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  • Blackglass Continuum
  • Aurora, Colorado

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ZoaGrad/README.md

Blackglass Continuum - Deterministic Runtime Assurance

Blackglass Continuum builds deterministic runtime assurance, hardware safety boundaries, and audit-grade evidence systems for autonomous agents and mission-critical infrastructure.

The work is aimed at systems that now act: AI agents, autonomous workflows, robotics-adjacent runtimes, and high-variance infrastructure. The emphasis is not "trust the model." The emphasis is measurable control behavior, explicit claim boundaries, and evidence that can survive external review.

Evidence Snapshot

Claim Anchor Boundary
Hardware arbitration-cycle timing 0.31 ms Measured sealed baseline only
GPIO interdiction response 420 ns DSLogic CH0 to CH1, event 131
GPIO pulse width 50 ns Event pulse duration only
Governance threshold 0.05V Tri-state variance gasket
Synthetic persistence validation F1 = 1.000, 0 FP, 0 FN across 5,000 scenarios Synthetic validation, not bench timing
Federal posture CAGE 17TJ5, SAM active, SPRS 110/110 Verify live before submission
Patent anchor U.S. provisional 63/992,753 Utility/PCT deadline 2027-02-27

Public Systems

System Purpose
Coherence SRE Read-only deterministic anomaly detection for high-variance infrastructure
Air-Node Finite-state incident recorder for agentic workflows
Sovereign Reliability Lab Generated evidence and cold verification under stochastic network conditions
Blackglass Dojo Adversarial simulation harness for AI-agent drift and guardrail failure modes

What Blackglass Claims

  • Deterministic runtime assurance can be measured, bounded, and audited.
  • Agentic systems need pre-action control, not only post-hoc logs.
  • Generated evidence beats authored evidence.
  • Hardware-isolated veto paths can strengthen software-only governance.

What Blackglass Does Not Claim

  • It does not claim solved AI alignment.
  • It does not claim deployment at a federal site.
  • It does not migrate old timing claims onto modified firmware.
  • It separates measured bench evidence, synthetic validation, design intent, and future work.

Current Focus

  • DARPA DICE: local inference control for role-coherent agent collectives
  • Verification harness: C-vs-Python differential oracle with generated run logs and SHA ledger
  • Watchdog path: hardware timer ISR veto, requiring new BGC-BM-RUN-002 captures
  • Demo shield/interposer: prime-readable hardware-in-the-loop evidence artifact

Contact

Blackglass Continuum LLC
Aurora, Colorado
colemanwillis@blackglasscontinuum.com

Pinned Loading

  1. ZoaGrad ZoaGrad Public

    Prime-facing profile README for Blackglass Continuum runtime assurance and evidence systems.

  2. air-node air-node Public

    Finite-state incident recorder for agent workflows: transition validation, forensic drift detection, and replayable audit trails.

    Python

  3. blackglass-dojo blackglass-dojo Public

    Adversarial simulation harness for AI-agent drift, guardrail failure modes, and 0.05V-style runtime interdiction.

    Python

  4. coherence-sre coherence-sre Public

    Read-only deterministic anomaly detection for mission-critical infrastructure using variance, allocation velocity, and amplification signals.

    Python 3