318: Who's Got Time for Automation When They've Got a Queue to Work Through?; with Brian Levine

Send us Fan MailWhen a customer asks a “simple question”, your org chart doesn’t matter. What they feel is speed, clarity, and whether they’re being helped or being handed off. That’s why we sat down with Ulrike Pitschke again, now leading Customer Success at Staffbase, to get honest about the real seam between customer support and customer success and how to make it stronger as a SaaS company scales.We talk about the practical split that actually works: support as the expert home for technical issues, ticket workflows, and efficient problem-solving, while CSMs drive proactive enablement, adoption, and strategic account outcomes. We dig into how the two teams operate on different cadences (ticket queues versus quarterly planning) and what that means for hiring, daily collaboration, and setting clear ownership without building silos.The best collaboration shows up when product changes land. Support brings the hard numbers and recurring patterns from Zendesk, while customer success brings the customer narrative from calls, renewals, and executive expectations. We cover how to align on beta features, prevent predictable ticket floods, and translate field feedback into roadmaps and timelines. We also get into shared tools and habits, including Zendesk access for CSMs and Slack channels that keep context from fragmenting.If you’ve ever worried that telling a customer “please contact support” sounds like rejection, you’ll take away language, structure, and team practices that keep the experience seamless and fast. Subscribe for more conversations like this, share the episode with a support or CS leader you work with, and leave a review with your best tip for making handoffs feel effortless.Support the show

Send us Fan MailYour support queue will always be there tomorrow, so “I’ll automate when things calm down” quietly becomes “never.” Charlotte Ward sits down with Brian Levine to get brutally practical about finding time for automation and using today’s AI tools without turning your job into a second full-time job. We talk about why the barrier to building support workflows has dropped so fast, and how that changes what a support leader can reasonably own.We break automation into three buckets: customer-facing flows, internal agent assist, and the overlooked one that unlocks everything else: personal automation. The goal is to start absurdly small. If a task is tedious, repetitive, or you simply hate doing it, that’s a perfect candidate. We swap real examples, from cleaning up messy Notion exports into branded PDFs, to letting an AI assistant handle the sorting work behind LinkedIn prospecting, to drafting queue-based insights you can use for voice of the customer reporting.Then we go deeper than time savings. AI can give support teams new perspectives on the queue by scanning for nuance humans miss, like buried promises to customers, mismatched timelines, and low-volume issues that are quietly trending upward. We also cover what changes in your build vs buy decisions once you’ve shipped a few small tools yourself, plus where security, permissions, and PII need to be part of the conversation.If you want practical ideas you can try this week, hit play, share this with a fellow support ops leader, and subscribe for more. After you listen, what’s the first task you’d love to never do again?Support the show

Send us Fan MailAI is moving so fast that it’s not just improving customer support, it’s changing what “support software” even is. We sit down with Andrei Kamarouski to unpack the real shift from the pre generative AI era, when teams spent months collecting data and training narrow models, to today’s world where language-first AI can classify tickets, analyse conversations, and accelerate product development with far less setup. If you lead support, CX, or support ops, this is a practical look at why the pace of tooling change feels so intense right now. We dig into the progression from analytics that simply shows signals, to AI copilots that make recommendations, and then to more autonomous agents that can help manage workforce decisions, SLA risk, and operational trade-offs. The big theme is judgement: where it’s realistic to automate rational, rules-driven decisions, and why high-quality context, clear policies, and transparent decision logic matter if you want automation you can trust. Then we go straight at the build vs buy question. When AI makes building cheaper, some teams can rebuild the core of a “mini Zendesk” internally and stop paying for features they never use. We also talk about the downside of big platforms that acquire tools that never fully integrate, and why the next generation of customer support tools will need tighter horizontal integration and far more personalisation. Finally, we look ahead to a near future where customers send AI representatives to negotiate with your AI and nobody forgets the details. If you’re rethinking your customer support stack, listen now, subscribe for more conversations like this, and share the episode with a support leader who is weighing build vs buy.Support the show

