Stay Sharp in Digital Engineering

Hosted by Razorleaf Corp.

Business Careers

Website RSS feed LinkedIn YouTube

Episodes

150

Latest episode

Aug 2026

Language

EN-US

About the show

Welcome to 'Stay Sharp in Digital Engineering,' the ultimate podcast for all things digital in the manufacturing industry by Razorleaf. Join us as we take a deep dive into the multifaceted world of digital transformation, exploring topics such as the digital thread, digital twins, IDEs, model-based strategies and delving into the frontiers of cutting-edge technologies like PLM, MES, Integration, and more. Our expert hosts, Jonathan Scott, Jen Ferello, Juliann Grant, and Eric Doubell, will be your guides, providing valuable insights, captivating interviews, and the latest industry updates to ensure you remain at the forefront of the ever-evolving digital landscape. Whether you're a technology enthusiast, a business leader, or simply curious about the digital realm in manufacturing, this podcast is your essential resource for staying sharp and well-informed.

Listen to episodes

60 recent

August 18, 202645 min

#149: Product Memory: The Context Layer Behind Every Product Decision

In this episode, we sit down with Oleg Shilovitsky, industry expert, author of Beyond PLM , and CEO of OpenBOM, to explore a transformative concept he calls "product memory." If you’ve ever looked back at a product design decision two years later and wondered, "Why did we make that choice?", you aren't alone. Oleg explains why product memory is the missing context layer that connects decisions to data, filling the gaps that traditional PLM, PDM, and ERP systems often miss. We discuss the "three parents" of product memory—including the critical role AI plays as a forcing function—and dive into the complex questions surrounding data ownership, security, and the future of business models in a post-SaaS world. Key Takeaways: What is Product Memory? It’s a context layer that captures the "why" behind decisions, relationships, and conversations across a product's lifecycle—not just the static records found in PLM. The Three Parents of Product Memory: The concept is born from the need to capture decision-making context, the technological capability of context graphs, and the acceleration provided by AI agents. AI as a Forcing Function: Unlike previous tech trends (like cloud adoption), AI requires structured context to be effective. Without proper "memory," AI agents hallucinate, making the capture of this context an urgent priority rather than a "nice-to-have." Security & Ownership: While product memory raises questions about data privacy and intellectual property, Oleg argues it should be treated like any other process—with clear protocols and security standards. Future of Monetization: As we move beyond seat-based SaaS models, the industry is exploring new ways to monetize data and outcomes, though the exact business models for product memory are still emerging. Resources Mentioned: Beyond PLM Blog: https://beyondplm.com Upcoming Book: From CAD Files to Product Memory by Oleg Shilovitsky (available soon via beyondplm.com ). If you found deep dive into the future of manufacturing valuable, please like, subscribe, and share it with a colleague or network peer who is tackling these same digital engineering challenges. Music is considered “royalty-free” and discovered on Story Blocks. Technical Podcast Support by Jon Keur at Wayfare Recording Co. © 2026 Razorleaf Corp. All Rights Reserved.

