Most companies say they want AI-native hires. Almost none of them can tell the real thing from a polished talking point.

You're writing "AI fluency required" into every job description, but when you sit across from a candidate, you don't actually know what good looks like. And your interview process? It's probably optimized for charisma, not competence.

Kyle Norton is CRO at Owner.com, one of the fastest-growing companies in restaurant tech B2B Tech. He leads a GTM org spanning sales, partnerships, onboarding, demand gen, rev ops, and enablement and he's built a dedicated Applied AI function inside his revenue team that most companies haven't even considered yet.

This conversation gives you a concrete framework for assessing AI fluency in interviews, a clear case for centralizing AI capability instead of spreading it thin, and a structured hiring process that replaces gut feel with repeatable data. You'll walk away knowing exactly where to invest and where to stop guessing.

Kyle breaks down the AI sophistication ladder for GTM professionals, explains why early-career hires are outperforming tenured reps at Owner.com, and makes the case for killing vibe-based interviews for good.

This one's for revenue leaders, founders, and hiring managers building teams that need to be competitive in the next two to three years.

Key Takeaways

>> Centralized AI teams produce orders-of-magnitude better output than reps tinkering side-of-desk. Kyle explains why he made Applied AI the first hire after Owner.com's Series C.

>> AI fluency matters most at senior and leverage roles like rev ops, but frontline managers and reps don't necessarily need it if the right infrastructure exists around them.

>> The fastest way to spot genuine AI fluency in an interview is to be deeply fluent yourself or have someone who is sitting in the process. Buzzwords fall apart fast under real scrutiny.

>> Structured interviews with identical questions, weighted scorecards, and separated criteria consistently outperform "vibe hiring" and they're the only way to build a data set you can actually learn from when a hire doesn't work out.

Chapter Markers

00:00 - Kyle Norton on AI fluency and hiring on vibes

01:56 - The internet comparison: why AI is already table stakes

04:48 - Where to actually learn about AI: Twitter, YouTube, and the feed algorithm

08:58 - Interviewing for AI fluency: what genuine answers look like

13:39 - Building a centralized Applied AI function inside GTM

16:45 - How the Applied AI team expanded beyond sales

19:04 - Why Owner.com shifted to early-career hiring

23:33 - Finding top talent at lesser-known companies

26:15 - The structured interview process: scorecards, mock calls, and bar raisers

32:32 - Go-to-market org structures for the next 2–3 years

36:25 - One concrete step: kill vibe hiring this week

40:09 - Danielle's closing thoughts

Useful Links & Resources

• Kyle Norton on LinkedIn: https://www.linkedin.com/in/kylecnorton/
• Owner.com: https://www.owner.com/

Connect With the Show

• Captivate Talent on LinkedIn: https://www.linkedin.com/company/captivate-talent/
• Danielle Parker on LinkedIn: https://www.linkedin.com/in/daniellemessler/
• Captivate Talent website: https://www.captivatetalent.com/

When did you last audit your interview process against real performance data? Drop your take in the comments or share the one hiring change that made the biggest difference for your team.

If this episode made you rethink how you're hiring for AI fluency or structuring your interviews, share it with a founder or revenue leader who needs to hear it. And if you're building a GTM team that needs to be competitive in the next few years, visit captivatetalent.com

Welcome to Human First.

The bar for AI fluency in go-to-market hiring has shifted dramatically and most executives haven't caught up.

You know you need to talk about AI in interviews, but you're not sure what "good" actually looks like anymore. Is using ChatGPT to brainstorm enough? Should you be building dashboards? And how do you evaluate something you're still figuring out yourself?

Andy Mowat built and scaled RevOps and demand gen at four unicorns - Box, Upwork, Culture Amp, and Carta. Now, as founder of Whispered, he's in constant conversation with senior GTM leaders about how AI is reshaping the way they hire and get hired. Few people have a broader, more grounded view of what's actually happening.

In this launch episode of Human First, Danielle Parker from Captivate Talent, and Andy get tactical about what AI fluency means right now, how it's being tested in interviews, and what you can do in the next 30 days to get across the chasm. You'll walk away with a clearer picture of what hiring managers are really asking and how to answer.

Key Takeaways

>> The AI fluency bar has moved from "curious" to "builder" in under 12 months. Using tools like Gamma or ChatGPT for slide decks is no longer enough to impress in interviews.

>> Most executives don't realize they're overselling their AI skills because the technology is moving faster than their self-assessment and many interviewers can't probe deeply enough to tell the difference.

>> The traditional take-home case study is broken and AI makes every submission look polished, so hiring managers need to rethink whether they're evaluating real thinking or just well-prompted output.

>> Hiring managers are over-indexing on "builder" without asking what's behind the question, whether it's doing more with less, flying low and high, or actually implementing AI tooling are three very different needs.

Chapter Markers

00:00 The question behind "hire a builder"

01:00 - Introduction to Andy Mowat and Whispered

01:38 - Biggest shifts in executive hiring conversations

03:33 - How AI fluency evaluation has changed

07:23 - What AI-fluent leaders actually sound like day to day

09:27 - Rev ops as the bridge role for GTM AI adoption

13:01 - How candidates oversell AI skills without realizing it

15:22 - Recognizing genuine AI passion in interviews

17:18 - Whispered's view on roles being reshaped by AI

19:23 - What rev ops looks like in two years

22:16 - The 30-day playbook to cross the AI chasm

28:30 - Is AI fluency learnable or inherent?

33:17 - Why take-home case studies are broken

38:06 - What should replace the case study

40:59 - Where go-to-market hiring is heading in 2-3 years

43:18 - One thing to do differently this week

Useful Links & Resources

• Whispered: AI platform for executive career moves
• Whispered Hiring Podcast: Andy's podcast on GTM hiring
• Claude Code by Anthropic: https://www.anthropic.com
• Lovable: No-code app building platform
• HyperBound: AI role-play platform for sales enablement

Connect With the Show

• LinkedIn: https://www.linkedin.com/company/captivate-talent/
• Website: https://www.captivatetalent.com/
• Danielle Parker on LinkedIn: https://www.linkedin.com/in/daniellemessler/

If this conversation hit home, we'd love to hear from you. What's the hardest part of evaluating AI fluency in your hiring process?

Drop a comment or send Danielle a message on LinkedIn — these are the conversations that make this show better.

Head to https://www.captivatetalent.com/ to see how Captivate Talent can help you find the right GTM leaders for what's next.