Send us Fan MailSupport teams don’t burn out only because the queue is busy. They burn out when the work feels endless, the career path feels foggy, and “helpful” side requests turn into untracked shadow ops that swallow the day. Charlotte Ward and Alec Moloney dig into what it takes to make customer support a final destination: a place where talented people build long, healthy careers and feel real pride in the craft.We get practical about structure in SaaS and B2B support: job levels that create clear progression, roles built for problem solving, and why you can have growth without building a two-tier system that removes senior folks from customers. We also talk about how leaders should capture the moments that matter such as incident handling, escalations, and customer wins then pair that evidence with measurable KPIs so promotions and recognition feel fair.Culture is the glue. We explore why a positive reputation outside the team doesn’t automatically fix the day-to-day inside it, how a clear vision plus strategy reduces uncertainty, and why “mechanisms” like feedback loops, escalation pathways, and cross-functional routines give the team the confidence to act. We close with a vital skill for every support professional: learning to say no politely, protect scope, and keep the work visible.If you want stronger retention, better performance reviews, and a support org that feels like a career, not a trap, press play. Subscribe, share this with a support leader, and leave a review with your biggest takeaway.Support the show

Send us Fan MailYou can change careers without throwing away everything you’ve built, but only if you can explain what you’re carrying with you. We sit down with Cynthia Ng, whose path runs from secondary school teaching to being a technology librarian, then into remote customer support at GitLab, and later into strategy and operations. Along the way, she’s had to translate her experience across wildly different job titles and hiring expectations, which makes her perspective incredibly useful if you’re planning a move into support or looking for a way out.We dig into what transferable skills really are, including the underrated technical ones like reading code, learning new tools quickly, and understanding fundamentals well enough to operate in a developer-focused environment. Then we spend most of our time on the big differentiator: soft skills. Communication, prioritisation, ownership, conflict handling, de-escalation, and cross-functional collaboration sound “soft” until you learn how to present them as measurable outcomes. We share practical examples of how to turn fuzzy claims into proof on a resume and in interviews.We also get tactical about finding your next growth area. We talk through using internal career matrices and leveling guides, comparing job descriptions, scanning job boards for patterns, and having coffee chats with people already doing the role you want. If you’ve ever struggled to name what you’re good at, or felt stuck on the support hamster wheel, you’ll leave with a clearer map and better language for telling your story. If this helps, subscribe, share the episode with a friend in support, and leave a review so more customer support leaders can find it.Support the show

Send us Fan MailSupport still gets treated like the lobby, not the building. If you’ve ever heard “So what do you want to do after support?” this conversation is for you.Charlotte Ward sits down with Alec Moloney to unpack “support as a final destination” and why perception is the first battleground. We talk about the hangover from call centre era thinking, the stubborn myth that great support people must eventually “move on,” and how that story quietly shapes hiring, retention, pay, and internal respect. This is part one of a two-part arc, focusing on the outside-in view: how the rest of the company sees customer support, and how that view becomes self-fulfilling.We get practical about what actually changes minds: strong support leadership, consistent advocacy, and a narrative grounded in real outcomes. Alec and Charlotte dig into progression frameworks that don’t cap talented people at “L1, L2, L3,” and why growth should include ownership, operations, quality work, and problem-solving not just deeper technical specialisation. We also share a simple tool that makes the story repeatable: a support report that tracks performance, shows improvement over time, and educates the wider business on what support really does.If you care about customer experience, support operations, technical support, or building a real customer support career path, hit play. Subscribe, share this with a support leader, and leave a review with your take: what would make support feel like a destination at your company?Support the show

Send us Fan MailYou can feel the ground shifting in customer support right now: AI is giving non-technical leaders the ability to build. I sit down with Italo Belandria, Head of Customers at Ringover, to unpack what that actually looks like day to day when you are responsible for customer success and customer support operations but you are not an engineer. We talk about moving beyond “AI writes emails” into AI-driven prototyping, where you create a working draft of a workflow and bring something real to product and engineering so they can make it scalable and secure.Italo shares how he uses AI agents to speed up product testing and internal documentation by recording a quick walkthrough, generating structured notes, and then validating the output before sending it on. We also dig into a customer support analytics story where a client believed average ticket resolution was 28 days. By analysing every ticket event with an AI workflow, Italo uncovered the real cause: an automation that updated tickets long after they were solved, making the metrics look terrible. The result is a clearer customer narrative, stronger trust, and a repeatable internal tool for future account reviews.Then we zoom out to the part most teams underestimate: change management. If one leader builds everything, everyone else can freeze. We talk psychological safety, getting teammates comfortable sharing rough prototypes, and why the next frontier is connecting all those mini tools into one coherent support operations ecosystem that shares data cleanly. If you care about AI in customer support, customer experience, and modern support leadership, this one will give you practical moves you can try immediately. Subscribe, share this with a support leader who is experimenting with AI, and leave a review telling us what you want to automate first.Support the show

