Evaluating Talent in the Age of AI

What Skills Should You Hire?

At one point, hiring someone who could do basic math in their head was crucial. Cashiers needed to calculate change and count it back without error. Then came 10-keys, and accountants needed lightning-fast data entry. Spreadsheets rendered those skills unnecessary. As technology evolves, so too do the skills we need from employees. Yet, many hiring managers and organizations are stuck in time, evaluating candidates with criteria that no longer matter.

It’s time to rethink what we’re hiring for.

The Skills of Yesterday

In software development, we’ve seen this play out repeatedly. In the 2000s, knowing the difference between public and protected in Java might have impressed an interviewer. A decade ago, solving coding challenges on a whiteboard with algorithmic precision became the gold standard. Today, asking a candidate to regurgitate trivia or write bubble sort from memory is about as relevant as testing a CFO on her ability to add columns of numbers in her head.

Why? Because technology has shifted the landscape. Google has democratized access to knowledge, and now AI can write code, design systems, and debug errors. The rote skills that once defined a good hire are no longer the competitive edge they once were.

The Age of AI and the Star Trek Parallel

One of the most fascinating aspects of AI today is how eerily similar it feels to interacting with the computer from Star Trek: The Next Generation. At first glance, the constant questions the crew asked their computer seemed like a narrative device—a way to make the story interesting rather than have an all-knowing machine solve every problem instantly. But perhaps the writers were more prescient than we realized.

The Star Trek computer didn’t just spit out answers—it worked alongside the crew’s intuition, expertise, and creativity. It needed prompts and insight. It couldn’t replace Captain Picard’s strategic thinking or Data’s moral calculus. Similarly, today’s AI requires human users to provide abstraction, iteration, and, most importantly, direction.

The New Core Competencies

AI can generate code, diagrams, videos, or even entire business plans, but it doesn’t inherently understand why something is being done or what the ultimate goal is. This is where humans—and the skills we need to hire for—come in.

Here are the new skills worth hiring for:

1. Vision and Motivation AI doesn’t care about solving your business’s challenges; it lacks a sense of purpose. Your employees need to supply that vision. They must articulate nuanced goals, understand the market, and set a direction that aligns with your organization’s values.
2. Guiding Iteration AI operates within the bounds of its context. It’s limited by its training data, the prompt it receives, and its inability to grasp the full complexity of human intention. Employees must bridge that gap, guiding AI through iterative refinement to achieve the desired results.
3. Critical Evaluation AI makes mistakes. It can hallucinate falsehoods, misinterpret subtlety, or produce output that only looks correct at first glance. Employees must possess the expertise to spot errors, verify results, and refine outputs.
4. Adaptability to Evolving Tools Tools and technologies come and go, but the ability to learn, adapt, and leverage new tools effectively is timeless. Candidates who are curious, eager to experiment, and quick to grasp new methodologies will outpace those stuck in rigid processes.

Why Your Hiring Process Might Be Failing

When companies evaluate candidates, they often cling to outdated metrics: rote knowledge, low-level skills, or even tasks that AI can now handle better and faster. This approach has two significant flaws:

1. It Filters for the Wrong Candidates You might hire someone who can solve coding puzzles but has no intuition for navigating real-world challenges. Worse, you’ll miss out on candidates with the strategic and abstract thinking skills you actually need.
2. It Ignores the Shift in Work The skills required to succeed in modern software development—or any knowledge work—are no longer about execution alone. They’re about setting up the problem correctly and managing the output intelligently.

What You Should Be Looking For

Let’s say you’re hiring a software engineer. In the past, you might’ve asked them to implement an algorithm or explain a technical concept. Today, the better questions might include:

• How do you guide AI to achieve complex goals?
• How do you verify the results AI generates?
• How do you balance using AI with your own expertise?

These questions aren’t about whether someone knows the syntax of a particular language or remembers a design pattern off the top of their head. They’re about whether they can wield modern tools effectively and critically.

There’s an ongoing discussion in software development about the tendency of some companies to reduce software engineers to mere "code generators." This mindset fundamentally misunderstands the role of an engineer. Engineers don’t just write code; they solve problems.

The distinction matters because AI is increasingly positioned as a replacement for engineers, marketed as a tool that can generate code, fix bugs, or optimize performance. But this framing misses the point: generating code is only a small fraction of what engineers do.

Engineers define what problems need solving and why. They determine how those solutions integrate into broader systems and align with business goals. AI, for all its capabilities, doesn’t understand context, purpose, or nuance. It needs direction—a clear problem, properly abstracted—before it can contribute meaningfully.

This is where engineers shine. The solution requires their intuition. Verification demands their expertise. And the value of AI is magnified when it’s wielded by engineers capable of framing complex problems, iterating on solutions, and knowing when and how to trust—or question—AI’s output.

In the modern landscape, a software engineer is not someone who simply produces code but someone who orchestrates the tools, abstractions, and insights needed to solve problems effectively. AI doesn’t replace that role; it enhances it. But only if you hire engineers who can rise above the superficial tasks AI handles and focus on the deeper, more critical aspects of engineering.

Rethinking the Hiring Process

To hire effectively in today’s world, leaders must adapt their processes:

1. Focus on Thought Process Assess how candidates think, not just what they know. Can they frame a problem effectively? Can they leverage AI tools to expedite the solution?
2. Evaluate the Ability to Abstract The best candidates can distill a messy, complex problem into its essentials, guiding both AI and their teams toward practical solutions.
3. Test for Judgment AI can spit out thousands of words or lines of code. Does the candidate know how to spot errors, adjust direction, and decide when to override AI suggestions entirely?

Closing Thoughts

The skills you hired for yesterday are not the skills you need today. As AI reshapes the way we work, the most valuable employees will be those who can navigate this new landscape with creativity, insight, and critical thinking.

Your candidates don’t need to be able to solve bubble sort from memory—they need to know how to solve your problems. So hire for that.