Customer Support Leaders

Send us Fan Mail
Customers are talking about you where your VOC program rarely looks and it’s shaping revenue, retention, and trust. Nate Brown joins me to introduce Fearless CX, a bold and practical way to lead customer experience in a time when fear is high, teams are tempted to retreat into silos, and “insular thinking” makes cross-functional work painfully slow.

We dig into what Fearless CX looks like inside the organization: leaders acting as a beacon, building trust through character and conviction, and creating psychological safety without drifting into comfort or inertia. The goal is healthy tension where people can challenge ideas, learn fast, and collaborate across the enterprise to produce a consistent customer experience outcome.

Then we get tactical about modern voice of customer strategy. Nate explains “wild sentiment” the unstructured feedback living on Reddit, YouTube, third-party communities, and public reviews. We talk about how AI search is changing customer support behavior, why customers often solve problems without ever contacting the brand, and how AI-enabled customer experience management platforms can finally harmonize structured and unstructured feedback into real themes, tags, and actionable insights.

If you want a customer experience strategy that survives uncertainty and actually earns trust, press play. Subscribe, share this with a CX or support leader, and leave a review, then tell me: where do you think your customers are shaping your brand story today?
Support the show

Send us Fan Mail
AI is starting to take the queue. So what’s left for a customer support team once automation handles triage, repetitive questions, onboarding, and a big chunk of ticket volume? Ryan Klausner joins me to get specific about “life after AI” and why the future of support is bigger than faster replies. We talk about how human-first support can still thrive while using AI in customer service in a way that actually improves the customer experience.

We dig into the real shift: moving from reactive ticket handling to proactive support that prevents issues before they hit. That means treating support as a central intelligence function, using AI to surface friction in the customer journey, spotting trends early, and turning messy contact data into clear insights that product and marketing teams can act on. We also get honest about the cultural and coaching work required to help frontline teams become strategic operators, not just great responders.

Ryan shares what new roles and skills are emerging, from conversational analysis and prompt design to owning knowledge bases, self-service, and customer education. We also unpack trust, why “fake empathy” from bots can backfire, and how to build a better resolution path with smart escalation and truly white glove human help for complex scenarios. If you’re thinking about customer support careers, CX strategy, or AI driven customer experience, this one will sharpen your view of what’s next.

If this conversation helps, subscribe, share it with a support leader on your team, and leave a review with your biggest takeaway. What part of support would you automate first, and what would you protect for humans?
Support the show

Send us Fan Mail
AI is already in your support queue, but the real question is what it’s doing to your career path. I’m joined by Hilary Dudek, Head of Customer Experience at Gamma, to get specific about how AI is reshaping customer support roles and why the “bots are coming for our jobs” narrative misses the most important part: new jobs are being created right now.

We dig into what AI chatbots are genuinely good at, like handling simple requests and searching your help center faster than any human can, and where they still struggle, especially around empathy, reassurance, and messy edge cases. We also talk about the shift away from chatbots masquerading as humans and toward clearer, more transparent bot experiences that set expectations and make handoffs to human support feel natural.

From there we go deep on the emerging roles: AI Support Engineer, support architect, and the growing need for people who can manage connectors across documentation, Slack, email, CRM, and data warehouses. We cover prompt engineering, knowledge management, routing and triage, hallucination risk, and why sensitive areas like billing and legal context still require careful human oversight. Hilary also shares a practical example of rapid experimentation: building a “support psychic” with AI that predicts likely follow-up questions and suggested responses from recent ticket patterns.

If you lead support operations, manage customer experience, or you’re on the frontline wondering how to stay relevant, this conversation is a roadmap for leaning in with confidence. Subscribe, share this with your team, and leave a review, then tell me: what AI-powered support role do you want to see next?
Support the show

Send us Fan Mail
Growth rarely happens on a straight line, and neither should coaching. We sat down with Andrew Rios, Head of Customer Experience at Cityside Fiber, to explore how leaders can tailor their coaching as people mature—from fresh hires forming their professional identity to seasoned operators who navigate constraints with judgment and calm. Andrew draws on an unexpected source—coaching youth sports—to reveal practical tactics that translate directly to support leadership.

We start with the early-career stage, where strong opinions and limited exposure often collide. Andrew’s approach is simple and effective: observe first, set clear expectations, explain the why, and check for understanding without condescension. He shares how to model the behavior you want, turn feedback into co-created next steps, and transform “I’m right” energy into team-first outcomes. Along the way, we talk about relatable storytelling, sticky lessons, and the value of asking people to reflect back what they heard so alignment sticks beyond the meeting.

As the conversation moves to senior ICs and emerging leaders, we shift to the realities of budgets, staffing, and process limits. Here, coaching is less about task accuracy and more about decision quality, trade-offs, and influence without authority. Andrew explains how transparency builds trust, how to run adult reflection loops (“If you could do it again, what changes?”), and why change usually takes longer than a 90-day plan. We also dig into inheriting teams, decoding norms from past workplaces, and preventing message drift by re-anchoring the why at regular intervals—even with your top performers.

Throughout, vulnerability is the backbone. Andrew talks openly about owning mistakes on the field and at work, thanking the team for the save, and using those moments to strengthen culture. If you’re a support leader, manager, or senior IC looking to evolve your coaching playbook, this conversation offers concrete tools and a mindset shift: meet people where they are, coach for where they want to go, and resist coaching them where they don’t.

If this resonated, follow the show, share it with a fellow leader, and leave a quick review to help more people find these conversations.
Support the show

Send us Fan Mail
What happens when AI automates the work that built your career story? We sit down with Lauren Eimers to trace a path from clinical counseling and genetics into customer support leadership and onward to clinical science liaison, then use that journey to unpack a bigger shift: the changing identity of support as AI handles the basics and reshapes teams, metrics, and roles.

Across this candid conversation, we question what “foundations” really mean. If bots resolve simple tickets in seconds, where do managers, directors, and VPs create value? We argue the center of gravity moves toward experience design: setting tone, training AI with the right knowledge, defining escalation paths, and architecting journeys that leave customers feeling seen and confident. That is where human strengths become strategy—storytelling that builds trust, empathy that defuses tense moments, and ethical judgment when answers affect health, money, or safety.

We also get practical about fear and planning. Instead of waiting for clarity, we model scenario thinking: inventory your durable skills, map them to AI-augmented roles like knowledge architecture, prompt strategy, and quality review, and use community to test and refine your plan. Expect a nonlinear path—more lily pads than highways—and treat each step as a chance to strengthen the human elements machines can’t replicate. The pace of change is fast, but the purpose endures: create support that feels simple, respectful, and human, even when the system behind it becomes radically new.

If this resonates, follow the show, share with a teammate, and leave a review telling us which human skill you plan to double down on next.
Support the show