What 100+ hours of interviews with Talent Acquisition Professionals Taught Us About the Future of Hiring

When we announced that shortlistd 1.0 was shutting down, the response was immediate: dozens of comments, DMs, and questions about what we discovered that made us "start over completely."

The answer lies in 100+ hours of conversations with talent acquisition professionals across every type of organization you can imagine—from 5-person startups to Fortune 500 enterprises, boutique executive search firms to high-volume tech recruiters.

What we found wasn't what we expected. And it changes everything.

The Research That Changed Our Minds

Over the past year, we've conducted in-depth interviews with recruitment professionals across various company types and locations. We talked to agency recruiters handling hundreds of placements, enterprise TA leaders managing complex hiring processes, and startup founders wearing the recruiter hat out of necessity.

We went in thinking we understood the problem. We were wrong.

The 95% Accuracy Crisis

The first shock came when we started hearing the same impossible numbers over and over:

"Between 95% of applications are inaccurate matches" - Agency owner, Boutique Agency

"7 out of 10 applications are not relevant" - Recruitment Manager, Tech Company

"80% of candidates don't even respond" - Recruitment Manager, Tech Company

Think about that for a moment. If 95% of applications are irrelevant, recruiters are drowning in noise while the 5% of quality candidates get lost in the chaos.

This isn't a matching problem. This is a signal-to-noise crisis.

The Administrative Time Trap

The second pattern was even more concerning. Every conversation revealed the same time management nightmare:

"Resume screening is a massive time sink" - VP of people, Tech Holding

"This is a job by itself and resourceers normally do this job" - TA Leader

"Recruiters don't like admin, anything to reduce admin would be super important" - Multiple respondents

Here's what hit us: The best recruiters—the ones who build relationships, assess cultural fit, and close great candidates - were spending 70% of their time on administrative tasks.

The human skills that matter most were being crowded out by busywork.

The Frankenstein Stack Problem

Then we discovered something we hadn't anticipated: the "frankenstein stack" phenomenon.

Companies have cobbled together 5-10 different tools that barely talk to each other:

• ATS systems (Workday, Lever, Greenhouse)

• Sourcing tools (LinkedIn, Indeed, Naukri)

• Scheduling platforms

• Assessment tools

• Communication systems

"Anytime there's an update, it needs to be updated across multiple systems" - Recruitment Manager

The result? Teams with either massive capability gaps or expensive, fragmented tool stacks that create more work than they eliminate.

The Surprising Solution Everyone Actually Wanted

Here's where our assumptions got completely shattered.

We expected recruiters to want better sourcing, smarter matching, automated outreach - the typical "AI recruitment" features.

Instead, 80% of respondents wanted the same thing: AI interview scribes and transcription.

"This would be super valuable" - TA Leader

"Recently had an interview, and this AI was taking notes and the experience was really nice" - Recruiter

Why was this the #1 request?

Because interviews are where the real value gets created. Where relationships form. Where cultural fit gets assessed. Where hiring decisions actually get made.

But taking notes during these crucial conversations was breaking the human connection.

The Pattern That Changed Everything

As we analyzed hundreds of hours of interviews, three distinct patterns emerged:

High-Volume Recruiters

• Need: Bulk automation for screening and filtering

• Pain: Drowning in irrelevant applications

• Goal: Get to the 5% of quality candidates faster

Relationship-Focused Recruiters

• Need: Augmentation during human interactions

• Pain: Administrative tasks crowding out relationship building

• Goal: More time for what humans do best

Tech-Forward Recruiters

• Need: Integration and data-driven insights

• Pain: Frankenstein stacks that don't work together

• Goal: Unified platform with advanced capabilities

The insight: Different segments didn't need different products. They needed different capabilities from the same intelligent system.

What This Means for the Future of Hiring

Traditional recruitment software treats all hiring the same way. Build a tool, make it slightly smarter, charge per seat.

But hiring isn't one thing. It's three different problems:

1. Volume problem: Finding signal in noise

2. Capability problem: Augmenting human judgment

3. Integration problem: Unifying fragmented workflows

What we're building solves all three. Differently.

The Uncomfortable Truth About AI in Recruitment

Here's something that surprised us: trust in AI recruitment tools is actually declining.

"We don't use the matching very often, probably because of mentality and lack of trust in AI" - Recruitment Manager, Small Agency

Why? Because most AI recruitment tools are black boxes that make decisions without explanation. Recruiters can't trust what they can't understand.

Our approach is different. Instead of replacing human judgment, we're augmenting it. Instead of making decisions for you, we're giving you superhuman capabilities to make better decisions yourself.

What We're Building

We can't reveal everything yet, but here's what we can say:

We're not building another ATS. We're not building another sourcing tool. We're not building another assessment platform.

We're building autonomous agents that handle the administrative heavy lifting so humans can focus on what they do best: building relationships and making great hiring decisions.

Think of it as giving every recruiter superhuman capabilities:

• Work 24/7 without fatigue

• Maintain perfect consistency across hundreds of interactions

• Never miss a great candidate due to volume

• Augment every human conversation with intelligent insights

The result? Teams of 3 recruiters performing like teams of 30. Not through replacement, but through augmentation.