AMR
A research program for connecting AI agents to controlled machine interfaces while preserving observability, permission boundaries, and recoverable execution.
Many real workflows happen outside clean APIs. AMR studies how agents can interact with operational software without losing auditability or control.
Problem Space
Useful software often lacks clean APIs, while direct automation can become brittle, opaque, or unsafe without supervision and recovery boundaries.
System Direction
AMR explores observable interaction layers, controlled execution surfaces, and recovery-aware operation across real software workflows.
Public Capabilities
- 01Controlled software interaction research
- 02Observable execution paths
- 03Permission-bounded operation
- 04Recovery-aware workflow design
- 05Human-supervised runtime patterns
AMR is publicly described as controlled runtime research. Specific software targets, internal adapters, and implementation mechanics are not disclosed.
What Is Not Disclosed
Private implementation details, security-sensitive internals, and unreleased runtime architecture are intentionally not disclosed.