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Ready for a clean slate and a smarter way to build support in 2026? We kick off a fresh season with a rebuilt website, renewed energy, and a clear map of the big shifts reshaping our work: AI moving from side experiment to operational backbone, the leadership ladder compressing, and the customer journey turning truly dynamic. With Alec back on the mic, we share what sparked our collaboration, why the site overhaul mattered, and how we’re structuring episodes to turn complex trends into practical playbooks.

We dig into the AI arc we’ve watched up close: from generic tools to tailored systems grounded in product context and team workflows. That evolution changes how leaders think about risk, signal quality, and measurement. When each team builds its own AI-enabled flow, the data footprint becomes unique, and so must the metrics. We talk about moving beyond simple taxonomies and into cross-functional signals that reflect real value: reliability, effort reduction, resilience, and trust. It’s not about more dashboards; it’s about clearer decisions and better outcomes.

We also tackle the role overlap between support and customer success. Instead of strict handoffs, many teams are sharing tasks based on customer need, account complexity, and timing. The goal isn’t to blur expertise, but to surface the right context—recent incidents, account health, adoption goals—so the person in the room can help. That leads to our favorite battleground: journey mapping. Static maps that live on slides are fading. Dynamic journeys that adapt to signals are rising, supported by shared definitions, event-level visibility, and orchestration that changes course without creating chaos.

Expect returning guests, a few unfinished arcs finally wrapped, and plenty of new voices pushing us forward on AI maturity, metrics that matter, and the craft of leading modern support teams. If you’ve got a burning topic or a story worth sharing, head to customersupportleaders.com, scroll to the podcast page, and book a call. Subscribe, share with a teammate, and leave a review to help more leaders find the show.

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Forget the glossy strategy deck. We’re digging into the real drivers of customer experience: the values people use to decide, the culture that shows up in daily behavior, and the incentives that shape how work actually gets done. With coach and consultant Conor Pendergrast, we unpack why a perfect plan won’t move the needle without the conditions that make good choices easy under pressure.

We start by drawing a clean line between objectives, strategy, and tactics—then flip the frame. Support is operational, reactive, and fluid, so the experience your customers feel depends less on long-range roadmaps and more on what your team is empowered to do in the moment. We explore how a tight set of actionable values can guide judgment when process hits the edge cases, why culture is simply the sum of visible behaviors, and how to spot “painted-on” culture that reads great but conflicts with what the metrics reward.

Then we get practical. We talk incentives that matter—protected time for knowledge creation, loops from customer pain to product fixes, KPIs that don’t punish improvement work, and recognition that matches how individuals like to be celebrated. We cover Goodhart’s law, double-loop thinking, and the operational rituals that keep teams learning: documenting confusing flows, aligning processes to ownership, and building capacity for continuous improvement. Expect candid examples, clear language, and tools you can use to align values, culture, and incentives so strategy becomes the way your team works, not a slide you forget by July.

If you want support that scales quality—fewer handoffs, clearer answers, and issues that don’t boomerang—start here. Subscribe, share with a fellow support leader, and leave a review to tell us which behavior you’ll reward first.

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Ever faced a customer whose day went off the rails before they reached you? We dive into the emotional mechanics of difficult conversations and show how empathy, clear choices, and a partnership mindset can turn even the messiest moments into momentum. Charlotte sits down with customer and employee experience strategist Marc Haine to unpack a practical toolkit that works across hospitality, retail, government services, and B2B support.

We start with a simple truth: your first customer is your employee. When teams feel supported, they can stay calm under pressure and ask better questions that reveal what customers actually need, not just what they say they want. Marc shares a gripping hotel story that reframes conflict through safety, ownership, and forward-focused language. You’ll hear the exact phrases that de-escalate fast—“I realize how frustrating this is for you,” “In your place, I’d feel the same way,” and “Is it okay if we focus on next steps?”—along with respectful boundaries when calls turn abusive. Then we walk through a three-option framework that returns control to the customer, shifting them from victim to decision-maker.

We also tackle the quieter, colder B2B fury where reputations and revenue are on the line. The method holds: empathize, name the impact, and become a partner in the solution. Great service isn’t perfection; it’s recovery done right. By preparing employees with language, rehearsal, and permission to set boundaries, teams can guide customers from lizard brain to logic, from blame to progress. If you lead support, CX, or customer success, you’ll leave with a repeatable playbook to calm chaos and build trust that lasts.

If this episode helps, follow the show, share it with a teammate, and leave a quick review—what de-escalation line works best for you?

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What if the fastest path to trustworthy AI starts with a better knowledge base? 

