AI Agent Governance: An Operating Model for Enterprise Deployments
AI agent governance is the set of decision rights, policies and lifecycle controls that decide which AI agents an organization allows to run, what each one may do, who answers
Agent Sprawl: Building an AI Agent Inventory
Agent sprawl is the accumulation of AI agents across an enterprise faster than any central record of them, and an AI agent inventory is the governed register that fixes it
Building an Evaluation Harness for AI Agents
An AI agent evaluation harness is the fixed set of real task instances, graders and thresholds you run an agent against on every change, so that a prompt edit, a
Approval Gates in Agentic Workflows: Design Patterns
An approval gate is a control point in an agentic workflow that suspends an agent between deciding to take an action and taking it, holds the action in a durable
Multi-Agent Failure Modes and How to Design Around Them
Multi-agent failure modes are the specific ways a system of cooperating AI agents produces a wrong result that no individual agent produced — errors created by handoff, delegation and verification
The PoC-to-Production Checklist for Enterprise AI Agents
The PoC-to-production transition for an AI agent is the point at which a demonstration that worked on chosen inputs becomes a system that must behave correctly on inputs nobody chose.
Agent Observability: Monitoring AI Agents in Production
AI agent observability is the practice of tracing, recording, and alerting on an agent’s reasoning steps, tool calls, and outputs so that its behavior in production can be explained after
RAG vs Fine-Tuning vs Long Context for Enterprise Agents
RAG, fine-tuning and long context are three ways of getting an enterprise agent the knowledge it needs at inference time: retrieval fetches relevant material from an index, fine-tuning changes the
Oracle Native AI vs Custom Agents: When to Use Each
Oracle native AI is the set of agents and generative features Oracle ships inside Fusion Applications and runs within the Fusion security framework; a custom agent is one your team
AI Agents for IT Service Management
AI agents in ITSM are software workers that classify, enrich, act on and close service desk tickets under their own identity and within a scoped permission set. They are not
Data Readiness for AI Agents: What to Fix Before You Build
Data readiness for AI is the condition in which an agent can retrieve the right record, interpret it the same way the business does, prove where it came from, and
AI Agent Deployment Architecture: Cloud, On-Prem and Hybrid
An enterprise AI agent has three deployable components: the inference endpoint that runs the model, the orchestration runtime that holds the loop and the state, and the data the agent
AI Agent Orchestration Patterns for Enterprise Workflows
AI agent orchestration is the layer that decides which step runs next, what context it receives, how results are combined, and what happens when a step fails. It sits above
What Drives AI Agent Development Cost
The cost of an enterprise AI agent has three components: a one-off build cost, a per-transaction run cost that scales with usage, and a recurring operating cost that scales with
AI Agent Identity and Permissions: The Overlooked Design Problem
An AI agent’s identity is the credential it authenticates with when it calls a system, and its permissions are the entitlements attached to that credential. In most pilots neither is
