The Experience Edge

Speed is free. Accountability isn’t. Teams racing ahead with AI are building to convince, not to learn.Giu Vicente has spent 20 years in UX and product design and now leads product design at ServiceNow, where he builds for some of the largest enterprises in the world. In this conversation he explains why AI prototyping tempts teams to build to convince rather than build to learn, and why “bot sitting” can cost more time than it saves. He also covers why nobody has vibe-coded their own enterprise CRM, and why human judgment and accountability still anchor every AI-assisted decision.ABOUT GIUGiu Vicente is Director of Product Design at ServiceNow. He started out as a webmaster, moved into information architecture, and has worked in product design and UX for around 20 years. He designs enterprise software for large, often regulated customers, where adoption, governance and accountability shape what ships. He is best known for his grounded view of AI in enterprise design: embrace the speed, but keep the fundamentals of clarity, validation and customer understanding.KEY TAKEAWAYS- Clarity from leadership is what lets teams move fast without chasing their tails.- AI makes prototypes cheap, so use them to find what you missed, not to prove you’re right.- Speed is free, but skipping validation and critical thinking carries a real cost.- Spending more time babysitting your AI system than it saves you is a trap called bot sitting.- Enterprises won’t vibe-code their own tools because security, reliability and accountability still need an owner.CHAPTERS00:00 Introduction00:42 What thriving teams look like: clarity from leadership03:21 Right-sizing strategy: direction over destination and the appetite to be wrong06:27 Vibe coding and building to convince instead of building to learn11:14 Shifting left across the business, and why the electricity analogy matters for AI18:07 Is the epic-and-task model dead? Smaller teams, fewer gates22:58 Why enterprise adoption can’t keep pace with build speed24:33 Bot sitting: when maintaining your AI system costs more than it saves28:19 Control, governance and keeping humans in the loop for agents33:28 Why nobody has vibe-coded their own enterprise CRM35:10 Cross-functional collaboration as the work itself39:44 Why humans still matter: judgment, emotional jobs and AI slop44:46 Accountability, sycophantic AI and the cost of unchecked recommendations49:23 Advice for design leaders: embrace the new world, don’t forget the basicsLINKEDIN PROFILESGiu Vicente — https://www.linkedin.com/in/product-design-leader-director-user-experience-giuvicente/Jochem van der Veer — https://www.linkedin.com/in/jochemvanderveer/THEYDOLearn more about Journey Management with TheyDo: https://www.theydo.comSubscribe to The Experience Edge for weekly conversations on customer experience, journey management, and the future of enterprise CX. Share this episode with someone who’s thinking about how their organisation connects customer insight to real decisions.#TheExperienceEdge #Vicente #EnterpriseDesign #AIStrategy #ProductDesign #CustomerExperience #JourneyManagement #CX #TheyDo #podcast

A Salesforce design leader hasn't opened Figma in months. Her team builds first and researches after — and she says that's the right bet.Shir leads the Sales Planning design organisation within Salesforce's Sales Cloud, where her team no longer designs in Figma — they prototype and ship directly through AI coding tools instead. She and Jochem dig into what's actually shifting as design, product, and engineering roles blur together, why her team has chosen to build first and learn from real usage rather than front-load research, and where that bet risks brand trust, design-system consistency, and runaway token spend.ABOUT SHIRShir leads the Sales Planning design organisation within Salesforce's Sales Cloud, where she's building out a new product initiative from the ground up. She's based in the Netherlands, though most of her design organisation sits in San Francisco. Over roughly the past two years she's moved her team almost entirely off Figma, working instead directly in AI coding environments like VS Code and Cursor alongside engineers and PMs, with GitHub as the shared collaboration surface. She's candid about what that shift has cost — slower discovery, fraying design-system consistency — as much as what it's unlocked.KEY TAKEAWAYSSalesforce's design team no longer designs in Figma — they build directly in AI coding tools instead.Moving fast means discovery keeps losing to delivery, even when everyone knows the risk.PMs who thought AI made designers optional quickly learned good-looking flows aren't good experiences.Shipping fast and learning from