Are Hiring Managers The Real Problem? Key Takeaways From Hire Ground Live#2

By Tanisha ·

Are Hiring Managers The Real Problem? Key Takeaways From Hire Ground Live#2

AI is changing how companies recruit, but it has not solved one of the oldest challenges in hiring: getting hiring managers and recruiters on the same page. That was the focus of this Hire Ground Live conversation: 

Are Hiring Managers the Real Problem?

Hosted by Desiree Goldey, the discussion brought together Lori Golden, founder of Rebel HR, and Mayur Macwan, founder of RoundOne AI.
The conversation covered unrealistic job descriptions, vague requirements, interview training, candidate alignment, recruiter accountability, and the role AI should play in hiring.

The central theme was simple: AI cannot fix a hiring process that was poorly defined in the first place.

Hiring Problems Often Start Before The Job Is Posted

A recruiter can only work with what a hiring manager gives them. If the requirements are vague, unrealistic, or copied from an old job description, problems can start before a single candidate is contacted.

Lori emphasized pressure-testing requirements during intake instead of simply accepting everything the hiring manager asks for. Recruiters can ask:

  • What does this requirement actually achieve?
  • Why does this experience matter?
  • Which requirements are essential?
  • What tradeoffs are you willing to make?
  • What would make someone successful?

This forces the hiring team to define the role instead of searching for an imaginary “perfect” candidate.

“Find Me Another Jimmy” Is Not A Hiring Strategy

One example from the conversation was the hiring manager who says:

  • “Just find me another Jimmy.”

The problem is that Jimmy is not a job requirement. Recruiters need to understand what made Jimmy successful, whether that was technical expertise, communication, decision-making, ownership, or experience in a particular environment.

Without identifying those traits, recruiters are trying to recreate a person rather than define the requirements of the role. Pattern matching may feel easier, but it does not necessarily identify what the next successful hire needs.

“I’ll Know It When I See It” Needs A Calibration Step

Hiring managers may struggle to describe what they want, especially when hiring for a new type of role. That does not mean recruiters should immediately move into full-scale sourcing.

Lori suggested using early candidates for calibration instead. Recruiters can bring a range of profiles, such as junior, mid-level, senior, agency, or in-house candidates, and use those conversations to refine the target profile.

This gives both sides a chance to clarify requirements before investing significant time in sourcing and interviews. If the profile is still being defined, candidates should not be led to believe the process is already fully established.

Recruiters Need To Be Strategic Partners

Recruiters should not simply take a job description, find candidates, and ask the hiring manager which one they want. Lori described recruiters as subject matter experts who should challenge assumptions and bring market knowledge into the process.

That starts during intake. Instead of asking only what the hiring manager wants, recruiters can bring:

  • Market research
  • Compensation data
  • Candidate availability
  • Hiring benchmarks
  • Questions about role requirements
  • Insights from previous searches

When recruiters bring this expertise, the relationship can shift from order-taker and requester to partners working toward the same outcome.

Hiring Managers Need Interview Training

A strong recruiting process can still fall apart during interviews. Experienced professionals may not automatically know how to evaluate candidates consistently or communicate effectively during an interview.

Lori discussed interview training covering compliance requirements and strategic interviewing. This includes what to ask, what not to ask, how to evaluate candidates, and how to approach passive candidates.

The conversation highlighted one example: asking a passive candidate, “Why do you want to work here?” If the recruiter persuades them to take an exploratory conversation, they may not have a reason to want the company yet. The hiring manager may need to sell the opportunity instead.

Alignment Has To Work Both Ways

Hiring is not only about whether a candidate fits the company. The company and candidate also need to understand whether they are aligned on the role and expectations. Lori shared that one role had received nearly 2,000 applications in 24 hours. At that scale, simply processing more applications is not necessarily the answer.

A clear intake process helps teams establish what they are actually looking for before sorting through hundreds or thousands of applications. That clarity can then carry into screening and interviews.

AI Does Not Replace Good Hiring Practices

AI was another major part of the discussion. The speakers pointed out that AI can make poorly defined job descriptions even more complicated by adding polished language and more requirements without addressing what the role actually needs.

That creates more volume without necessarily creating more useful candidates. As Lori noted, AI can become another scapegoat when the underlying problem is unclear hiring requirements. The bigger takeaway was that AI does not necessarily create every hiring problem. It can expose problems that were already there.

AI Can Help Turn Job Descriptions Into Explicit Requirements

Mayur explained how RoundOne approaches this problem. Instead of simply using a job description as a screening input, RoundOne extracts the requirements and asks the recruiter or hiring manager to review them.

This creates an additional checkpoint:

Job description → requirements → screening criteria

The review can reveal missing requirements or clarify what should actually influence candidate screening. It creates more alignment between what the company says it wants and what the screening process evaluates.

AI Should Find Evidence, Not Make The Final Judgment

Mayur also explained that RoundOne is designed to use AI to find evidence rather than make the final hiring judgment. For example, if a requirement is five years of experience in a particular area, the system can look for evidence supporting or not supporting that requirement. The recruiter or hiring manager can then use that evidence when making a decision.

This keeps the human decision-maker involved instead of treating an AI-generated score or recommendation as the final answer.

CV Screening And Voice Screening Serve Different Purposes

Some requirements can be assessed directly from a CV, while others require a conversation to establish whether a candidate demonstrates the relevant experience or capability.

Mayur explained that RoundOne uses a two-stage approach:

  1. CV screening for requirements that can be assessed from the resume.
  2. Voice screening for requirements that need a conversation to evaluate.

The purpose is still screening rather than replacing the hiring manager’s final judgment.

The Real Goal Is Better Alignment

The discussion ultimately moved beyond whether hiring managers are “the problem.” Hiring involves recruiters, hiring managers, candidates, leadership, systems, and plenty of opportunities for miscommunication.

The goal is to create alignment early, clarify requirements, train interviewers, and use data to identify where the process is breaking down. AI can support parts of that process, but it cannot replace the need to define the problem clearly.

Watch The Full Hire Ground Live Conversation

Want to hear the full discussion on hiring managers, recruiters, AI, interview training, job descriptions, and evidence-based hiring?

Watch the full Hire Ground Live conversation to hear Desiree Goldey, Lori Golden, and Mayur Macwan unpack these challenges and practical solutions in more detail.

Watch the full recording

Better hiring does not start with finding more candidates. It starts with getting clearer about who you need, why you need them, and how you will evaluate them.

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