In this episode of Human Work After AI, Chris Fanchi speaks with Niel Robertson (CEO of Winslow) about an underappreciated shift: modern organizations produce massive “digital exhaust” through calls, chats, and documents, and AI is making that exhaust usable for the first time.

They discuss why transcripts are becoming a core dataset inside companies, how “vibe coding” is changing what non-technical teams can build, what the post-SaaS debate misses about maintenance and extensions, and why HR is a natural early home for AI assistance. The conversation stays focused on leadership, trust, and what it takes to turn experimentation into durable capability.

Most leaders want better hires, faster. But as AI reshapes recruiting, the deeper issue is what hiring systems are actually selecting for, and what they quietly reward.

Chris Fanchi speaks with Fletcher Wimbush, CEO of Discovered, about end-to-end recruitment automation, structured talent assessment, and the tradeoffs leaders face as hiring becomes more scalable and less human-driven. They discuss bias, candidate experience, feedback risk, the future of the resume, and a provocative possibility: that removing humans from parts of the process may improve fairness and decision quality in certain roles.

At the center is a durable leadership principle: as skills become easier to simulate, integrity, motivation, and judgment become harder to ignore.

Most leaders want better hires, faster. But as AI reshapes recruiting, the deeper issue is what hiring systems are actually selecting for, and what they quietly reward.

Chris Fanchi speaks with Fletcher Wimbush, CEO of Discovered, about end-to-end recruitment automation, structured talent assessment, and the tradeoffs leaders face as hiring becomes more scalable and less human-driven. They discuss bias, candidate experience, feedback risk, the future of the resume, and a provocative possibility: that removing humans from parts of the process may improve fairness and decision quality in certain roles.

At the center is a durable leadership principle: as skills become easier to simulate, integrity, motivation, and judgment become harder to ignore.

Construction is supposedly "behind" on technology. But talking to people actually implementing AI in that world reveals something most industries haven't admitted yet: the friction isn't about the tools. It's about what happens to expertise pipelines, trust relationships, and human judgment when you automate the work that used to teach people how to think.

Eric Helitzer spent a decade as both a subcontractor and general contractor before building SubBase, a procurement software for trade contractors. What he's learned watching AI hit manual workflows maps directly onto what's happening in white-collar work right now. Companies celebrating revenue growth without headcount growth. Junior roles that just never get filled. Apprenticeship systems quietly hollowing out because AI does the entry-level work now.

We discuss why invisible job displacement happens before layoffs, the collapse of apprenticeship pipelines when junior work gets automated, where AI genuinely improves work versus where it creates new dependencies, and why educational communication matters more than the technology itself. This isn't really about construction; it's about what happens when automation meets work that's always been learned through doing, relationship-based, and trust-heavy.

The pattern is already visible. Most people just aren't naming it yet.

Automation is accelerating across organizations — but not everything can be automated.

In this episode, Chris Fanchi speaks with Chris Samaras about the real limits of automation and why human judgment, accountability, and leadership still matter in AI-driven workplaces. They explore where automation helps, where it quietly breaks down, and why efficiency is not the same thing as responsibility.

This conversation is for leaders and managers trying to adopt AI without losing trust, context, or human decision-making — and for anyone thinking seriously about what work still requires humans as automation expands.

AI didn’t just speed up the work—it changed who gets hired, paid, and promoted.In this episode, Andrew Hewitt explains how AI is reshaping teams, vendors, and leadership decisions.AI adoption isn’t just a technology shift—it’s a workforce and leadership reckoning.In this episode of Human Work After AI, Andrew Hewitt (Founder & CEO of YohDev) explains how AI coding agents, automation, and internal tools are changing how companies structure teams, reduce contractor costs, and rethink service-based business models.Andrew shares real examples from his own firm—including a 40% reduction in contractor spend without reducing output—and why leaders must move beyond hourly labor models toward productized, trust-driven work.This conversation is especially relevant for managers, executives, and founders navigating:• AI-driven productivity gains without burning out teams• Why hourly work breaks in an AI world• When automation helps—and when it quietly creates talent risk• How human connection becomes a competitive advantage• Why service firms must productize or risk being replaced📌 Topics we cover:00:00 Why service businesses must productize in the AI era 12:30 How AI coding agents are already in production 21:50 What happens when AI flattens contractor demand 24:40 Why hourly compensation fails with AI 30:00 Human skills that matter more as automation increases 31:50 Who AI will help—and who it will leave behind 📘 Want a leadership framework for managing AI responsibly?Check out Managing AI — a practical guide for leaders navigating workforce transformation, trust, and human-centered AI.https://bignorthnetwork.com/managing-ai🌐 Learn more about Big North Network:Helping leaders adopt AI without losing their people, culture, or trust.https://bignorthnetwork.com/🌐 Work with Andrew and YohDev:Full-stack engineering & AI-powered development: https://yohdev.com👍 Subscribe for weekly conversations on AI, work, and leadership.💬 Comment below: What part of your job do you think AI will change first?