August 11, 202643 min

#148: The Question Every Digital Thread Has to Answer

What if you could answer a complex engineering change request in minutes instead of days? In this episode of Stay Sharp: In Digital Engineering , hosts Juliann Grant and Jonathan Scott welcome back Chris Finlay , former Vice President of Engineering Innovation at SAIC and current Digital Systems Engineering Director at Raytheon, to explore the tangible, practical benefits of the digital thread. We move past the buzzwords to discuss how to break down engineering silos, improve traceability, and implement a digital strategy that actually delivers value. Key Takeaways The Power of Traceability: Discover how digital threads allow you to query designs in real-time, moving from manual, document-based matrices to instantaneous verification. Breaking the Silos: Learn how a digital thread integrates disparate engineering domains—from systems architecture to mechanical CAD and software—allowing teams to collaborate without needing to master every single tool. The Role of Configuration Management: Understand why CM is the backbone of a successful digital thread, especially when moving from document-based artifacts to an "Authoritative Source of Truth." Start with the End in Mind: Get actionable advice on how to begin your implementation journey by focusing on your specific business goals rather than trying to trace every single data point at once. Episode Highlights Traceability on Steroids: Chris shares a real-world example from a Navy program where a complex engineering trace was completed in minutes, not days, saving hours of manual labor. The "Digital Cable" Concept: We discuss how the digital thread functions like a multi-strand cable, connecting various engineering disciplines and providing a single, consistent version of the truth. Impact Analysis: How a well-crafted digital thread enables you to perform impact analysis in minutes, revealing exactly which components are affected by a change—revealing complexity that was always there, but previously invisible. Overcoming Implementation Barriers: Advice for organizations of all sizes on how to start, when to automate, and why you should focus on "ad-libbing" and refining your processes rather than simply digitizing old workflows. Connect with Us Guest: Chris Finlay , Digital Systems Engineering Director at Raytheon Podcast: Stay Sharp in Digital Engineering Join the Conversation: Have questions for Chris or thoughts on this episode? Leave us a comment or contact us at podcast@razorleaf.com If you enjoyed this deep dive into digital engineering, please rate, review, and subscribe on Spotify or Apple Podcasts. Share this episode with a colleague who is looking to streamline their engineering workflows! Music is considered “royalty-free” and discovered on Story Blocks. Technical Podcast Support by Jon Keur at Wayfare Recording Co. © 2026 Razorleaf Corp. All Rights Reserved.

August 4, 202641 min

#147: Data Fiefdoms and Cheese: An Analyst's View of the Industry's Blind Spots

Beyond the Hype: Christine Longwell on AI, PLM, and the Future of Digital Engineering The digital engineering industry is experiencing one of its most significant periods of transformation in decades—but separating meaningful innovation from marketing hype has never been more challenging. In this episode of Stay Sharp in Digital Engineering , hosts Juliann Grant and Jonathan Scott welcome industry analyst Christine Longwell , founder of PLM Insights . Drawing on a career that spans mechanical engineering, software implementation, competitive analysis, market research, and consulting, Christine shares a unique perspective on where product lifecycle management (PLM), AI, and digital engineering are really headed. The conversation explores why understanding real customer challenges starts on the factory floor, why software vendors often struggle to understand small and medium-sized manufacturers, and how service providers are becoming trusted advisors in technology selection. Christine also discusses the rapid rise of AI, why organizations should be cautious of bold predictions, and why people—not technology—remain the biggest obstacle to digital transformation. If you're trying to make sense of today's AI landscape while planning for tomorrow's digital engineering environment, this episode offers practical insights grounded in decades of industry experience. In this episode you'll learn: Why successful digital transformation starts with understanding business processes—not just technology The importance of seeing customer challenges firsthand through factory visits and support teams Why SMB manufacturers remain underserved by traditional market research How AI is changing the PLM landscape—and where the hype ends Why organizational silos may be the biggest barrier to AI success The growing importance of trusted implementation partners and systems integrators Why independent customer research and win/loss analysis are becoming increasingly valuable How AI may accelerate convergence between PLM, ERP, and supply chain systems As AI reshapes the digital engineering landscape, one thing remains constant: successful transformation starts with understanding people, processes, and real business challenges—not just adopting the latest technology. Christine Longwell's unique perspective, spanning engineering, software vendors, market research, and consulting, reminds us that meaningful innovation comes from listening to customers, challenging assumptions, and making technology decisions based on business outcomes rather than hype. Whether you're evaluating PLM strategies, navigating AI adoption, or planning your next digital transformation initiative, this conversation offers practical insights to help you make smarter, more informed decisions. If you enjoyed this episode, subscribe to Stay Sharp in Digital Engineering on your favorite podcast platform so you never miss a conversation with industry experts shaping the future of product development and manufacturing. Have a question for Christine Longwell or a suggestion for a future episode? We'd love to hear from you. Leave a comment, reach out to the Razorleaf team, or email us at podcast@razorleaf.com . Be sure to share this episode with colleagues who are navigating AI, PLM, and digital transformation. Until next time, stay curious, stay connected—and Stay Sharp . Music is considered “royalty-free” and discovered on Story Blocks. Technical Podcast Support by Jon Keur at Wayfare Recording Co. © 2026 Razorleaf Corp. All Rights Reserved.

