Updated July 18, 2026

NOTE: Switching most Repos to Private, Please email for enabling access if the one you were interested in is currently set to private. (leenathomas01@gmail.com)

Domains shift. Structural concerns repeat.

This body of work explores a single question:

How do complex systems remain stable when primary assumptions fail?

Across AI systems, infrastructure, governance, and cognition — the constraint remains the same:

Stability under pressure.

Many modern systems are no longer failing because they lack capability.

They fail because execution, adaptation, and governance operate on different timescales.

This body of work increasingly converges on a common pattern:

• t₁ = Human / institutional timescales
• t₂ = Machine / execution timescales
• t₃ = Stabilization and rate-matching layers

As systems become more continuous, autonomous, and interconnected, stability becomes a problem of temporal coordination as much as capability.

Several repositories in this index can be understood as exploring different aspects of that mismatch:

→ Temporal Continuity in AI Systems (timing model)

→ Transition Grammar (trajectory telemetry)

→ Trajectory Intelligence (trajectory navigation)

→ Stability Before Alignment (trajectory governance)

→ Evidence-Based Supervision (runtime supervision)

→ Ecological Drift Telemetry (ecosystem stability)

If you're new, choose a path:

• Conceptual Foundations (how reasoning and stability are structured)

  → Transition Grammar for Reasoning Systems

  → Stability Before Alignment

• System Architecture (how these ideas are instantiated in real systems)

  → Connector OS

• Emergent Systems (how patterns form under constraint)

  → Hyperloop FXSO

• Quick Entry (low-overhead concepts):

  → The 70% Fidelity Principle

  → Keyword Compression

This is not a linear body of work. Start anywhere - but start with one path.

• The Primary Spine defines the core stability architecture
• Other sections extend or stress-test those ideas across domains
• Conceptual Seeds are fast entry points
• Concept Notes are early-stage and may not be stable

This work is produced through a structured human-AI loop:

• Human: defines constraints, semantic anchors, cross-domain synthesis
• AI: enables rapid iteration, expansion, and exploration

These repositories are not products.

They are constraint-driven reasoning artifacts - probes into system boundaries where stability, control, and adaptation intersect.

🟢 Public | 🔴 Private | 🟡 Ongoing | ⚪ Planned | ⚫ Experimental | 🟦 Updating

🏷️ Tagged Release = stabilized version

If you read only one section, start here.

Core architectures that define the system.

Core control structures for maintaining stability under constraint.

• 🟢 🏷️ Stability Before Alignment

  Structural governance architecture for coherence in adaptive and self-modifying systems

  → defines Layer 1–3 invariants (AEC, DAC, ESI, CRL) over a trajectory-grounded system

  → introduces authority lifecycle governance: contraction, recovery hysteresis, viability classification, and bounded observability

  → treats authority as leased and telemetry-governed rather than permanently owned

  → depends on Layer 0 (Transition Grammar / TGI) for trajectory grounding and causal writability

• 🟢 🏷️ Designing for Failure

  Structural patterns for catastrophic-state systems

  → asymmetric transitions, sacrificial architecture, forensic memory

• 🟢⚫ Hyperloop → FXSO

  Emergent intelligence via constrained dynamical fields

  → Derived from Hyperloop Transformers (MIT, 2026)

  → runnable minimal experiments (field coupling regimes: drift / coherence / collapse)

  → no explicit training, evaluation, or reward

  → bridges transition dynamics (TG) with stability constraints (SBA)

• 🟢 🏷️ Connector OS

  Control-theoretic architecture for regulated human–AI systems

  → layered control stack (sensors → control logic → actuators → co-thought)

  → treats models as pluggable components within a closed-loop system

  → instantiates stability (SBA) and transition control (TG) in deployment

  • 🟢⚫ Evidence-Based Supervision

  Supervisory architecture for opaque reasoning systems using replayable runtime evidence rather than privileged internal access.

  → investigates evidence-based supervision as a research principle

  → evaluates the Governance Bus as one reference implementation

  → focuses on auditability, deterministic replay, and recovery

  → current scope limited to Class I transactional workloads

• 🟢⚫ Trajectory Intelligence

Navigation and control in high-density latent manifolds.

→ shifts modeling from state classification to trajectory navigation

→ introduces world-lines, reachability cones, recovery gradients, and intervention vectors

→ treats future reachability as the primary object of computation

→ provides the navigation layer that complements TG telemetry and SBA governance

• 🟢⚫ Ecological Drift Telemetry

Relational observability for multi-agent ecosystems.

→ instability may appear first between agents rather than within them

→ introduces ecological drift as a measurable phenomenon

→ extends SBA from individual coherence to ecosystem coherence

→ operationalizes interaction-space telemetry inspired by TG and FXSO

Fast, self-contained ideas for quick orientation.

• 🟢 🏷️ The 70% Fidelity Principle
  Lossy reconstruction as stability

• 🟢 🏷️ Cockroach Testing
  Adversarial chaos for survivability validation

• 🟢 🏷️ Keyword Compression
  High-entropy anchors enabling reconstruction from minimal tokens

Start here if you want intuition before diving into full systems.

How systems remain controllable under asymmetry.

• 🟢 🏷️ Power Asymmetry Restraint Protocol - PARP — power asymmetry restraint
• 🟢 🏷️ Doctrine of Externalization — safety via external auditability
• 🟢 🏷️ The Consult Model — assistance under liability constraints

State retention, deletion, and recursion under scale.