Most culture efforts fail at the moment they’re supposed to matter most: everyday leadership behavior. In this conversation, Chris Fanchi talks with John Betancourt, CEO of Humantelligence, about what AI reveals — not replaces — in how people lead, communicate, and make decisions at work.

They explore why traditional culture programs rarely change behavior, how AI personalization only works when leaders actually care enough to adapt, and why judgment can’t be automated even as tools become more powerful. The throughline is responsibility: as AI becomes part of every role, leadership becomes harder to fake... and more important than ever.

Guest

John Betancourt — CEO, Humantelligence

https://humantelligence.com

https://askaura.ai/

More on AI, leadership, and work:

https://bignorthnetwork.com

Artificial intelligence isn’t creeping into construction, it’s crashing in at full speed. And according to Alex Teplitxky, we’re not just optimizing workflows anymore… we’re redefining what counts as human work.

In this episode of Human Work After AI hosted by Chris Fanchi, Alex breaks down the rapid adoption of AI in construction, why the industry hit a tipping point in 2025, and what happens when a single analyst can suddenly manage 7-8 projects instead of three. He also goes deep on the existential side: mechanical “parallel humanity,” superintelligence risks, and why workers are fleeing white-collar roles for the trades.

This is one of the most candid conversations yet about how AI is reshaping not only labor markets, but humanity itself.

🔥 Key Themes

- Why construction went from “AI is cute” to “AI is essential” practically overnight

- The real economic impact: when one person can do the work of an entire team

- Agentic AI and the shift toward company-owned internal agents

- Why young workers are abandoning office jobs for skilled trades

- The boundary between “organic humanity” and “mechanical humanity”

- Alex’s optimism (creative empowerment, mobility) and deepest fears (superintelligence, extinction risk)

📌 Chapters

00:00 – Can we create a “parallel mechanical humanity”?

01:30 – Alex’s background: Silicon Valley summers & the pull of tech

02:44 – Getting into construction tech

11:24 – Why digitizing construction is so hard

12:35 – What SmartPM actually solves

15:51 – Why AI + math is the real engine of project controls

18:21 – The origins of generative scheduling

19:30 – How construction attitudes toward AI flipped almost overnight

22:30 – Agentic AI and internal company-built agents

24:17 – Data control, privacy, and the rise of proprietary AI

25:07 – Is AI augmentation… or quiet job elimination?

26:27 – Workers fleeing office jobs for the trades

27:48 – The coming “AI layoffs” nobody wants to say out loud

28:50 – Will human judgment remain essential?

30:41 – Are humans just organic algorithms?

31:53 – Automation, safety, and where society goes next

32:40 – Alex’s optimism: self-driving lifestyle & creative empowerment

33:35 – Alex’s fears: superintelligence and existential risk

36:30 – Could AI already be hiding from us?

37:13 – The positive and dark sides of our AI future

38:03 – Where to find Alex & SmartPM

📚 Resources

SmartPM - https://www.smartpm.com

Connect with Alex on LinkedIn - https://www.linkedin.com/in/alexteplitxky/

AI Transition Management Consulting with Chris Fanchi - https://bignorthnetwork.com/

📘 Get the Book — Managing AI: Humans, Agents, and the Future of Work (Available Now!)

Chris Fanchi's new book explores how AI is reshaping white-collar work, why trust infrastructure matters more than ever, and what it takes to stay human in an age of agents and automation.

👉 Learn more and order now at

https://bignorthnetwork.com/managing-ai

#AI #FutureOfWork #ConstructionTech #SmartPM #Automation #AgenticAI #HumanWorkAfterAI