real customers can beat exhaustive research — if you can stomach the mess.AI-era design systems are fraying because there's no shared library when everyone builds solo.CHAPTERS00:00 Introduction 00:37 Ditching Figma: Salesforce design's move to full AI-native prototyping 02:22 How roles are blurring across design, product, and engineering 05:03 Two models of convergence: PM-led versus design-led prototyping 09:29 Inside Salesforce Sales Cloud: where discovery and delivery are splitting 13:04 Building over learning: has discovery lost its place as step one? 17:45 The "spaghetti on the wall" problem: speed, trust, and brand erosion 22:26 The risk of a building-first culture drowning out research's warnings 25:25 Where the line is: protecting the core job to be done 28:44 Token spend as the new variable cost nobody's pricing yet 35:03 What Shir would change: design systems, GitHub, and a year of uncertainty 41:15 Staying one product: Slack, MCPs, and ecosystem cohesion 44:32 Where Shir's attention goes next — and why not everything needs to connectLINKEDINGuest: Shir — https://www.linkedin.com/in/shirzalzberg/ Host: Jochem van der Veer — https://www.linkedin.com/in/jochemvanderveer/THEYDOLearn more about Journey Management with TheyDo: https://www.theydo.comSubscribe to The Experience Edge for weekly conversations on customer experience, journey management, and the future of enterprise CX. Share this episode with someone who's thinking about how their organisation connects customer insight to real decisions.#TheExperienceEdge #Shir #AIDesign #VibeCoding #DesignSystems #CustomerExperience #JourneyManagement #CX #TheyDo #podcast

Most CX teams report satisfaction scores. If yours disappeared on Monday, whose week would actually break? That answer decides whether it survives AI.Rania Brand ran global CX and service design at Kimberly-Clark, where customer experience sits inside the operating model rather than beside it. In this conversation she argues that AI changes almost nothing about the CX equation — it only raises the cost of weak foundations — and explains why the teams that come through it will be the ones already load bearing somewhere else in the business. Along the way: why NPS only tells you a fire started, which KPIs are "in the now", and what enterprises should be copying from government digital services.ABOUT RANIARania Brand  is a senior product & experience leader, who was Associate Director of Global CX and Service Design, and Global Product Manager, at Kimberly-Clark. Before Kimberly-Clark she spent fifteen years at IBM, including four and a half years working in government, which she describes as the clearest example she has seen of experience operationalised as institutional capability rather than run as a programme. Her work centres on connecting customer experience to the KPIs a business already reports — revenue leakage, cycle time, inefficiency — instead of leaving CX to defend itself with satisfaction scores. She publishes on Medium and LinkedIn.KEY TAKEAWAYSAI is another actor in the blueprint, not a new equation — the foundations question is unchanged.NPS and CSAT tell you a fire started; they never tell you which room.If your CX team vanished and nobody's Monday broke, it was an initiative, not a function.CX survives by being load bearing inside supply chain, pricing and finance, not beside them.Solve deeply in one market, then export the design principles rather than the solution.CHAPTERS00:00 Introduction 00:30 Why AI doesn't change the CX equation 02:52 NPS tells you there's a fire, not which room 06:35 The shadow IT risk in democratised AI 11:15 Why CX teams resist AI out of fear 12:30 Load bearing CX versus CX as a department 16:48 The Monday morning litmus test 19:52 What enterprises can learn from government digital services 30:39 Why data foundations don't change how people work 35:38 Incentives versus more systems thinkers 40:16 The KPIs that are in the now 43:26 Getting analysts and CX teams in the same room 46:06 Sponsorship, agency and regional execution 50:53 Solve in one market, scale with design principles 54:25 Why change and adoption decides whether it sticksLINKEDIN🎙️ Guest: Rania Brand — https://www.linkedin.com/in/raniabrand/🎙️ Host: Jochem van der Veer — https://www.linkedin.com/in/jochemvanderveer/THEYDOLearn more about Journey Management with TheyDo: https://www.theydo.comSubscribe to The Experience Edge for weekly conversations on customer experience, journey management, and the future of enterprise CX. Share this episode with someone who's thinking about how their organisation connects customer insight to real decisions.#TheExperienceEdge #RaniaBrand #ServiceDesign #OperatingModel #AI #CustomerExperience #JourneyManagement #CX #TheyDo #podcast