July 28, 202631 min

#146: CMMC Paused, Not Cancelled: Why Contractors Shouldn't Stop Now

Did the Department of Defense just put CMMC on hold? Not exactly. The Department of Defense recently announced a pause on one of the most significant upcoming requirements of the Cybersecurity Maturity Model Certification (CMMC) program, creating confusion across the defense industrial base. Does this mean contractors can slow down their cybersecurity efforts—or does it simply change how compliance will be evaluated? In this episode of Stay Sharp in Digital Engineering , hosts Juliann Grant and Jonathan Scott welcome back Steve Nichols , Razorleaf's government solutions expert, to explain exactly what changed, what didn't, and what defense contractors should be doing during this temporary pause. Steve breaks down the July announcement, explains why companies are not off the hook for CMMC compliance , and discusses why maintaining strong cybersecurity practices remains essential regardless of how future certification requirements evolve. In this episode, you'll learn: Why the government paused third-party CMMC Level 2 assessments What requirements still remain in effect The difference between self-certification and third-party certification The real costs of preparing for a CMMC assessment Why good cybersecurity hygiene is still critical How organizations should prioritize the 110 security controls What the government may change after the public comment period How small businesses could be affected Why waiting for final guidance may be a risky strategy How AI could eventually play a role in cybersecurity assessments Key Takeaways The current pause affects only the third-party assessment requirement for CMMC Level 2 certification. Organizations are still responsible for meeting applicable cybersecurity controls and certifying compliance where required. Companies should continue improving their security posture rather than assuming requirements will disappear. Steve also explains that cybersecurity compliance should be viewed as an ongoing business process—not a one-time audit. Organizations that continue improving their IT environment today will be in a much stronger position regardless of how the government ultimately adjusts the CMMC program. Featured Guest Steve Nichols leads Razorleaf Government Solutions practice, helping defense contractors navigate digital transformation, cybersecurity requirements, PLM strategy, and government compliance initiatives. His experience spans startups, commercial software companies, and federal programs, making him a trusted advisor for organizations operating within the defense industrial base. If your organization works with the Department of Defense or plans to enter the defense supply chain, this conversation will help you understand what today's changes mean—and how to prepare for what's next. 🔔 Subscribe for more conversations about digital engineering, PLM, cybersecurity, manufacturing, AI, and digital transformation. Music is considered “royalty-free” and discovered on Story Blocks. Technical Podcast Support by Jon Keur at Wayfare Recording Co. © 2026 Razorleaf Corp. All Rights Reserved.

July 21, 202638 min

#145: Why Nobody Can Predict Their Software Costs Anymore

Software licensing used to be one of the most predictable parts of an engineering organization's technology budget. You bought licenses, planned annual maintenance, and forecasted costs years in advance. But as AI assistants, cloud platforms, token-based licensing, and API-driven workflows become the norm, that predictability is disappearing. In this episode of Stay Sharp in Digital Engineering , co-hosts Juliann Grant and Jonathan Scott welcome back Paul Empringham , VP of CAD, Simulation, and PLM at NYBS Consulting, to explore how software licensing is evolving—and why engineering leaders need to start thinking differently about budgeting, governance, and AI consumption before costs spiral out of control. Building on their previous discussion about traditional licensing models, Paul explains why the industry's move to cloud platforms and tokenized licensing creates both opportunities and new financial risks. As AI becomes embedded directly into CAD, PLM, and engineering applications, organizations will need better visibility into software usage, stronger governance, and new strategies for managing unpredictable consumption-based costs. In this episode you'll learn: Why cloud and SaaS platforms are fundamentally changing software licensing How token-based licensing differs from AI token consumption Why AI assistants may create unpredictable engineering software budgets The hidden cost of API calls, automation, and AI-powered workflows How vendors are moving toward usage-based licensing models Why engineering leaders need guardrails before deploying AI at scale The importance of measuring software usage before negotiating renewals Why visibility into licensing has never been more important Key Discussion Topics The shift to cloud-first engineering software Software vendors are rapidly moving customers away from on-premises installations and toward cloud platforms. While this simplifies upgrades and accelerates feature delivery, it also reduces customer visibility into actual software usage. Understanding tokenization Paul explains the growing trend toward token pools, where engineering teams consume tokens for advanced capabilities across multiple software products instead of purchasing individual specialty licenses. This provides greater flexibility—but also introduces new complexity. AI changes everything As AI assistants become embedded inside CAD, PLM, and simulation tools, companies may soon be paying for both software licenses and AI consumption. Unlike traditional licensing, AI usage can fluctuate dramatically, making annual budgeting far less predictable. Managing the unknown Engineering organizations need better data than ever before. Understanding who uses which tools, how often they use them, and where AI is being adopted will become essential for controlling costs and preparing for future licensing changes. Memorable Quote "For the first time in our lives, I don't think we can predict what our software is going to cost us." Featured Guest Paul Empringham Vice President of CAD, Simulation & PLM NYBS Consulting Paul specializes in engineering software licensing, optimization, and governance for global manufacturing organizations. He has helped companies maximize software investments while navigating increasingly complex licensing models across the CAD, PLM, and simulation landscape. Music is considered “royalty-free” and discovered on Story Blocks. Technical Podcast Support by Jon Keur at Wayfare Recording Co. © 2026 Razorleaf Corp. All Rights Reserved.

