01
One-sentence definition
It does more than answer questions; it can use tools to advance a controlled workflow.
02
What problem it addresses
It fits repetitive, describable and verifiable processes, but requires clear permissions, exception handling and human oversight.
03
Fit and non-fit
Good fit
- Repeatable, rule-bounded workflows spanning multiple tools
- Teams able to set permissions, exception handling and human takeover
Not a fit
- Tasks with vague goals, shifting rules and unverifiable outcomes
- Unsupervised autonomy in high-risk environments
04
Prerequisites
Clear task, success and stop conditions
Tool permissions, data scope and audit requirements
Evaluation set, exception handling and human takeover
05
Inputs and outputs
| Inputs | Outputs |
|---|---|
| Workflow steps and decision rules | Agent workflow and responsibility boundaries |
| Tool, knowledge and permission configuration | Evaluation, logs and exception records |
| Test cases and risk scenarios | Launch, rollback and human-takeover plan |
06
Standard steps
Research organization
Drafting and review routing
Monitoring summaries and internal Q&A
07
Decision criteria
Models, tools and instructions form the system
Permissions and data boundaries must be explicit
Keep logs, evaluation and human takeover
08
Common failure modes
An agent is simply a chatbot
Connecting more tools is always better
No ongoing evaluation is needed after launch
09
Metrics
Task completion rate
Share of tasks completed correctly within defined conditions.
Human takeover rate
Share requiring human intervention due to uncertainty, exceptions or risk.
Severe errors and permission breaches
Incorrect execution, data exposure or actions outside authorized scope.
10
Case anatomy
From suggestions to controlled execution
Context
A team wanted to automate repetitive work, but incomplete inputs and exceptions were common.
Approach
Task boundaries and evaluations were defined first, tool permissions were expanded gradually, and human confirmation remained before critical actions.
Key lesson
An agent is defined less by tool count than by reliable completion within boundaries.
11
Tools and templates
12
Revision history
Version 2.0
2026-07-15
Upgraded to a deep knowledge unit with fit boundaries, inputs and outputs, metrics, a case and claim-level evidence.
Related terms
Evidence and sources
OpenAI
2026-07-15
A practical guide to building agents
This source supports: Agent design across models, tools, instructions, orchestration and human oversight.
U.S. National Institute of Standards and Technology
2026-07-15
AI Risk Management Framework
This source supports: A general framework for governing, mapping, measuring and managing AI risk.
Cyberspace Administration of China and other authorities
2023-07-13
Interim Measures for the Management of Generative AI Services
This source supports: Governance, content, data and accountability requirements for public generative AI services in China.