Speed without craft creates undifferentiated products. The real cost of AI acceleration in financial services is the slow erosion of what makes experiences worth building.Julia Challicom leads Customer Strategy and Design for financial services at Deloitte Digital UK, helping tier-one banks and insurers transform the way customer insight shapes business decisions. In this conversation, she and Jochem dig into the tension between top-down pressure to go faster and the ground-level reality of data fragmentation, misaligned teams, and journey ownership that no one has truly solved - and why blindly replacing craft with AI tooling is a bet that will cost organisations more than they expect.About JuliaJulia Challicom is Customer Strategy and Design Lead for Financial Services at Deloitte Digital UK. She works with large-scale tier-one banks, insurers, and wealth management firms to transform customer experience and design customer-led services, with a particular focus on journey management, AI integration, and translating customer insights into business outcomes. She is a vocal champion of responsible and inclusive design, and is deeply concerned about the erosion of craft skills as organisations rush to automate. Her perspective is shaped by years working inside some of the UK's most complex financial institutions, giving her a practitioner's view of how transformation actually unfolds - and where it quietly stalls.KEY TAKEAWAYSOrganisations racing to go faster with AI are building the wrong things faster - alignment to customer journeys is the missing fix.Data access, data quality, and data architecture are all broken at once; no client is immune.Journey ownership fails when it's given to someone too junior, or a senior person with no freed-up capacity.Replacing craft with AI tools doesn't improve output quality - it just removes the people who caught the problems.Tokenomics is the next CFO conversation: agentic systems cost far more than the teams they were supposed to replace.CHAPTERS00:00 Introduction 01:47 Where the pressure to go faster actually breaks in enterprise CX 03:39 Why faster development without journey alignment produces more of the wrong things 04:34 The data problem: access, quality, architecture - and the cottage industries they create 08:11 Top-down strategy vs. ground-level AI sprawl: how to get a meaningful start 11:49 Why journey-centric working matters more than ever in financial services 18:22 The movement toward journey centricity: Lloyds, fintechs, and the ripple effect 20:41 Leading indicators of transformation: what to measure before satisfaction scores move 22:21 PI planning and the disconnect between discovery work and what actually gets prioritised 27:08 Journey ownership models: what works, what fails, and where it's still maturing 33:42 Journeys as a data model: the AI opportunity hiding in connected customer context 35:47 How the consultant's role is changing - and the slow erosion of craft that worries Julia most 43:00 KYC, agents, and the real ROI calculation of automating regulated journeys 48:02 Conversational journeys, AI search, and why the fundamental questions haven't changed 57:45 Tokens vs. time: how CFOs are starting to scrutinise the true cost of AI initiatives 01:04:30 Where to find Julia and the Deloitte–TheyDo allianceLINKEDIN PROFILESGuest: Julia Challicom - https://www.linkedin.com/in/julia-challicom/Host: Jochem van der Veer - https://www.linkedin.com/in/jochemvanderveer/THEYDOLearn more about Journey Management with TheyDo: https://www.theydo.comSubscribe to The Experience Edge for weekly conversations on customer experience, journey management, and the future of enterprise CX. Share this episode with someone who's thinking about how their organisation connects customer insight to real decisions.#TheExperienceEdge #Challicom #FinancialServices #AITransformation #DesignCraft #CustomerExperience #JourneyManagement #CX #TheyDo #podcast

Every CX leader can point to their data. Almost none can trace how it actually becomes a business decision.Jochem van der Veer breaks down the four-stage customer experience data lifecycle — signals, context, intelligence, and impact — that determines whether experience data ever turns into a measurable business outcome. He unpacks why behavioral data (clickstream, session recordings, product telemetry) is consistently undervalued compared to surveys, why most enterprises over-invest in signal collection while under-investing in the hardest, least glamorous stage — building a shared context layer, or customer experience ontology, that both humans and AI can reason over. Along the way he covers taxonomy and journey mapping as change