Samuel, this hits small businesses even harder. A 10-person company can't afford a bad hire, and it usually has no technical interviewer to ask the follow-up question. The owner I'd want to hire for is the one who can explain what they'd do when the AI gets it wrong. That's still hard to fake. Have you seen any simple tests a non-technical owner could run?
That's a really good point, @Juan. I think small businesses actually have more reason to focus on this because they often don't have the luxury of multiple interview stages or dedicated technical assessors.
One simple approach is to give candidates a realistic, role-related scenario involving an AI-generated output and ask them to evaluate it. For example, a business owner could present an AI-generated customer response, business analysis, or report containing a deliberate error and ask: What would you check? What could go wrong if we acted on this? How would you handle it?
The interesting part isn't necessarily whether they spot every error. It's how they approach the problem, what questions they ask, whether they recognize the limitations of the output, and how they decide what needs human intervention.
I think that's a useful way to make judgment, rather than just familiarity with AI tools, part of the hiring conversation.
'Why did you choose that approach?' is the whole thing. AI can produce the artefact but not the judgement behind it. Same with leaders: trade-off thinking is the new signal.
Samuel, this hits small businesses even harder. A 10-person company can't afford a bad hire, and it usually has no technical interviewer to ask the follow-up question. The owner I'd want to hire for is the one who can explain what they'd do when the AI gets it wrong. That's still hard to fake. Have you seen any simple tests a non-technical owner could run?
That's a really good point, @Juan. I think small businesses actually have more reason to focus on this because they often don't have the luxury of multiple interview stages or dedicated technical assessors.
One simple approach is to give candidates a realistic, role-related scenario involving an AI-generated output and ask them to evaluate it. For example, a business owner could present an AI-generated customer response, business analysis, or report containing a deliberate error and ask: What would you check? What could go wrong if we acted on this? How would you handle it?
The interesting part isn't necessarily whether they spot every error. It's how they approach the problem, what questions they ask, whether they recognize the limitations of the output, and how they decide what needs human intervention.
I think that's a useful way to make judgment, rather than just familiarity with AI tools, part of the hiring conversation.
Great example. Thank you!
'Why did you choose that approach?' is the whole thing. AI can produce the artefact but not the judgement behind it. Same with leaders: trade-off thinking is the new signal.
Well said Ian 💯… And a professional’s ability to answer these questions highlights the level of mastery present.
It’s not just about solving problems. It’s about understanding why a specific solution should be chosen above other alternatives.
Exactly, Samuel. 'Why this and not that' is where real expertise shows, and it's the one thing AI can't fake for you yet.