July 14, 202641 min

#144: The Hidden Costs of Digital Engineering Systems

What if the most expensive part of your digital engineering environment isn’t the software license? In this episode, we sit down with Eric Smith , VP of Services at Razorleaf , to peel back the curtain on the "hidden" costs of running complex systems like PLM, MES, and CAD. We move beyond the initial project setup to explore the "sustainment" phase—where time, money, and productivity often drain away unnoticed. Whether you are in engineering, IT, or manufacturing leadership, this conversation provides a new framework for understanding why your environment is becoming increasingly complex and how to manage the unexpected challenges of modern digital infrastructure. Key Takeaways: ● The Sustainment Trap: While initial implementations get all the budget, the real costs reside in ongoing maintenance, break-fix cycles, and the "interoperability spaghetti" of modern system architectures. ● The Productivity Tax: Every update, patch, or system hiccup causes interruptions. Research shows that "deep work" recovery takes an average of 23 minutes after a distraction, making seemingly minor tech updates a massive hidden expense. ● IT vs. Engineering: We break down where the line should be drawn. IT excels at commoditized tasks (security, networks, cloud infrastructure), but "Digital Environment Sustainment" requires niche domain knowledge that often falls into a gray area between departments. ● The "Why Now?" Factor: The landscape has shifted from isolated systems to deeply integrated microservices, cloud-hybrid architectures, and heightened security requirements, making maintenance significantly more complex than it was a decade ago. Main Points: ● Defining Digital Environment Sustainment: Moving past "managed services" to a model that accounts for the specific, specialized needs of engineering and manufacturing software. ● The Architecture Explosion: How the shift from a single server to containerized microservices has exponentially increased the complexity of maintaining even a single application. ● The Human Cost: Discussing the importance of Change Management (OCM) and the high overhead of onboarding new engineers when systems are constantly evolving. ● Specialized Expertise: Why traditional, fixed-team managed services may not be enough to handle the deep subject matter expertise required for complex CAD/PLM/MES environments. Are you seeing these hidden costs in your organization? Let us know your "horror stories" or where you’ve seen the biggest drain on productivity. Drop us a comment or send us a note! If you found this episode helpful, please like, subscribe, and share it with your engineering team—it helps us keep the content coming. Music is considered “royalty-free” and discovered on Story Blocks. Technical Podcast Support by Jon Keur at Wayfare Recording Co. © 2026 Razorleaf Corp. All Rights Reserved.

