How to choose an AI agent without buying the demo
A decision framework for comparing AI agents on control, evidence, recovery, and fit with your actual workflow.
Choose the autonomy boundary first
The best agent is not necessarily the one that takes the most actions. It is the one whose autonomy matches the consequences of your work. Drafting a document, editing a production database, and sending a customer message require different approval boundaries.
- Which actions can it take without confirmation?
- Can permissions be limited by tool, project, or environment?
- Does it distinguish reversible edits from high-impact changes?
Demand an inspectable work trail
A strong agent leaves enough evidence for you to understand what happened. Look for focused diffs, test results, source links, tool-call history, and a clear explanation of anything it could not verify.
The work trail matters more than a confident summary. If the result is wrong, evidence determines whether you can diagnose and recover quickly.
Measure recovery, not just first-pass success
Give each candidate the same realistic task and include one controlled complication: a failing test, missing permission, ambiguous instruction, or stale document. Compare how each agent notices the problem, asks for help, and preserves work already completed.
- Time to a verified result, not time to the first answer.
- Number of manual corrections required.
- Quality of rollback or recovery when a step fails.
- Clarity about uncertainty and remaining risk.
Rate the workflow you actually experienced
After the trial, record the use case, the model or tools involved, the failure you encountered, and whether you would use the agent again for the same job. That review will be more valuable than a generic list of features—and easier for another user to compare with their own needs.