David Kay is Principal at DB Kay & Associates, a consultancy focused on knowledge management and self-service for support. He was recognized as an Innovator by the Consortium for Service Innovation, and has been KCS v6 Certified as a Knowledge-Centered Service (KCS) practitioner, coach, and trainer. He held leadership roles at an innovative knowledge management technology provider from early 1998 to the end of 2002, and has been granted five patents for his work in knowledge management technology. His current work leverages thirty-five years of experience in envisioning, developing, marketing, and rolling out technology to aid knowledge-intensive businesses. David is co-author of Collective Wisdom: Transforming Support with Knowledge, and instructor of Customer Service: Knowledge Management and Customer Service with AI and Machine Learning on LinkedIn Learning.

I sit down with David to test a bold claim: you don’t do AI to get a knowledge base—you build a knowledge base to get good AI. Together we unpack what customers and agents actually need from information: it must be findable, usable, and accurate. Generative tools already deliver speed and clarity, but accuracy is where the stakes rise, especially in complex, safety‑critical domains where a confident wrong answer can do real harm.

We explain hallucinations in plain language and why persuasive, well‑phrased but incorrect outputs are harder to spot than sloppy forum posts. Then we explore retrieval augmented generation, a practical way to ground answers in trusted sources and expose citations for verification. That’s where a governed knowledge base becomes essential. KCS offers a proven way to capture knowledge in the flow of work, use the customer’s words, and evolve articles through real‑world reuse—exactly the structured, current content an AI pipeline needs to stay reliable.

The conversation turns tactical: how to start or reboot your KB, which KCS practices matter most, and why teams see faster AI wins when they invest in knowledge quality first. We also dig into the elusive aha moment in troubleshooting. AI can summarize long case histories, but spotting the hypothesis that changes the outcome still leans on human meaning making. The exciting frontier is assistive AI that recognizes patterns across cases, nudges better questions, and shortens time to insight without sacrificing judgment.

If you’re being pitched quick fixes that “solve knowledge with AI,” this episode offers a saner roadmap: build a resilient knowledge base, ground your models with RAG, and keep humans in the loop for accuracy and nuance. Subscribe, share with your support and product teams, and leave a review telling us: are you building your KB to make your AI better?

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Outages test more than systems—they test culture. We dig into what “calm under pressure” actually looks like, from the first hint of trouble to the final post‑incident review. Together with guest Kat Gaines of PagerDuty, we explore why support must be a core stakeholder, how trust and blamelessness turn heat into focus, and the small operational moves that make the next incident smoother than the last.

We start with the why: customers feel the wobble first, and support carries that weight. Clear roles, fast approvals for updates, and a cadence everyone understands protect users and the team. Kat shares how to make calm a measurable goal, not a motivational poster—think time‑boxed check‑ins, explicit ownership, and language that separates immediate action from root cause. We unpack retrospectives that actually change behavior, documenting principles so they hold during the toughest minutes, not just the easy ones.

We also talk about people. Training newcomers requires more than docs; it needs pairing, gentle course correction, and real reps in safe situations. The signal of maturity is when veterans guide first‑timers in the moment without chaos. Kat offers a powerful lens for jobseekers and leaders alike: watch a real incident to learn a company’s values. Healthy teams honor roles, communicate clearly, and iterate with intent. Finally, we map incident skills to career growth—cross‑functional coordination, high‑stakes comms, and judgment under pressure—showing how support pros earn visibility and create paths into leadership or adjacent teams.

If you want fewer escalations, faster updates, and a team that stays steady when it counts, this conversation gives you the frameworks and the human skills to build it. Subscribe, share with a teammate who handles the heat, and leave a review telling us the one change you’ll make before your next incident.

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Sauce jokes aside, we get real about AI in customer support: why it’s tempting to chase the trend, how early demos can mislead, and what actually works once you bring models into day-to-day operations. Rob Dwyer joins us to unpack the difference between toy and tool, sharing lessons from building conversational analytics and automated QA across diverse industries.

We dig into the myth of “one model to rule them all” and get specific about task fit. Generative models shine at qualitative judgments like tone, professionalism, and focus in short, discrete interactions. They stumble with counting, sequence checks, and multi‑step logic—especially across long, technical threads. That gap matters when you’re grading complex troubleshooting or evaluating revenue potential. We talk about the demo effect, why a few promising outputs aren’t proof, and how to set up meaningful evaluations with enough data to avoid false confidence.

If your world is regulated or highly technical, retrieval‑augmented generation (RAG) becomes essential. Grounding model answers in a current, curated knowledge base cuts hallucinations and keeps responses aligned with policy. But RAG is only as good as your content ops, which means version control, ownership, and clear guardrails. We also challenge the monolith instinct: mega‑suites promise simplicity yet often deliver stitched‑together mediocrity. A best‑of‑breed stack with clean integrations and strong observability gives you better performance and control.

