Spotting Top AI Talent: What Actually Matters

Hiring for AI is hard. Resumes are loaded with shiny tools and top logos. But surface signals can mislead — especially in a space evolving as fast as AI.

If you want to build a world-class AI team, start by asking better questions.

1. Are you hiring for what matters now… or what lasts?

“It’s more important now than ever to hire for learning agility and curiosity — not just what’s hot today.”

— Hal Tily, Advisor at Plenty (ex-Apple, Netflix, Oura)

Today’s trending tool will be tomorrow’s footnote. Prioritize curiosity, adaptability, and raw thinking skills over resume buzzwords.

“Right now, everyone’s talking about agentic workflows. In a year, no one will be using that term.”

— Hal Tily

What to look for instead:

• Clear examples of fast learning or career pivots

• Curiosity about how things work, not just how to use them

• Depth in problem-solving, not just breadth of tools

2. Can they explain how they’ve failed — and what they did next?

“I care more about whether they’ve recovered from failure than what company they worked at.”

— Hal Tily

Forget the perfect resume. Look for signal in the hard stuff:

• Have they made tough calls or shut down projects?

• Can they explain the ‘why’ behind those decisions?

• What did they learn — and how did it shape their approach?

Those answers tell you more than any job title ever will.

3. Are their fundamentals strong enough to flex?

“Statistical and engineering fundamentals are harder to learn on the job. They’re still worth screening for.”

— Hal Tily

Fast learners still need a base to build on — especially in AI roles. You want:

• Solid stats, not just plug-and-play LLM experience

• Engineering hygiene that scales

• The ability to troubleshoot when packages fail

“Building a model is easy. Asking the right question — that’s the real skill.”

— Travis Nixon, Chief Data Scientist at Microsoft, ML Leader at Meta, and Founder of SynerAI

4. Are you falling for logos instead of talent?

“Top performers often didn’t have shiny resumes. Startups need to go beyond lazy recruiting.”

—  Thach Nguyen, Founder & Managing Partner, Plenty

“I never took a computer science class. I got in by driving toward problems until someone said yes.”

— Travis Nixon

Look for trajectory, not pedigree. Pay attention to:

• Unconventional paths

• Side projects or self-driven learning

• Evidence of scrappy, high-leverage problem-solving

The best talent doesn’t always come pre-packaged. And that’s the point.

Bottom Line

✅ Hire for curiosity, not credentials

✅ Ask about failure — not just wins

✅ Check the fundamentals

✅ Ignore the logo. Read the story.

Want help spotting AI talent ?

That’s what we do. Reach out — or share this with a founder trying to scale their AI team.