Hiring is broken (for those who keep making this mistake)

Hiring in the AI era is a mess. You're interviewing, and you keep getting rejection emails. Or, you're trying to grow your team, and the hires don't land. The hiring process is broken, and I learned that the hard way.

Shortly after I joined my first startup in 2020, I was asked to take on HR and grow a scrappy small team into a company large enough to operate a centralized exchange at scale. It was a huge challenge. It was my first "real" job, and my only prior experience was a few months of customer support.

That experience taught me that sometimes, when you put someone with almost zero knowledge in charge of something they've never done before and aren't prepared for, the trial of fire is often what yields the best results.

It was the beginning of an incredible journey. I spent my first weeks cold-DM'ing HR professionals on LinkedIn and Twitter, asking if they'd mentor me. I wanted to learn as much as I could to start building my own approach to hiring. In that process, I met many incredible and generous people, began building my own hiring approach, and, over time, discovered the key to hiring top performers.

A simple framework to fix the broken hiring process

After interviewing hundreds of people over the years across different companies, I discovered a simple, often-ignored principle that served as a compass for choosing the best candidates.

Whether you're a recruiter or someone looking for a job, you should know this: every time you go into an interview, use this framework of two layers to evaluate

1. the 'how I operate' layer (traits), and
2. the 'what I know / can do' layer (trades)

Traits are the group of skills you can't really teach someone: proactivity, curiosity, attitude toward change, comfort with being wrong, integrity. These are some of the traits I usually look for in a person during an interview, and I believe everyone should evaluate them when hiring in the AI era, where soft skills are hard to fake.

The second group, trades, are skills you can teach someone. Some simple examples could be programming languages like Rust, Python, etc. This set of hard skills might be more or less important depending on the role's seniority, but most recruiters and candidates make one massive mistake: they put the majority of focus on trades during the interview.

Let's imagine one scenario

Let's say you're a recruiter looking for a senior Rust developer, and you have two candidates. Candidate A is an expert in Rust, but is reluctant to adopt AI tools and prefers to maintain a familiar style of working that has served them well for a long time. Candidate B has been coding in Python for years, is actively learning Rust, and is an early adopter of AI, using it to move faster, but also knows how to review, test, and not blindly trust the output.

In the AI era, the hard part is rarely "can you write Rust." The hard part is whether you can learn quickly, adapt your workflow, and keep on shipping reliably while tools and constraints constantly change. In scenarios like the one outlined above, I usually would hire Candidate B and give them a few weeks to ramp up on company processes. The compounding effect of their trailblazer traits will outperform Candidate A over time.

My piece of advice

If you're a recruiter, don't fall in love with perfect, polished resumes. Look for people who treat being wrong as a data input. Ask questions that reveal how they learn: What did you believe six months ago that you don't believe anymore? What changed your mind? Then test their trades with a practical task.

If you're a candidate, your edge isn't "I know X tool." Your edge is how fast you can learn the next tool and still ship reliably. Make that visible: talk about how you ramped up, how you iterate, and how you use AI without outsourcing your judgment.