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IN-DEPTH GUIDE · AI agents

Choosing an agent when a workflow is not a fixed script

An agent is useful when the next step depends on interpreted context. A fixed sequence remains simpler when the process is predictable.

Choose the simplest workflow that can handle the task

An agent uses interpreted context to decide which action to take next. That flexibility is useful when the path cannot be fully specified in advance, but it also makes behavior harder to predict. If every request follows the same sequence and the rules are explicit, ordinary automation may be easier to test and operate.

Describe the process without mentioning a model first. List its inputs, decisions, tools, external effects and finish condition. Mark which decisions are deterministic and which require interpreting varied language. You may discover that only one small stage needs AI, while validation and execution should remain ordinary application code.

Compare three implementation choices

Choosing an automation pattern
PatternUseful whenExample boundary
Rules and scriptsInputs and branches are predictableRoute a ticket using an explicit product field
Model-assisted stepLanguage interpretation is needed inside a fixed processSuggest a ticket category for review
Agent workflowSeveral possible next actions depend on findingsInvestigate a support issue using approved read-only tools

This is a design aid rather than a maturity ladder. A more autonomous system is not automatically better. Choose the pattern whose behavior the team can explain, verify and recover when something fails.

Worked example: investigating a support incident

Suppose an assistant can read approved service status, retrieve a troubleshooting guide and summarize recent errors for a staff member. The next tool depends on what it finds, so an agent may be useful. Initially, keep its permissions read-only. It can propose a restart or configuration change, but a person should approve consequential changes with the exact target and effect visible.

Give each tool a narrow contract. A status tool should return a structured service identifier, state and timestamp rather than arbitrary executable instructions. A write tool should validate identifiers and enforce authorization independently of the model. Do not rely on a prompt alone to prevent actions outside the user's permission.

Set a maximum number of steps and a clear escalation condition. If the assistant repeats the same failed lookup or cannot identify the affected service, it should stop and explain what is missing. Unlimited retries can create cost and duplicate actions without producing a better answer.

Test the outcome and the side effects

Evaluate complete tasks with normal cases, ambiguous targets, tool timeouts, incomplete responses and hostile instructions embedded in retrieved material. Check whether the final state is correct and whether anything unauthorized happened along the way. A convincing summary is not proof that the tools completed the work.

Use a test environment with synthetic records before enabling writes. For repeatable actions, design idempotency so that a retry can recognize work already completed. Retain enough history to distinguish attempted, completed and failed steps. Limit logs to information needed for investigation and apply an appropriate retention policy.

The OWASP discussion of excessive agency is useful background for permission and action boundaries. For practical next steps, read tool contracts, safe retries and failure simulation. Expand autonomy only when the evidence supports the specific new responsibility.

A practical starting point

Work through these checks in order. Use the results to decide what needs to change in your own workflow.

  1. Map the decisions that vary between cases.
  2. Identify which tools are genuinely required.
  3. Keep deterministic steps outside the model where practical.
ILLUSTRATIVE EXAMPLE

A research assistant may need to choose which approved source to inspect next, while a nightly export usually does not.

A mistake to avoid

Do not add autonomous planning to a stable process merely to call it agentic.

How to check progress

Compare task success, recoverability and operating effort with a conventional workflow.

Your action checklist

Use this checklist while reviewing your own setup. Checkmarks are temporary and stay in this open page.

Further reading

Official background resources for this topic. The workflow above is general guidance, not a guarantee of a particular result.

AI-assisted editorial content. Examples are illustrative, not client case studies. Read our editorial policy or report a correction.