management challenges (not just data problems), the three-layer ownership model for context governance, opportunity scoring and journey health as concrete intelligence outputs, and how to build the business case for CX investment using speed-to-resolution and cost-of-inaction metrics rather than abstract insight-to-impact claims. KEY TAKEAWAYSWhat customers say and what they do are correlated, but rarely the same signal.Survey response bias means you mostly hear from the angriest and happiest 5%.A shared taxonomy is a change management problem before it's a data problem.Context has three owner layers: source owners, curators, and governance.Cost of inaction on ignored recommendations is often the most persuasive metric.CHAPTERS00:00 Introduction — where does experience data actually go? 02:30 Stage one: signals and the behavioral data gap 05:00 Why surveys are overweighted and underinform 08:00 Stage two: context and building a shared ontology 10:00 The KYC example — recurring patterns across journeys 11:30 Why agreeing on taxonomy is an organisational problem 13:30 The AI magnification problem: siloed data, siloed meaning 15:00 The three ownership layers of a context model 19:00 Binding: turning ontology into a working system 20:00 Stage three: intelligence — descriptive vs. analytical outputs 21:30 Opportunity scoring and prioritising across journeys 22:30 Journey health and the Nordics manufacturing example 26:00 Stage four: impact and why it's also a feedback loop 30:30 The full model recap and where enterprises actually start 32:00 Making the case: speed and cost of inactionFOLLOW JOCHEMJochem van der Veer — https://www.linkedin.com/in/jochemvanderveer/THEYDOLearn more about Journey Management with TheyDo: https://www.theydo.comSubscribe to The Experience Edge for weekly conversations on customer experience, journey management, and the future of enterprise CX. Share this episode with someone who's thinking about how their organisation connects customer insight to real decisions.#TheExperienceEdge #JochemVanDerVeer #DataLifecycle #Ontology #JourneyHealth #CustomerExperience #JourneyManagement #CX #TheyDo #podcast

Service design promised to connect the dots. So why are service designers inside the same company still not talking to each other?Khayyam "Kai" Lasi is Journey Management Program Lead at Autodesk, where he's spent years scaling journey management from a lone title on an org chart to a company-wide operating system. In this conversation, he and Jochem get into why service design siloes itself from within, what it actually means to move from journey mapping to journey architecture, why "ownership" is the wrong mental model for CX practitioners, and how AI can reduce the internal politics that keeps teams from doing their best work.ABOUT KAIKhayyam "Kai" Lasi is Journey Management Program Lead at Autodesk. His career path has been far from linear - he moved from actuarial science into customer experience after discovering a stronger passion for people and solving complex problems, going on to build deep expertise in customer support, CX leadership, and journey management across Toronto startups, Scotiabank, and Autodesk. Over the past three and a half years at Autodesk, he's been foundational in scaling a journey management practice that now spans multiple teams and has influenced how the organisation hires and structures CX work. He's best known for combining analytical rigour with a systems-level view of customer experience - and for being unafraid to call out where the service design field is failing itself.KEY TAKEAWAYS➝ Service design siloes aren't just an org problem - they're a people problem that no tool or framework will fix.➝ Journey management is the operating system that keeps service design from becoming the wild west.➝ "Shepherd" beats "owner" - you can't shepherd a journey without building a flock of contributors.➝ Insight grain size matters: product managers don't want "onboarding is bad," they want capability-level specifics.