Cycles Guides
Long-form guides covering the enforcement dimensions of runtime authority for AI agents. Each guide is a map — a short orientation per subtopic that links into the deep coverage. Read top to bottom for a structured view, or jump to whichever section matches what you are working on.
The enforcement dimensions of runtime authority
Cost, action, and tenancy are different enforcement problems. Cost controls how much an agent can spend. Action authority controls what it is allowed to do. Multi-tenant operations control who owns which budget and how isolation holds up under shared infrastructure. Most real production incidents touch at least two of the three.
- LLM Cost Runtime Control Reference — bounding what AI agents spend. Causes of cost blowups, why dashboards are not enough, the runtime patterns that work, unit economics, and provider-specific patterns.
- AI Agent Risk & Blast Radius Reference — bounding what AI agents do. Risk scoring, action authority, blast-radius containment, degradation paths, delegation chains, governance frameworks, and incident patterns.
- Multi-Tenant AI Operations Reference — bounding who owns which budget. Scope hierarchy, per-tenant enforcement, multi-agent coordination, tenant lifecycle, identity and keys, cross-platform tenancy, and the failure modes specific to shared infrastructure.
A guide on audit / evidence — the byproduct dimension that compliance and post-incident review build on — is in development.