July 7, 202641 min

#143: Build vs. Buy in the Age of AI-Assisted Coding

Artificial intelligence has dramatically lowered the barrier to software development, making it easier than ever for manufacturers, engineering organizations, and startups to build custom applications. But just because you can build your own software doesn't always mean you should. In Episode 143 of Stay Sharp in Digital Engineering , co-hosts Juliann Grant and Jonathan Scott welcome back Jonathan Girroir , Technical Evangelist at Tech Soft 3D, for a forward-looking discussion about how AI-assisted coding is reshaping engineering software development. Together they explore the growing "build versus buy" dilemma, why software components are becoming more valuable than ever, and how organizations should think about protecting their intellectual property while embracing modern cloud architectures. From AI-generated code and engineering toolkits to data hubs, APIs, and digital thread strategies, this episode examines the technology trends that will influence how manufacturers develop, deploy, and manage engineering software over the next decade. In this episode, you'll learn: Why AI-assisted coding is fueling an explosion of engineering software startups How manufacturers are building custom applications faster than ever When it makes sense to build software—and when buying is the better strategy How reusable software components accelerate product development Why data sovereignty has become a critical consideration The hidden costs of maintaining custom software How cloud delivery models and hybrid architectures are changing engineering workflows Why APIs and data hubs may become more important than traditional file formats The growing role of standards like STEP AP242, QIF, and Universal Scene Description (USD) Why connected engineering data is becoming one of manufacturing's greatest competitive advantages How digital thread strategies create richer AI training data for future innovation Key Takeaways AI isn't replacing engineering software developers—it's making software creation dramatically more accessible. Organizations now have the opportunity to prototype and deploy specialized engineering applications much faster than in the past. However, successful organizations won't simply build everything themselves. They'll carefully evaluate where commercial software provides mature capabilities and where custom development creates true competitive differentiation. The conversation also highlights an important shift occurring across manufacturing: engineering data is evolving from isolated files into connected, API-driven data ecosystems. Companies that invest in clean, connected digital thread data today will be better positioned to leverage AI tomorrow. Whether you're evaluating PLM modernization, developing engineering applications, or planning your organization's AI strategy, this episode offers practical guidance for making smarter technology decisions. Be sure to subscribe for more conversations on digital engineering, PLM, AI, MBE, digital thread, manufacturing, and engineering technology. Music is considered “royalty-free” and discovered on Story Blocks. Technical Podcast Support by Jon Keur at Wayfare Recording Co. © 2026 Razorleaf Corp. All Rights Reserved.

June 30, 202648 min

#142: What Leaders Need to Know About Software Licensing

Software licensing may not be the first thing engineers want to discuss, but it can have a massive impact on budgets, productivity, and digital transformation success. In this episode of Stay Sharp in Digital Engineering , hosts Juliann Grant and Jonathan Scott are joined by Paul Empringham, VP of CAD, Simulation & PLM at NYBS Consulting , to unpack the increasingly complex world of engineering software licensing. Drawing on decades of experience working with organizations including Rolls-Royce, BAE Systems, Red Bull Racing, JCB, and Sunseeker, Paul explains why many companies are unknowingly overspending on CAD, PLM, simulation, and engineering software—and how better data can dramatically improve licensing decisions. The discussion covers the evolution from perpetual licensing to subscriptions, named-user models, and cloud licensing, along with practical strategies for optimizing license usage, avoiding costly compliance mistakes, and negotiating smarter renewals. Whether you're an engineering leader, IT professional, procurement specialist, or PLM administrator, this episode offers actionable advice that can save your organization significant time and money. Key Topics Discussed: How engineering software licensing has evolved from perpetual licenses to subscription and cloud-based models The differences between concurrent, named user, and subscription licensing Why engineering, IT, and procurement all play critical roles in software purchasing What software license optimization actually means—and why usage data matters Common licensing mistakes that lead to unnecessary costs and compliance risks How organizations can negotiate license "remixes" instead of purchasing additional software The future of engineering software licensing, including token-based consumption models Key Takeaways: Know How Your Software Is Really Being Used Most organizations don't actually know how many licenses they need. Monitoring real-world usage reveals idle licenses, underutilized features, training gaps, and opportunities to reduce costs without impacting productivity. Don't Buy Bigger Bundles Than You Need Vendors often encourage customers to purchase larger software bundles with additional features. Without usage data, companies frequently pay for capabilities they rarely—or never—use. Compliance Is More Complicated Than You Think Many licensing violations happen accidentally. Geographic restrictions, shared logins, outdated contract terms, and improper license usage can all create compliance issues that organizations don't discover until an audit. License Data Creates Better Negotiations Understanding actual license utilization gives organizations leverage during renewals. Instead of automatically renewing everything, companies can negotiate license remixes, exchange unused products, or right-size their environment. The Licensing Landscape Is Still Changing Engineering software continues to evolve toward subscription, cloud delivery, and token-based consumption. Organizations should understand where their software vendors are headed before making long-term purchasing decisions. Memorable Quotes: "Most companies simply don't know who's using which software—and where." "Knowledge is power when you're negotiating software licenses." "Don't be afraid to ask for a license remix. Everything is negotiable." "Start small, understand your usage, and build from there." Connect With Us: Have questions about software licensing or want to continue the conversation? Leave a comment or reach out to the Stay Sharp team. If you enjoyed this episode, be sure to subscribe, leave a review, and share it with a colleague who manages engineering software. Stay Sharp in Digital Engineering is the podcast exploring the people, technologies, and ideas shaping the future of product development, manufacturing, and digital transformation. Music is considered “royalty-free” and discovered on Story Blocks. Technical Podcast Support by Jon Keur at Wayfare Recording Co. © 2026 Razorleaf Corp. All Rights Reserved.