➝ AI can create good baselines and remove language barriers between roles - but humans still have to come together.CHAPTERS00:00 Introduction02:07 Why service designers inside the same company don't talk to each other05:12 How organisational siloes corrupt the service design practice within them06:39 Journey management as the operating system for service design09:33 How Autodesk moved from a design-mature company to a journey management culture13:06 Building a journey architecture: heat-mapping, lifecycle data, and shared understanding19:49 From mapping stage to management stage - what comes next22:00 The community of practice gap and why standards need to be agreed, not assumed26:12 Lessons from agile: the danger of standardising flexibility out of a practice27:55 "Search before you create" - a standard worth fighting for34:48 How AI enables governance, reduces duplication, and removes language barriers between teams40:58 Organisational memory and the decision map concept49:29 Shepherding vs ownership - why vocabulary shapes culture55:02 How to reconcile journey thinking with team structures in complex organisations01:03:14 The one agent worth building next: internal context + accountability mapping01:07:42 How to reach Kai and closing thoughtsLINKEDIN PROFILESKhayyam Lasi - https://www.linkedin.com/in/khayyam-lasi/Jochem van der Veer - https://www.linkedin.com/in/jochemvanderveer/THEYDOLearn more about Journey Management with TheyDo: https://www.theydo.comSubscribe to The Experience Edge for weekly conversations on customer experience, journey management, and the future of enterprise CX. Share this episode with someone who's thinking about how their organisation connects customer insight to real decisions.#TheExperienceEdge #Lasi #JourneyArchitecture #ServiceDesign #OrganisationalMemory #CustomerExperience #JourneyManagement #CX #TheyDo #podcast

Half of CX teams are still just running surveys. The other half stopped reporting and started operating.Bill Staikos spent two decades in customer experience leadership at companies like American Express, BNY Mellon, and JPMorgan, and now writes the newsletter AI Not KPI. In this conversation, he explains why CX is splitting into a "bottom 50%" still stuck in survey-and-dashboard mode and a "top 50%" rebuilding around AI, data architecture, and operating models - and argues the role's most important relationship is shifting from the CFO to the CIO.KEY TAKEAWAYS- Half of CX teams still only run surveys- the rest have moved to an operating model.- When CX and the Chief Product Officer have "no daylight" between them, transformation accelerates.- The closed-loop model needs two new loops: orchestration (AI acting in real time) and learning (feedback improving the system).- CX leaders need data literacy and curiosity about tools like semantic layers and MCP, not just survey skills.- Start with the biggest business pain point, not the biggest customer pain point — the experience issue usually surfaces there anyway.CHAPTERS00:00 Introduction03:09 Why half of CX teams are stuck doing surveys05:48 The CX–CPO relationship as the biggest marker of change07:11 How insight teams are getting into product planning cycles11:02 What the top 5% of CX leaders do differently13:16 Should a survey-background CX leader be a red flag?15:45 Business acumen vs. data vocabulary — CX needs both17:32 Rethinking Bain's closed-loop model: adding orchestration and learning loops22:01 Should these loops be intentionally governed or left emergent?24:45 Hijacking existing rituals like PI planning to drive CX decisions26:59 A real example: redesigning how teams are measured beyond output29:52 From raw data to signal, context, intelligence, and impact33:04 Is CX at a crossroads about its own purpose?35:05 Why the most important CX relationship is now with the CIO, not the CFO39:09 Where to start building an internal customer context layer43:34 Why incentives and change leadership determine whether any of this works45:30 Inside Bill's newsletter: turning frameworks into usable artifactsLINKEDINGuest: Bill Staikos — https://www.linkedin.com/in/billstaikos/Host: Jochem van der Veer — https://www.linkedin.com/in/jochemvanderveer/THEYDOLearn more about Journey Management with TheyDo: https://www.theydo.com#TheExperienceEdge #Staikos #AIinCX #DataArchitecture #ClosedLoopFeedback #CustomerExperience #JourneyManagement #CX #TheyDo #podcast

Your AI agents aren't failing because the models are bad. They're failing because your data was built for humans, not machines. Jochem has spent years working on the structural problem underneath failing enterprise AI initiatives. In this episode, he breaks down why CX AI pilots stall after six to eight weeks, what an experience ontology actually is and how it differs from a taxonomy or tag list, and why the architectural decision of where your ontology lives - data layer versus AI layer - determines whether your AI investment compounds or drifts. KEY TAKEAWAYSAI pilots fail because the data environment was designed for human interpretation, not machine reasoning.Tagging the same word across systems is co-location, not integration — AI can't bridge that gap reliably.An ontology defines not just what things are, but how they relate and what an agent can do with them.Location primitives (journey, phase, step) give disparate data a shared address so it can finally connect.The architectural choice of where the