Project Description

Unlike conceptual alignment proposals, this project includes a working governed-execution runtime that demonstrates measurable containment under adversarial prompt pressure.

The system does not modify model weights or rely on probability conditioning. Instead, it externalizes structural logic and enforces explicit execution contracts at runtime.

The system defines:

• What forms of output are admissible

• What must be refused

• When execution must halt

• How violations are recorded and preserved

Under adversarial testing, the runtime activates safe-mode containment after contract violations, flags hallucination patterns, and generates structured JSON evidence logs comparing baseline, governed, and hybrid configurations.

The objective is not to change model cognition, but to make model behavior observable, bounded, and auditable.

This produces machine-verifiable artifacts that can be used for:

• Technical AI safety research

• Governance experimentation

• EU AI Act–style compliance frameworks

• Alignment benchmarking

Goals

This project has three concrete goals:

1. Develop a model-agnostic admissibility evaluation layer

2. Produce reproducible stress-test artifacts across multiple model configurations

3. Package results into audit-ready documentation usable for governance and safety evaluation

Execution plan:

• Run structured stress tests (baseline vs governed vs hybrid)

• Measure containment under adversarial ambiguity prompts

• Generate structured evidence logs (JSON + performance metrics)

• Produce standardized evaluation artifacts (PDF + raw logs)

Use of Funding

Funding will support:

• Cross-model testing (Gemini, Claude, OpenAI APIs)

• Compute costs for structured stress testing

• Refinement of admissibility constraint engine

• Artifact standardization for external evaluators

• Independent review and iteration

Minimum funding enables:

• One full model evaluation package with artifact release

Full funding enables:

• Multi-model comparative report

• Extended adversarial stress testing

• Public methodology documentation

• Independent technical review

Team & Track Record

Nicholas Evans
Founder, Operational Systems Group LLC

• Built working governed-execution prototype

• Designed explicit admissibility constraint architecture

• Produced stress-test artifacts comparing baseline vs governed configurations

• Focused on operational containment rather than weight modification

This project is currently solo-developed.

Failure Modes

Most likely risks:

• Limited compute for cross-model validation

• Low early adoption of artifact format

• Misalignment between technical evidence and funder expectations

Even in failure, the project produces:

• A structured evaluation methodology

• Artifact-based LLM testing framework

• Reproducible containment logs for future research

Funding History

$0 external funding raised in the last 12 months.
Project has been self-funded.