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AI tools can now write code, generate content, and solve technical problems in seconds. But here’s what they can’t do: replace the judgment of knowing who will actually thrive on your team.

I’ve been on both sides of this - building teams and placing people in other companies. The metric that matters isn’t how many people you’ve hired. It’s how long they stay and how much they grow. That tells you if you’re matching the right person to the right problem, not only filling a seat.

What Doesn’t Matter Anymore

Stop optimizing for these:

AI experience - Nobody has real AI experience. The field moves so fast that “expertise” from six months ago is already outdated. Someone claiming deep AI knowledge is either lying or about to be wrong. Disclosure, I’m referencing applied AI and not Machine Learning as a field.

Tech stack - A good engineer learns new tools quickly. Obsessing over whether someone knows your exact framework is a waste of time. If they can think clearly about problems, they’ll pick up your stack.

Recent projects - What someone built last year might be impressive, but it doesn’t tell you how they’ll handle your specific challenges. Past projects are weak signals.

Big logos - Working at a famous company proves they got hired once. It doesn’t prove they’ll be effective in your environment. I’ve seen brilliant engineers from unknown startups run circles around people from FAANG companies.

Employment status - Whether someone is “open to work” or currently employed tells you nothing about their ability. Some of the best hires I’ve made were people between jobs. Some of the worst were people I poached from competitors.

What Actually Matters

These are the things that predict whether someone will succeed:

Intent and Purpose - Why do they want this role? Not the rehearsed answer about “exciting challenges” - the real reason. Are they running toward something or running away from something? Do they understand what you’re building and why it matters? The best people I’ve hired had clear reasons for wanting to be there that aligned with where we were going.

Problem Solving Skills - Can they break down complex problems? Do they ask good questions? When they don’t know something, do they admit it and figure it out? This matters more than knowing any specific technology. AI can generate code, but it can’t decide which problem to solve.

Communication Skills - Can they explain technical concepts clearly? Do they listen? Can they disagree without being disagreeable? As teams scale, communication becomes the bottleneck. Someone who writes clean code but can’t communicate will create more problems than they solve.

Adaptability - When requirements change, do they complain or do they adjust? When their first approach doesn’t work, do they pivot or dig in? The roadmap you have today won’t be the roadmap you have in three months. You need people who can handle that.

Emotional Intelligence - Do they understand how their work affects others? Can they read a room? Do they know when to push and when to yield? Technical brilliance without emotional intelligence creates friction. I’ve passed on technically strong candidates because they lacked this.

Creativity and Innovation - Do they see solutions others miss? Can they connect ideas from different domains? Do they question assumptions? AI can optimize existing approaches, but it struggles with novel thinking. The humans who thrive alongside AI are the ones who can imagine what doesn’t exist yet.

Why This Matters Now

AI has made technical skills more accessible and less differentiating. Anyone can use Claude or ChatGPT to write decent code. The value is shifting to the things AI can’t replicate: judgment, taste, collaboration, and the ability to define what problem to solve.

When I’m hiring, I’m not looking for someone who knows the most about the current hot technology. I’m looking for someone who will still be valuable when that technology is obsolete. Someone with strong intent, clear thinking, and the ability to work well with others.

The people who last on teams are the ones who care about the mission, solve problems creatively, and make everyone around them better. That was true before AI, and it’s even more true now.