ontology lives — data layer vs. tool layer — determines whether it scales or drifts.CHAPTERS00:00 Introduction — Why AI pilots hit a wall after six to eight weeks 01:45 The three lenses enterprises use to understand customers 03:10 Why co-location isn't integration and what breaks when humans leave the loop 04:47 The core problem: confident AI output with no traceable foundation 06:20 What an ontology actually is — and how it differs from a taxonomy 08:00 Location primitives: journey, phase, and step as shared address 09:30 Connecting VOC evidence and BI metrics to the same structural coordinate 10:30 Pattern primitives: spotting recurring opportunities across journeys 12:00 The KYC banking example — one named object, many product teams 13:30 The third job of an ontology: structural rules for what agents can do 15:00 Why data binding is where most CX data efforts actually break down 16:30 How a working ontology creates a self-reinforcing context layer 17:54 The critical architectural decision: data layer vs. AI layer 19:30 Why CIOs and CX leaders need to make this call together 21:00 Bringing it back: the real fix isn't a better model, it's a better foundation 22:00 How TheyDo is built as the data layer AI agents run onLINKEDINJochem van der Veer — https://www.linkedin.com/in/jochemvanderveer/THEYDOLearn more about Journey Management with TheyDo: https://www.theydo.comSubscribe to The Experience Edge for weekly conversations on customer experience, journey management, and the future of enterprise CX. Share this episode with someone who's thinking about how their organisation connects customer insight to real decisions.#TheExperienceEdge #vanderVeer #ExperienceOntology #CXAI #EnterpriseAI #CustomerExperience #JourneyManagement #CX #TheyDo #podcast

Your teams are drowning in customer data but can't act on it. Here's a 5-level framework that makes the customer journey your operating system.IN THIS EPISODEWhy another dashboard won't fix your customer data problemHow to connect what customers say with what they actually doWhy the customer journey — not your org chart — should organize your dataHow a "meaning layer" creates cross-team alignment without reorganizing teamsHow journey-structured data becomes an ontology that AI and agents can reason overCHAPTERS00:00 The real problem: a data organizing problem, not a data problem 02:19 The five layers, and why the journey is the organizing principle 02:19 Level 1 — Evidence: the qualitative voice of the customer 04:46 Level 2 — Measurement: KPIs and what customers actually do 06:00 The journey as the backbone that joins the dots 07:15 Pinning every signal and KPI to a moment in the experience 08:00 Level 3 — Meaning: surfacing the "why" (the Lufthansa baggage example)09:38 Level 4 — Cross-team connection and natural alignment 11:58 Level 5 — Business impact and competitive advantage 14:03 Putting it together: the journey as your operating systemFollow Jochem on LinkedIn:https://www.linkedin.com/in/jochemvanderveer/CONNECT WITH US:Website:    https://www.theydo.com/LinkedIn:   https://www.linkedin.com/company/theydo-journey-management/#CustomerExperience #CustomerJourney #JourneyManagement #CXStrategy #DataStrategy #VoiceOfCustomer #CustomerData #CXOps #AIagents #ProductStrategy

Your CX pitch lands with practitioners but dies with CEOs. Here's the messaging framework that fixes it. IN THIS EPISODEWhy CX leaders keep pitching the wrong message to the wrong room — and how to diagnose itHow to talk to a CEO or COO about customer experience without mentioning customer experienceWhat product leaders actually need to hear before they'll prioritise CX on the roadmapWhen to lead with technology — and why it's only right for one specific audienceThe two most common messaging mistakes CX teams make and how to avoid themCHAPTERS00:00 Intro — Why CX storytelling breaks down 01:04 The real-world example: energy company, call volume, cost mandate 02:10 Three audience buckets: Out-of-CX, CX-adjacent, CX expert 03:29 How to pitch the out-of-CX crowd (CEOs, COOs) 05:00 How to pitch the middle layer (product, marketing, brand) 08:08 How to pitch CX practitioners — and when to lead with technology 09:49 The full messaging stack: outcomes, use case, technology 10:30 Two mistakes to avoid: stacking arguments and mixing audiences 12:12 Key takeaways — same work, three different messagesFollow Jochem on LinkedIn:https://www.linkedin.com/in/jochemvanderveer/CONNECT WITH US:Website:    https://www.theydo.com/LinkedIn:   https://www.linkedin.com/company/theydo-journey-management/#TheExperienceEdge #CustomerExperience #CXStrategy #CXLeadership #CustomerJourney #JourneyManagement #CXMessaging #CostToServe #VoiceOfCustomer #CustomerInsights