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soyuz43/README.md

William Stetar

Systems Developer · Mechanistic Interpretability · Computational Epistemology

I build deterministic software, multi-agent environments, and computational frameworks for studying AI safety and scientific reasoning.

My work bridges abstract epistemic theory with practical systems engineering. I develop everything from fidelity-first physics sandboxes and automated developer tooling to adversarial LLM engines and hidden-state analysis probes.

Links

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  1. I-have-no-mouth-and-my-tokens-must-scream I-have-no-mouth-and-my-tokens-must-scream Public

    Persistent adversarial multi-agent LLM engine: one controller (AM), five agents, emergent psychological torment. Live inference, no exit.

    JavaScript 1

  2. ftype-audit-safe ftype-audit-safe Public

    Safe PowerShell tool for auditing and repairing Windows file type associations with backup, dry-run, and signature support.

    PowerShell

  3. holoplan-cli holoplan-cli Public

    A CLI tool that transforms user stories into Draw.io wireframes via multi-agent LLM reasoning. Chunks narratives into views, builds layouts, validates geometry, and outputs clean XML. Tech stack: G…

    Go

  4. DreamTracker DreamTracker Public

    DreamTracker is a full-stack web application for recording, managing, and reflecting on dreams. With features like tagging, favoriting, keyword filtering, and client-side caching via React Query, i…

    C#

  5. Regime_Detection_and_Transition_Invariance_in_High_Dimensional_Language_Mappings Regime_Detection_and_Transition_Invariance_in_High_Dimensional_Language_Mappings Public

    A pre-registered adjudication protocol to validate if behavioral partitions (e.g., withholding) are empirically stable regimes or prompt artifacts before mechanistic investigation.

    1 1

  6. input-conditioned-gain input-conditioned-gain Public

    This project measures how different system prompts (instruction vs. base behavior) alter hidden state geometry in Qwen2.5-7B. Using pre-extracted directional vectors (v*), I track linear separabili…

    Jupyter Notebook