Paper
Governed execution for AI systems working with private and licensed knowledge
Paper defining why AI needs explicit control over retrieval, permission, and downstream action when knowledge cannot be treated as open input.
Research and system notes from AnyMDL
Writing
Notes, papers, and essays on governed AI for private, licensed, and institutional knowledge.
Writing index
Papers
Essays
Essay
Why model output is not permission
Essay explaining why generation, access, permission, and action have to remain separate in real systems.
Essay
The case for licensed AI retrieval
Essay on bounded access, rights-aware retrieval, and why access to content does not automatically permit a response.
Essay
AI systems need execution boundaries, not just better models
Essay on why AI systems control depends on execution boundaries above the model layer and on permission before response, not on model quality alone.
Essay
Stateless models, paid output, and the missing layer of control
Essay on stateless AI models, token-based pricing AI, and why generation cost arrives before permission unless control exists upstream.
Essay
The difference between retrieval and use
Essay on AI retrieval vs use, and why access has to remain separate from permission and whether a response is allowed to exist.
Essay
Why AI access must be role-aware in institutional knowledge systems
Essay on contextual access, institutional boundaries, and why AI systems must preserve who is allowed to know what and whether they may receive a response at all.
Essay
Why AI systems cannot replace controlled reasoning in legal environments
Essay on legal AI risk, permission before response, and why persuasive output cannot replace controlled reasoning.
Notes
Note
Why AI access must be licensed
Note on how content owners retain control as AI systems expand their use of governed material.