Recruiting is in an arms race: job seekers spray AI at every open role; recruiters crank filters to keep up. Nobody wins. 

⚡ Kristen Habacht—CEO of Elly and former head of revenue at Trello (then Atlassian) and CRO at Typeform—thinks the fix isn’t more filters. It’s tech that actually learns, so recruiters can do the human work.

Wade and Kristen talk about why most ATSs are “filing cabinets,” what “ICP for hiring” would look like, and why Elly never says yes or no to a candidate—only “did you see this? Is it important?” They cover the 1,000-applicants-in-24-hours reality, PLG in talent/HR, bias and AI screening, her take on AI “cheating” in interviews (“who really cares? It shows they know how to use the tool”), and why she’s giving away a lot of free usage instead of buying a billboard. Plus the story of the day she found out Trello was being acquired by Atlassian—and shoved her co-founder thinking he was joking.

In this episode, you’ll hear:

- 🎯 Why recruiting is broken for both sides and how the current arms race got here.

- 📋 What’s wrong with today’s ATSs and why “ICP for hiring” could change the game.

- 👥 How Elly keeps humans in the loop—and why the AI never decides anyone in or out.

- 🔍 Why keyword search fails hiring (and what Trello’s early PLG hiring had to do with it).

- 🤖 Whether AI in interviews is “cheating,” proctored interviews, and what might actually stick.

- 🔗 Why TA and HR still don’t talk—and why that has to change.

- 🌐 What a “universal job application” could look like—and where Elly is putting its $8M.

Guest: Kristen Habacht — CEO, Elly.

Is SaaS about to be replaced by people “vibe-coding” their own apps — or is something deeper at stake? Dharmesh Shah, co-founder and CTO of HubSpot, joins Wade to cut through the hype and give a refreshingly practical view of how companies should show up for AI.

Dharmesh argues the right question isn’t “How do I compete against AI?” but “How do I compete with AI?” — and explains how culture, curiosity, and a little bit of tinkering unlock real value. From practical starting points for SMBs, to why large SaaS vendors still have a massive advantage, to the power of simulation and retrieval-augmented workflows, this episode maps out what leaders and teams should actually do next.

In this episode you’ll hear:

• Why “compete with AI” beats “compete against AI.”
• The rituals that help organizations adopt AI (hackathons, demos, and scheduled retries).
• Low-risk starting points: creation → synthesis → automation → simulation.
• Why large SaaS companies likely aren’t going extinct — and when vibe-coding does make sense.
• How AI can amplify careers: automate the small stuff, get promoted to bigger problems.
• Practical ideas for marketing, personalization, and building dynamic UIs that fade into the background.

Guest: Dharmesh Shah — Co-founder & CTO, HubSpot

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Most companies talk about becoming “AI-first.” Very few actually stop the business to make it real.

Wes Schroll — Founder & CEO of Fetch — joins Wade to unpack what it actually takes to scale a consumer platform, evolve a decade-old company, and integrate AI without losing focus, culture, or trust. From building his first business at 14 to leading a reward destination that now influences more consumer spend than nearly anyone outside Walmart and Amazon, Wes shares the behind-the-scenes decisions that shaped Fetch’s growth.

They dig into Fetch’s business model, how Wes’s perspective on AI shifted from skepticism to urgency, and why leadership had to get hands-on — not delegate AI exploration to a task force. Wes breaks down the decision to shut down the company for a full week so 1,000+ employees could participate in an AI hackathon, the hard lessons learned from early automation missteps, and why simple, readable AI guidelines matter more than fear-based policy.

The conversation also explores how AI is changing founder–engineering dynamics, reshaping what counts as a competitive advantage, and lowering the barrier for non-technical leaders to communicate, prototype, and collaborate more effectively.

In this episode, you’ll hear:

• How a founder’s personal AI “aha moment” sparked a company-wide shift.
• Why task forces fail and hands-on leadership creates real momentum.
• What Fetch learned from shutting down the company for a week-long AI hackathon.
• How to evaluate AI aptitude, scalability, and vendor promises realistically.
• Why short, human-readable AI guidelines outperform long, punitive policies.
• How AI reduces expertise asymmetry between founders, product, and engineering teams.
• Lessons on resilience, responsibility, and surviving the emotional highs and lows of entrepreneurship.
• Why using AI isn’t “cheating” — and how leaders must reset that narrative.

Guest: Wes Schroll—Founder & CEO, Fetch

Most security playbooks weren’t built for an era where AI moves faster than policy. Rob T. Lee says the default answer of “no” is creating a far bigger problem: shadow AI — widespread, unsanctioned usage that quietly exposes organizations to risk.

