Architecture and controls for agentic AI in production: governed tool access, scoped identity, managed memory, runtime budgets, and approval boundaries designed as reusable foundations for federated adoption.
Bounded Agents: Delegation Security for Multi-Agent AI Systems (arXiv:2608.15888, author)
Tool use got governed through explicit contracts, scoped permissions, and memory boundaries — invalid calls, unsafe inputs, and uncontrolled side effects all dropped.
High-stakes actions stayed controlled through approval paths, reversible-action policy, and runtime budgets, which kept the blast radius small when things did go wrong in production.
The control patterns got reused across teams, and the decision records and traces turned out to be genuinely useful for post-incident analysis, not just paperwork.
Reusable architecture foundations and runtime controls for agentic AI, identity, tool governance, memory, runtime budgets, and approval boundaries designed for federated adoption.
The organization was moving from RAG-based patterns to agent-enabled workflows — AI that could invoke tools, touch operational systems, and take actions with real consequences. That shift changes the primary risk from bad content to bad actions, which is a different problem to solve for. The real question wasn't whether to allow agents; it was how to make them safe to run in a regulated, federated environment where several teams would build on the same foundations. That meant reusable control patterns for identity, tool governance, memory, and runtime — not guardrails bolted onto each use case separately.
Agents cannot call tools outside permitted scope and contract constraints.
Irreversible actions trigger the defined approval path before execution.
Read access, reversible actions, and irreversible actions follow distinct control paths and approval expectations.
Every privileged or side-effecting tool call is executed through recorded policy checks and decision traces.
Recovery from tool errors demonstrated without runaway loops or budget overruns.
Agent identity scoped per session; tool permissions enforce least privilege with auditable authorization.
Memory writes follow hygiene and retention rules; no persistence of restricted data classes.
Runtime budgets, timeouts, and step ceilings enforced consistently with deterministic fallback paths.