Send us Fan MailYou’re going to die, and pretending otherwise is a terrible project plan. Val Turner joins us with a blunt premise and then makes it surprisingly hopeful: if you accept the timeline, you can design better defaults for your family, your future self, and even your team at work.We start with Val’s path from customer support into product leadership and the constant translation work it requires. Support urgency is real and immediate, while product urgency is scheduled and constrained. That gap breaks the customer feedback loop in countless companies, even the ones drowning in data. We dig into the human layer behind the process fixes: team “cultures” inside the same organisation, conflict management as a practiced skill, and why AI can push us toward avoidance instead of clarity.Then we go where most workplace podcasts do not: death planning, digital legacy, and the practical mechanics that keep everything from falling apart. Val shares the idea of a physical “death binder” that spells out where to find critical information, how trusted people can access accounts when it matters, and why redundancy and regular updates are more important than perfection. We also talk about prioritising life goals while health, time zones, and family stages make them possible, plus how the same thinking improves documentation, delegation, and decision-making at work.If you want a conversation that ties customer support leadership, product prioritisation, and real-life planning into one clear message, hit play. Subscribe, share this with a friend who needs the nudge, and leave a review with the one goal you refuse to keep postponing.Support the show

Send us Fan Mail“Escalate to engineering” sounds normal, but it quietly shapes how your whole company treats support. We challenge that default and replace it with a more accurate model: routing work to the right skill set, while keeping escalation for the moments that truly need higher priority and attention. Along the way, we explore how small language choices change ownership, expectations, and trust between customer support and engineering teams.Alex Batchelor, founder and CEO of Pebble, shares what happens when support gets the same technical context engineers use: logs, error monitoring, product analytics, documentation, and code-level clues. We talk about turning customer signals into product improvements without getting trapped at either extreme of the spectrum: raw data with no story, or vivid anecdotes with no proof. The goal is practical support operations that reduce context switching, shorten time-to-resolution, and create feedback loops engineering can actually act on.We also dig into proactive support and the future of AI in customer support. If your systems can detect an integration token expiring or a recurring error before a customer files a ticket, you can reach out first and create a genuinely delightful customer experience. And as automation handles the basics, we look at where humans add the most value: building the support system, solving the hardest technical tickets, and delivering consultative support that feels closer to a partnership than a transaction.If you want tighter engineering collaboration, cleaner ticket routing, and a more scalable technical support model, listen now. Subscribe, share this with a support or engineering leader, and leave a review with your biggest takeaway.Support the show

Send us Fan MailChaos in customer support rarely starts as chaos. It starts as “organic” growth, a few heroic workarounds, a helpful engineer jumping into Zendesk, or a fast acquisition that bolts on a new product and a new team without a shared operating system. Then the outcomes get unpredictable: escalations drag, customers hear different answers, and everyone feels busy while nothing feels steady. We dig into how to bring cohesion back without killing the good parts that made the team successful in the first place.Colin Flanigan joins me to unpack what he does in technical support leadership across B2B SaaS, including the messy reality of joining after rapid change. We talk about the first weeks on the job as a blend of journalist and analyst: running a genuine listening tour, collecting complaints as signals, building a friction map, and then validating the story with real support metrics. From there, we explore how to use proven frameworks (not rigid prescriptions), where bespoke work matters most (especially voice of the customer programs), and why many “technical” problems are actually broken communication systems across teams.We also go deep on the human side of change management: how to earn trust even when people do not fully agree, how to recruit champions from the people who care most about specific pain points, and why early wins in the first 60 to 90 days matter. We finish with practical leadership tactics like disagree-and-commit, time-boxed experiments, not optimizing for edge cases, and setting clear boundaries between support, engineering, and product so goodwill does not turn into resentment.If you want sharper support operations, stronger cross-functional alignment, and more predictable customer experience outcomes, listen now. Subscribe, share this with a support leader who is cleaning up chaos, and leave a review with the one boundary you wish your org would clarify.Support the show