Rob T. Lee — Chief of Research & Chief AI Officer at the SANS Institute — joins Wade to unpack pragmatic ways leaders can move forward without breaking things. From the “tinker/hacker” mindset that helps teams learn, to treating security like a lifeguard (not a chokehold), Rob lays out the short, repeatable moves that actually get enterprises experimenting safely: enable small experiments, create accountability partners (not mythical “AI champions”), red-team your integrations, and make governance part of the daily routine.

In this episode you’ll hear:

• Why a blanket “no” to AI creates shadow AI and greater risk.
• How to flip policy toward a cautious “yes” and act like a lifeguard, not a jailer.
• Practical training tactics: 30 minutes a day, micro-projects, and hackathons.
• What good AI governance looks like — rules of acceptable use, vendor checks, red teams, and regulatory thinking.
• Why executives and boards need to be hands-on learners, not just hire an “expert.”
• The origins and purpose of the SANS Secure AI Blueprint and how to use it to align strategy, governance, and operations.

Guest: Rob T. Lee — Chief of Research & Chief AI Officer, SANS Institute

Most enterprise AI talk sounds great in theory—until you try to make it work across 40 disconnected systems. Jason Cottrell says that’s exactly where the real wins are hiding.

As CEO of Orium (and the new president of the MACH Alliance), Jason has seen what happens when companies stop chasing one big AI solution and start stacking small, composable ones. The result? For one retailer, a 9-month transformation that led to 5x digital growth—and a repeatable roadmap any enterprise can follow.

In this episode, Jason and Wade unpack why “many agents, many jobs” beats the mythical all-knowing AI, how interoperability is quietly rewriting retail, and the cultural shifts that make automation actually stick.

Grammarly didn’t just change its company name—it changed the story of AI.
In a deep-dive conversation following the company's rebrand, Superhuman CEO Shishir Mehrotra joins Zapier CEO Wade Foster to unpack why this move signals a seismic industry shift: AI is moving from tools you have to remember to use to infrastructure that works wherever you do. Superhuman’s “AI superhighway” already makes 100 billion LLM calls a week, running across over 1 million apps and websites where work happens.
Shishir shares how Superhuman Go—the company's proactive AI assistant—turns intention into execution, how to run four products as a “compound startup,” and why the next frontier of AI-driven productivity won’t look like traditional software at all.
A rare glimpse into a monumental shift—from AI as a product to AI as the plumbing of modern work.

What happens when AI meets 10 years of enterprise data?

Box CTO Ben Kus joins Zapier CEO Wade Foster to dig into how enterprise AI actually works when scale, security, and governance aren’t optional. They explore what happens when agents start reasoning across real customer data—and why the hardest part isn’t the model, it’s everything around it.

Ben shares how Box is teaching AI to work with human workflows, not against them, while Wade connects it to the shift he’s seeing inside automation: from “set it and forget it” to systems that think alongside you.

Because in the enterprise, AI has to earn trust before it scales.

AI that sells, reasons, and closes like your top rep? It sounds terrifying—but it’s not. Amanda Kahlow’s Superhumans are proving that automation doesn’t erase people; it elevates them. Her team rewards employees who replace their own jobswith AI by promoting them, not firing them. And her customers? They’re seeing sales cycles shrink from 22 days to 2 and average deal sizes double.

In this episode, Zapier CEO Wade Foster and Amanda dig into what “AI-led growth” really means—and why the smartest move in 2025 isn’t resisting AI, it’s learning how to lead with it. They unpack why 76% of 1Mind’s pipeline now comes from their own AI, and how org charts are evolving around a new role: the agent manager.

It’s a grounded, surprisingly human look at the future of work—and a reminder that the best way to stay relevant is to build the AI version of your best self. As Amanda puts it: “Your sellers hallucinate—AIs do it less.”

For Chris Pedregal, CEO of Granola, AI isn’t about replacing thinking—it’s about deepening it. He joins Zapier CEO Wade Foster to talk founder-to-founder about what it takes to build products that think with you, not for you. Together they explore why it’s the best time in history to be a builder, how AI can eliminate busywork without erasing human judgment, and why context will define the next decade of AI.

From living on the bleeding edge to running their own company on Granola, this is a masterclass in building AI that actually makes people smarter.

Replit’s mission: turn 100 million people into builders. CEO Amjad Masad joins Zapier CEO Wade Foster to discuss the real blocker to AI adoption—creativity, not code—and how enterprises can unlock it. They cover why most users freeze at the prompt, how social contagion drives adoption, and why your next “employee” might be an AI agent sitting in Slack.