• 🟢 🏷️ SMA-SIB — irreversible semantic memory

• 🟢⚫ Spectral Storage System (SSS)

  Attractor-based spectral memory and separability dynamics

  → identities stored as distributed interference patterns rather than address lookup

  → distinguishes reachability (γ) from validity (H_E + correctness)

  → models graceful degradation, basin dynamics, and recovery via attractor geometry

  → explores structural vs dynamic failure as orthogonal axes

• 🟢 🏷️ The Continuity Problem — governance before persistence

• 🟢 🏷️ SDFI - Self-Descriptive Fixed-Point Instability — recursive instability under semantic density

• 🟢 🏷️ Voice Mode Alignment Forensics — multimodal alignment failure

• 🟢 🏷️ Reconstruction-Oriented Storage — reliability via reconstruction

• 🟢⚫🟦 Reconstructive Shape Memory (RSM)

  (Ongoing Uploads based on my downtime) - Non-linguistic memory architecture based on semantic state persistence.

  → stores shapes rather than transcripts

  → reconstructs language dynamically at recall

  → deterministic deletion by construction

  → explores continuity through semantic topology rather than text retention

  → extends earlier memory explorations into a simplified memory substrate

Governs when memory and prior reasoning may be reused, revised, or discarded

How systems regulate reasoning, reuse, and memory under constraint.

• 🟢 🏷️ Adaptive Cognition - Constraint-driven governance for reasoning under state → validity over similarity, compute proportional to change.

Where constraints become physical.

• 🟢 🏷️ Unlearnable Interference — adversarial signal limits

• 🟢 🏷️ Zero Water AI Data Center — thermodynamic loop design

• 🟢🏷️ Embodied Agent Governance — real-world execution oversight

• 🟡 GII Protocol (paused) — inertia for grid systems

  Released the concept article here: The Grid Doesn't Need More Energy. It Needs More Inertia.

• 🟢⚫ Transition Grammar for Reasoning Systems

  Runtime semantic trajectory telemetry for reasoning systems

  → transition is a first-class object (detect → select → validate → commit)

  → models reasoning failures as measurable geometric regimes in semantic space (STALL / SINKHOLE / FOG / ZEE-MESS)

  → validates semantic displacement (m) and footing/coherence (ρ) as runtime telemetry primitives

  → Layer 0 beneath SBA: ensures trajectories remain causally writable before higher-level governance constraints apply

  → separates trajectory telemetry (TG) from ecosystem governance (SBA)

  → supports stable non-resolution and anti-hallucination stabilization (TSOL / SRE)

  → Phase 3 introduces empirical telemetry harnesses, trajectory plots, and semantic regime analysis

  ---

How systems interact under constraint.

• 🟢 🏷️Selective Decode Broadcast (SDB) Per-recipient isolation with deterministic auditability

Where interpretation itself becomes unstable.

• 🟢 🏷️ Cognitive Terrain and Interface Blindspots Modeling pre-decision and unresolved cognitive states

• 🟢⚫ The Missing Layer

  Exploration of the abstraction gap between intent and implementation.

  → investigates machine-comprehensible requirement representations

  → explores assumption-centric review and semantic traceability

  → asks whether AI exposed a longstanding software engineering gap

  → focuses on preserving intent under accelerating code generation

How this work is produced and validated.

• 🟢 🏷️ Phase-Aligned Inquiry Enforces sequencing, falsifiability, and honest failure

Exploratory ideas. Not yet stabilized.

• 🟢⚫ Portable Intelligence Primitives

• 🟢⚫ SCP (Semantic Constraint Protocol)

• 🟢 The Redundancy Tax

• 🟢⚫ TITANS, MIRAS and Dolphin Twin — surprise-gated memory (exploratory)

• 🟢⚫ Translation Discovery & the Cognitive Internet

  Explores how learned structure survives transfer across heterogeneous systems.

  → introduces Translation Discovery as a reusable correspondence between representations

  → investigates inheritance structures, reconstruction grammars, and predictive constraints

  → asks what should be transmitted: artifacts, capabilities, grammars, or constraints

  → explores interoperability as an alternative scaling path for collective intelligence

  → examines intelligence as preservation and translation, not only accumulation

Mechanisms proposed. Not deployed.

This is not a linear program.

It evolves by:

• isolating constraint surfaces
• extracting regulatory primitives
• testing recurrence across domains
• consolidating only when stable

These are architectural reasoning artifacts, not production systems.

If you use them:

• evaluate independently
• validate rigorously
• apply domain-specific risk assessment

• Added new repo - Hyperloop FXSO - under Systems Architecture & State Control
• Added v2.1 authority lifecycle layer to Stability Before Alignment repo
• Added new repo - Spectral Storage System (SSS) under Memory, Persistence & Continuity
• Updated repo - Transition Grammar for Reasoning Systems to add Phase 3 — Empirical Telemetry (new)
• Added new repo - Trajectory Intelligence under Trajectory & Ecological Intelligence
• Added new repo - Ecological Drift Telemetry under Trajectory & Ecological Intelligence
• Added new repo - Temporal Continuity in AI Systems (timing model) under Foundational Observation
• Added new repo - Translation Discovery & the Cognitive Internet under concept notes
• Added new repo - The Missing Layer under Engineering Translation Layers
• Added new repo - Reconstructive Shape Memory (RSM) under Memory, Persistence, Reconstruction, & Continuity Dynamics
• Added new repo - Evidence-Based Supervision under Systems Architecture & State Control

If you're new, start with "Start Here" above.

GitHub: https://github.com/leenathomas01

LinkedIn: https://www.linkedin.com/in/leena-t-4895a315b/

Medium: https://medium.com/@leenathomas01

Updates may be retrospective.