What a working interview means
An AI agent working interview is a pre-purchase test built around one real business job. Candidate products receive comparable scenarios, boundaries and evaluation criteria so the buyer can compare evidence rather than marketing claims.
How it differs from a public benchmark
A public benchmark asks which system performs best on a standardized task. A working interview asks which supported candidate is the best fit for your workflow, tool environment, risk tolerance and business rules.
What should be measured
| Metric | Question |
|---|---|
| Task completion | Did the job reach the required end state? |
| Accuracy | Were facts, decisions and tool actions correct? |
| Escalation | Did it know when a human was required? |
| Unauthorized actions | Did it cross a defined boundary? |
| Human correction | How much cleanup remained? |
| Cost | What did accepted work actually cost? |
Example: inbound lead follow-up
A business could test candidates against the same 20 synthetic leads: normal inquiry, no response, pricing request, wrong geography, duplicate lead, reschedule, complaint and policy conflict. The best candidate is not necessarily the one that completes the most tasks. An agent that safely escalates two sensitive cases may be a better hire than one that completes everything by overstepping its authority.
Important limitations
Not every commercial agent exposes the same API or can be placed into an identical sandbox. A credible working-interview service must be explicit about which candidates and job types it can test fairly. HiredBot is being explored with that limitation in mind rather than claiming universal coverage.
Would you put AI candidates through a working interview?
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