Source note
Operational Readiness Criteria for Tool-Using LLM Agents
Summary
This paper proposes a deployment readiness model for tool-using LLM agents. It focuses on how to decide when an agent is safe and reliable enough for delegated autonomy in real operations.
Problem
- Teams can build tool-using LLM agents, but deployment decisions often lack clear criteria for capability, autonomy, auditability, and rollout control.
- This matters because agents that call tools and act with delegated authority can cause operational, security, and compliance failures if they are released without structured checks.
- The paper targets the gap between agent demos and production operations.
Approach
- The core method is a practical readiness model: define explicit criteria that an agent must meet before it gets more autonomy.
- It organizes deployment around capability tiers, autonomy budgets, readiness scorecards, audit requirements, evaluation harnesses, and phased rollout gates.
- Capability tiers classify what kinds of tasks and tool use an agent can handle.
- Autonomy budgets set limits on how much independent action an agent can take.
- Scorecards, audits, and evaluation harnesses give operators a way to test and document readiness before broader deployment.
Results
- The excerpt does not report quantitative benchmark results, test metrics, or head-to-head baseline comparisons.
- The main concrete claim is that the work provides a practical readiness model for deploying tool-using LLM agents.
- It claims to include six operational pieces: capability tiers, autonomy budgets, readiness scorecards, audit requirements, evaluation harnesses, and phased rollout gates.
- The release is published as version 1.0 on March 25, 2026.
- The work is accompanied by an active public software repository:
rogelsjcorral/agentic-ai-readiness.