AI Agents
AI Agents explained
A text draft is an output. An agent workflow may also find relevant information, identify missing details and select another processing step. What is possible and permitted depends on the application. Calling something an agent does not establish reliable competence.
The goal, data access and tools need to fit together. A system may be allowed to read a file without changing it. Creating a draft and publishing it are different actions too. Reflect these boundaries in technical permissions and the interface.
Check the result beyond the agent’s response. If it reports updating information, the correct change should be verifiable in the correct place. Repeated calls should not silently create duplicate actions. Uncertain states need a defined recovery route.
Value may come from fewer manual handovers and better prepared results. Setup, review, error handling and operation also require work. Compare the complete process with a simpler alternative rather than treating autonomy itself as success.
Examples
Hypothetical application
An agent checks a brief for missing required information, searches approved product material and creates a supplemented draft. The team sees sources and open questions. The agent may save the draft but cannot email customers; the saved version is checked at its destination.
Key Points
- Capability and permission are different questions.
- Connect the request, available information and actual outcome.
- Actions that change data need clear boundaries.
- Include total effort and error handling in assessment.
Practical application
Start with a bounded task and describe its verifiable final state. Define permitted tools, data and handovers. Trial typical cases plus missing information, tool failures and repetition before everyday use.
Useful measures
Completed tasks
Share of test cases achieving the previously defined final state.
Unintended actions
Incorrect, duplicate or unauthorised changes and their consequences.
Total effort
Time and cost including interventions, corrections and maintenance.
Common mistakes
- Presenting an agent categorically as an independently working employee.
- Equating read access with permission to edit or publish.
- Checking only the final response instead of the achieved state.
Sources and context
- Anthropic: Building effective agents
Technical distinction between predefined workflows and model-directed processes; not a general performance guarantee.
- Anthropic: Demystifying evals for AI agents
Assessment of agents through defined tasks and actual outcomes.
Frequently Asked Questions about AI Agents
No. A chatbot may only generate replies. An agent workflow may also select further steps and use tools. Terminology varies, so assess the actual functionality.
No. Predefined flows, bounded decisions and model-directed steps can be combined. Match the available discretion to the task and the consequences of errors.
Check the agreed final state in the relevant system or document. A completion message, planned step and successful tool call each provide only part of the evidence.
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