Photo By: Vitaly Gariev
Artificial intelligence has transformed recruiting. Employers can search millions of professional profiles, automatically screen resumes, and identify qualified candidates in minutes. Yet hiring remains frustratingly inefficient. The technology has made it easier to find people, but it has not necessarily made it easier to understand them or determine whether they are truly a good match for a role. As a result, the hiring process can still feel impersonal and disconnected for both employers and candidates. Companies interview candidates who never accept offers, while job seekers apply to dozens, or even hundreds, of positions without finding the right fit.
According to Sebastian Scott, CEO of Clera, the industry’s biggest problem is no longer finding talent. It is understanding people for who they really are.
Scott describes this challenge as the “discovery gap,” which is the difference between what employers know about a candidate’s experience and what they do not know about that person’s ambitions, motivations, and willingness to change jobs.
“Most people are discoverable,” Scott says. “You can usually find their LinkedIn profile, GitHub account, or resume. What you can’t easily discover is whether they’re open to moving, why they would consider leaving, or what kind of opportunity they’re actually looking for.”
That missing information, he argues, often determines whether a hire succeeds.
Two software engineers may have nearly identical resumes, yet be motivated by completely different goals. One may want to become an engineering manager, while another wants to return to hands-on technical work. One may value stability at an established company, while another is looking for the risks and rewards of an early-stage startup. Those preferences rarely appear on a resume, but they shape every hiring decision.
Ironically, Scott believes AI has made this disconnect more obvious. While automation has made it easier to source candidates and process applications, it has also increased the volume of hiring activity without revealing the human context behind it.
“We’ve become very good at processing profiles,” he says. “We’re still not very good at understanding why someone would actually take a particular job.”
Scott does not believe the hiring system was intentionally designed this way. Applicant tracking systems, job boards, and recruiting firms all solved legitimate problems by making hiring more organized and accessible. Over time, however, they also created a process optimized for managing candidates instead of building meaningful connections. Clera aims to reverse that trend by making the hiring process more focused on understanding people and finding the right fit.
That realization shaped Clera’s approach.
Initially, Scott assumed better matching would come from collecting more data and building stronger algorithms. Instead, the insights that changed hiring decisions almost always emerged through conversation. Candidates would explain they wanted to work directly with founders again, cared deeply about a company’s mission, or no longer wanted management responsibilities. Those details rarely appeared in formal applications, yet they frequently determined whether an opportunity made sense.
For that reason, Clera starts with a candidate’s motivations before making introductions.
Beyond technical qualifications, the company seeks to understand what candidates hope to learn, what type of company they want to join, what tradeoffs they are willing to make, and what they will not compromise on. Scott argues that this produces more focused hiring conversations because both sides begin with realistic expectations instead of assumptions.
He also believes hiring managers are often missing one of the most valuable pieces of information: why a candidate is exploring new opportunities in the first place.
“A resume tells you where someone has been,” Scott says. “It doesn’t tell you where they want to go.”
Sometimes, candidates share information that initially sounds limiting, such as never wanting to manage another large team or only considering startup roles. Scott sees that honesty as an advantage, not a weakness.
“The things people don’t want are often just as important as the things they do,” he says. “Being specific rules out poor matches and makes the right ones much clearer.”
Ultimately, Scott believes recruiting should move away from measuring success by the number of applications submitted or interviews completed. Instead, hiring should be judged by long-term outcomes. Are candidates still thriving months or years after accepting an offer? Did both the employer and employee make the right decision? This approach shifts the focus from short-term hiring metrics to the quality and sustainability of the match. It also encourages companies to think more carefully about how they identify talent and evaluate potential, rather than relying on traditional processes that may overlook strong candidates. For job seekers, it could create a system where skills, experience, and potential matter more than connections or the ability to navigate a complicated application process.
“If someone can discover the right opportunity without already knowing the right person,” Scott says, “and a company can understand them without asking for another generic application, that would be real progress.”
