A practical guide from DigiMartrix. Use it to frame the decision, make trade-offs visible and choose a next step that fits your context.
Use the least complex system that works
A fixed sequence of predictable steps may be best handled by ordinary software automation. A conversational assistant can help when people need to ask varied questions over trusted information. An agent is more relevant when a system must choose among tools or steps based on the task and its current context.
Check that the task is bounded
Define the agent’s goal, allowed tools, data scope, stop conditions and maximum number of steps. The task should have a way to verify its result. If success is subjective or the action is hard to reverse, keep a person responsible for the decision.
Put controls around every tool
Enforce authorization in the service that performs the action, not only in the model prompt. Validate parameters, restrict the records and actions available, rate-limit execution and record a useful audit trail. Treat external content as untrusted input.
Use approval for consequential changes
Sending communications, changing customer records, spending money or making commitments should have explicit review and confirmation appropriate to the impact. Give operators a way to inspect the proposed action and stop the workflow.
Test failure as well as success
Evaluate wrong tool selection, malformed results, unavailable services, conflicting instructions, duplicate requests and partial completion. Make retries idempotent where possible and explain when the task needs a person.
Decide from evidence
Compare task completion, error severity, review time and ongoing operating effort with a simpler baseline. If the agent cannot outperform the simpler approach under the agreed safety limits, do not add autonomy.