Books, tools, music systems, and governed AI code work
Zadeo
A home for Michael's creative systems: published books, Elysium Beat Station, and the coming ZadeoOS project.
Explore Now
Official links for people who saw the shirt and want to know what Zadeo is building.
What Makes ZadeoOS Different
ZadeoOS is being built for autonomous code work that stays accountable.
- Local-first control The operator stays in charge of the workspace, files, and approval boundary.
- Receipts before trust Important actions are backed by evidence records instead of vague claims.
- No silent apply Planning, review, and patch application are separated so code does not move without permission.
- Autonomy with boundaries Agents can inspect, plan, and prepare work while deployment, credentials, services, and promotion stay gated.
- Continuity for real projects ZadeoOS is designed to remember proof, context, rollback plans, and next actions across a build.
EMRESET
EMRESET is part of a diagnostic and governance framework at Zadeo. It runs a continuous read on twelve indicators of structural decay in a system, split across two tiers: load-bearing warning signs such as deception, betrayal, and erosion of will, and systemic signs such as unchecked complexity, displaced authority, and breakdown of institutional memory.
When systemic indicators cross threshold, the system enters a strict authorization state. Escalation can be requested, but it cannot be forced open by anyone in the loop. Lucid Drill then takes over as a phase-based correction sequence: contain, correct, restore. The goal is to drive a decaying system back to baseline faster and more reliably than manual intervention would, without letting the process stall halfway.
The demo is interactive. Use the day slider and intervention toggle to watch the architecture respond live. Nothing on the page is pre-recorded.
Honest boundary: this is the architecture in action, not a clinically validated instrument. Clinical validation is a separate track of work. The current capability is catching decay before failure and enforcing correction through completion.
We are actively looking for companies, offices, physicians, and domain operators willing to review the model and tell us where it does or does not map to real operational failure patterns. The same architecture is intended for AI oversight, insurance risk underwriting, federal program integrity, and health-adjacent monitoring as that track matures.