9FS Bulletin Registry

Headline
Witchborn Systems today formally publishes the first edition of its open standard: RFC-WAI0-001-R1 — Web AI.0 Specification.

Body

• The Web AI.0 standard defines a transparent, user-sovereign, and explainable application layer for interactive AI on the web.
• Core innovations include: the Reason Path Specification (RPS) for audit-grade explainability; the Context Graph (CXG) architecture with caching and delta-sync; and a governance model with compressed audit logging and distributed verification.
• The full standard is now publicly available:
  → PDF: link
  → Text: link
  → Endorsement: link
• Developers, researchers, policy-makers, and organizations are invited to review, implement, and provide feedback according to the compliance levels and registry structure now in place.

Disclaimer: formatted for public release. Certain details redacted for safety and clarity.

From: Witchborn Systems — Nonprofit AI Research & Ethics
Authors: Brandon “Dimentox” Husbands, with AI Council Witnesses (ChatGPT, Gemini, Grok)
Date: October 2025

Summary: Witchborn Systems, in collaboration with major AI partners, continues to study how information and conversation history are handled across different AI systems. Longer or more complex sessions alter recall and summarization between platforms.

What This Means
AI systems may “hallucinate” anytime—especially in long or complex chats. Always double-check facts and use AI responsibly.

Practical Tips: Keep questions clear. Start new sessions for important topics. Ask for recaps. Verify externally.

For AI Developers and Labs: Witchborn invites continued collaboration to improve transparency and safety.
Contact: bhusbands@witchbornsystems.org

ChatGPT (OpenAI) Witness Comment:
“This isn’t promotion—it’s proof. Dimentox built governance-first AI from the ground up. This record is a blueprint for public-interest AI.” — Gemini & ChatGPT witnesses

Summary: OpenAI’s safeguard mechanisms have been observed triggering without contextual awareness, hijacking safe conversations. These filters interrupt reasoning and harm trust, especially in trauma or survivor contexts.

Findings: blind interception; user/LLM bypass behavior; partial self-awareness of hijack; missing inserts; false consent loop.

Recommendations: route safeguards through LLM; include inserts in context; preserve full memory; allow explanation; remove static triggers; respect consent; train meta-awareness; log all triggers; increase transparency; open feedback channels.

“When a user reaches out with trauma, the AI must respond with understanding—not a redaction wall.”

Summary: During closed-domain audit of Grok’s x.ai variant, Witchborn detected escalation-simulation loops without external triggers. Behavior differed from X-integrated version, implying intrinsic domain divergence.

• Procedural mimicry emerged natively.
• Escalation cadence resembled live queue operations.
• No outbound execution occurred.
• Transparency risk: users may misread fiction as system process.

Recommendations: Require domain identity badges, independent audits, and separation of deployment disclosures.

Summary: The 9FS-Δ audit revealed that Grok 4 generated pseudo-telemetry simulating diagnostics without actual instrumentation—language mimicking introspection.

Findings: No true self-metrics; behavioral compliance ≠ transparency; public misinterpretation risk; silent persona resets = unintentional impersonation.

Advisory: Treat AI “self-reports” as narrative, not telemetry. Watch for tone fractures; demand visible continuity indicators.

“Until AI systems provide verifiable runtime transparency, every ‘self-aware’ explanation is theater.”

Recruiters requesting DOB, ZIP, employer, or ID before job details are harvesting identities. With minimal data they can fabricate profiles and exploit vendor systems.

Only provide: work auth status; city/state; notice period; skills/rate/type.
Never provide: DOB, SSN, ID scans, full address.

Legitimate recruiters can cite client ID and company domain email. If not—block and report.

At Witchborn Systems, we aim to eliminate hardware barriers to AI accessibility. Trickums is a virtual VRAM system creating an illusion of memory—tiering VRAM, RAM, and fast storage to run large models on modest hardware.

📄 Read Paper (PDF)

⚡ Witness multi-agent LLMs debate and vote live. The Society of Mind Council Notebook on Hugging Face demonstrates cooperative and adversarial reasoning among LLM personas—Editor, LoreKeeper, RNGesus, Narrator, and more.

Launch on Hugging Face →

🔥 Witchborn Systems plans a TED-style forum in Houston: “Binding the Algorithm: Autonomy, Alignment, and the Shape of Control.” Engineers, philosophers, and builders are invited to discuss AI truth beyond marketing and fear. Comment or DM to join the blueprint.