You’ll leave with a practical framing: good use cases (assisted QA for tone and policy, summarization, intent clustering), maybe use cases (autonomy on complex workflows), and “oh hell no” zones (high‑stakes decisions without grounding or oversight). The throughline is patience—define the problem, validate with real samples, measure cost per correct outcome, and keep humans in the loop where it counts. Subscribe for more clear-eyed conversations on building support that’s fast, human, and genuinely smarter with AI.

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The alarms stop, but the real work is just getting started. Charlotte Ward and Kat Gaines pull back the curtain on what effective teams do after an incident is resolved—how to pause, learn, and communicate in a way that actually strengthens trust.

We explore why a short breather prevents knee‑jerk conclusions, how to balance pressure for instant answers with thoughtful analysis, and what belongs in a preliminary update versus a full review. Kat explains how to structure a live, blameless postmortem, why support must be in the room as a source of customer signal, and the right ownership model for running the review. You’ll hear a practical flow for the meeting—shared timeline, missed details, what’s been done, and what’s next—plus how to use Five Whys to move beyond “who messed up” and into “what systems allowed this.”

Communication takes center stage. We get specific about writing external reports that avoid clichés, match tone to impact, and clearly state what will change to prevent a repeat. We dig into accessible language for differently skilled audiences, personal follow‑ups for key accounts, and how to invite customer questions as a final step in closing the loop. The mantra running through it all: fix systems, not people. By treating incident reviews as a chance to improve detection, playbooks, tooling, and ownership, teams turn a rough day into durable resilience.

If you care about incident management, customer trust, and making your next outage less painful than the last, this conversation packs a complete framework you can put into practice. Subscribe, share with your on‑call crew, and leave a review to tell us your top rule for a great post‑incident report.

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Ever wondered what distinguishes a true leader from the rest? Join me, Charlotte Ward, as I unlock the secrets of leadership potential within customer support teams alongside Meredith Malloy. Discover how to identify the "unicorns" among your team—those rare individuals who possess the natural empathy and connection skills that are foundational to effective leadership. Meredith sheds light on how these talents can transform into impactful leadership roles, enhancing both employee and customer satisfaction.

Meredith also offers invaluable guidance for those aspiring to lead, stressing the importance of proactive engagement and a genuine passion for growth. She emphasizes the need for continual learning and curiosity, advocating for leadership driven by authentic motivation rather than mere title or salary allure. Together, we explore the journey of nurturing future leaders, providing them with the necessary resources and support to thrive. Tune in to learn how spotting and cultivating leadership talent can bring about positive, far-reaching changes within your organization.

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Unlock the secrets to mastering technical support as we, Robert Cabral and I, guide you through the art of enlisting engineering support for complex inquiries. You'll discover how data-driven strategies can transform your support processes, leading to a drastic reduction in ticket escalations. Robert shares his expertise on creating a robust taxonomy for categorizing issues, ensuring clarity and efficiency in resolving them. We promise you'll leave with actionable insights into improving collaboration between support and engineering—essential knowledge for anyone navigating the SaaS landscape of platforms like DataCamp.

Robert and I also delve into the power of empathy and continuous improvement in fostering a proactive support environment. By embedding support team members within engineering, we’ve not only improved communication but also decreased escalations from 40% to under 10%. Our conversation sheds light on the importance of strategic conversations, empathy-building, and securing engineering buy-in. Join us as we unravel the gradual journey of transforming support teams with small wins and iterative progress—your roadmap to a more efficient, less reactive customer service experience.

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Unlock the secrets to building a standout customer support team by tuning into our captivating conversation with Alyssa Purcell, a seasoned manager from New York City. Alyssa brings her expertise to the table, offering strategies for crafting precise job descriptions that attract the right candidates. She shares the nuanced art of balancing skills assessment with cultural fit, and the importance of having a diverse interview panel featuring both leadership and peers for a comprehensive evaluation process. You'll leave understanding how to identify the strengths and qualities necessary for each role, paving the way for effective hiring.

Alyssa also unveils her unique approach to interviews, providing real-time feedback to candidates as a means of gauging their potential for growth. Her insights on coaching peers for interviews, maintaining consistency, and reducing unconscious bias with quality feedback are invaluable for anyone in a hiring position. Whether you're bringing in newcomers for entry-level roles or seeking seasoned professionals, Alyssa's proven strategies will equip you with the knowledge to enhance your hiring process and improve candidate outcomes. Listen and transform your approach to hiring in customer support.