters Foundation.

Contact

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