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​AI Fluency : The Next Interviewing Skill​

Algorithms needed for unpredictable journey. Significant compute costs, endless data processing, long periods of unexplained failures. Safe convergence doubtful. Honor & recognition in event of success.

What Shackleton might have written in 2025.

AI isn’t perfect but its productivity gains are undeniable. ServiceNow, Microsoft, and Amazon, plus nimble startups generating tens of millions in ARR with teams small enough to feed with a few pizzas all have benefitted.

The new boast of 2025? ARR per employee measured in the millions up 5x or more from the previous generation of software companies.¹ Fueled by AI.

Work examples are an essential part of an well-constructed interview & they evolve with AI :

• Use an AI to build an email client in an hour
• Research carbon sequestration and present an investment case with a presentation in an hour
• Write a legal brief on AI regulation and the impacts to unions in the next 30 minutes

At the same time, the candidate must manage potential for hallucinations & develop techniques to catch errors. OpenAI published research showing current models solve only about 25% of current real-world tasks.

Interviewers also face a new challenge: developing golden standards to evaluate AI fluency.

Will they run candidates’ code through dynamically generated unit tests? Will they feed legal briefs back into AI systems for cross-examination? The metrics for success are evolving as rapidly as the tools themselves.

Of course, this modern interview won’t exclude the other critical components of a high quality process, identifying characteristics of teamwork and sales skills or marketing expertise.

Recruitment has always been a competitive advantage, whether crossing the Antarctic or selling AI software. The difference between success & disaster is the right team.

¹ Contrast that with the $200-400k of public companies.

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