A useful agent example describes a task and its boundaries, not just an industry. Each pattern below includes inputs, tools, outputs, metrics and the main risk.

Support triage

The agent reads a request, queries account history, identifies intent and routes to the correct flow. Financial changes wait for approval. Measure correct resolution, transfer, time and reopened cases.

Research with sources

The agent turns a question into searches, retrieves permitted documents and produces a linked synthesis. Measure source coverage, citation accuracy and unsupported claims.

Operations and incidents

The agent queries alerts, logs and runbooks, proposes a diagnosis and performs only authorized reversible actions. Measure time to diagnosis, accuracy and worsened incidents.

Product feedback analysis

The agent groups feedback, links claims to evidence and relates themes to metrics. The output must retain a path to original excerpts. Measure grouping accuracy and revised conclusions.

Software engineering

The agent reads a bounded task, edits code in isolation, runs tests and prepares review. Measure test success, regressions and human acceptance. Do not grant unrestricted production or secret access.

Choose a frequent, reversible and measurable first task with clear tools. Use the AI agents guide to choose a pattern and the evaluation template to compare alternatives.

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AI Agents

Understand, build, evaluate and operate AI agents with clear goals and boundaries.

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