Why AI-First Companies Are Desperately Hiring Humans Like Me
Beyond the Algorithm: The $200K Job That Exists Because AI Isn't Enough
Last week, I told the story of the last recruiter and how her work was slowly taken over by automation and AI. This week I have good news: she got a new and even better job. This is how.
I am Alice, and this is the story of how I thrived after my old skills and job became obsolete.
What I am doing and why I’m in demand
I sit in a sun-drenched studio that does not feel like an office. Across from me is Leo, a brilliant quantum-computing engineer. He aced every AI assessment. His technical scores are perfect. The hiring system has already recommended him for a role at a top R&D firm. By algorithmic logic, he should be receiving an offer—not sitting here with me.
But he is here because of a 0.03% anomaly. The system’s sentiment analysis of his video interview detected a “micro-expression cluster” consistent with high-functioning anxiety and a potential aversion to unstructured collaboration. The model flagged him as a “high-skill, high-attrition risk.”
The company does not want to lose him. They need me to make a decision.
“Leo,” I say, calm and friendly, where the AI is clinical. “The system says you’re brilliant. It also suggests you might hate working here.”
He freezes, then laughs nervously. “It said that?”
“Not in those words. But that’s the gist. I’m here to find out if it’s right—or if it’s missing something.” I do not look at a screen. I watch him.
I am in demand because the AI is excellent—and its excellence is the problem. It can find the objectively best candidate for a specification. But, it cannot grasp the messy, subjective, human reasons a person might want a job or why a company might need a particular human, flaws and all.
Companies soon discovered a fatal flaw in AI agents: their algorithms were optimized to eliminate risk. They found safe, competent, predictable candidates. They struggled to find the wildcards—the gems who do not fit the pattern, the innovators whose greatest strengths are often the inverse of their weaknesses. The AI-built symphony orchestras were technically perfect, but no one played with emotion or composed new music.
How I got here
As soon as I walked out the door from my previous employer, I was already prepared for the next step. I had seen the writing on the wall. While colleagues complained and feared AI and automation, I had enrolled in courses