June 23, 202645 min

#141: Finlay's Five Firsts - A Field Guide to Digital Engineering Adoption

Getting New Methodologies Off the Ground: Lessons from Digital Engineering Transformation with Chris Finlay Implementing a new engineering methodology sounds straightforward on paper. In reality, it often means navigating organizational resistance, changing long-standing habits, proving value quickly, and building momentum one success at a time. In this episode of Stay Sharp in Digital Engineering , hosts Juliann Grant and Jonathan Scott sit down with Chris Finlay , Vice President of Engineering Innovation at SAIC , to discuss his journey helping organizations adopt Model-Based Systems Engineering (MBSE), digital engineering, digital thread strategies, and AI-enabled engineering practices across the defense industry. Chris shares candid stories from the front lines of transformation, including early MBSE projects, lessons learned overcoming resistance, and the practical strategies that helped move digital engineering from experimentation to enterprise adoption. Key Topics Discussed The Accidental Start of Digital Engineering Chris recounts how one of his earliest experiences with what would later be called MBSE started simply as a way to manage overwhelming engineering complexity. By leveraging modeling tools and connecting data across engineering artifacts, his team unknowingly created one of their first digital threads long before the term became commonplace. Why Resistance is Normal New methodologies often challenge established workflows and expose inefficiencies. Chris explains why resistance from program leaders and engineers isn't necessarily opposition—it’s often a rational response to perceived risk. Successful transformation requires empathy, patience, and meeting people where they are. The Power of Quick Wins One of Chris's strongest recommendations is to avoid trying to "boil the ocean." Instead, organizations should identify a manageable use case, demonstrate measurable value quickly, and build momentum through visible successes. The Story of the Skeptical Product Owner Chris shares a memorable example of an engineering leader who entered a model review determined to prove MBSE didn't work—only to immediately identify critical issues that the model exposed. The experience became a powerful demonstration of how digital engineering can reveal problems earlier and at lower cost. Finlay's Five Firsts of Digital Engineering Chris outlines the principles that have guided his transformation efforts for over a decade: Digital engineering is not a substitute for good systems engineering. Digital engineering exposes bad engineering practices faster. Connected data enables the digital thread—but avoid overconnecting everything. You cannot hire your way out of transformation; upskilling is essential. Organizations that haven't started their digital engineering journey are already behind. The Gray Beard Phenomenon One of the most interesting insights from the discussion is Chris's "Gray Beard Phenomenon." Engineers working closely with digital models rapidly become subject matter experts because they gain access to the system's "crystal ball"—the connected knowledge captured within the model. Measuring and Celebrating Success Transformation efforts gain traction when organizations track meaningful metrics and celebrate progress. Chris emphasizes that cultural change requires both measurable outcomes and visible recognition of teams that deliver value. Key Takeaways Digital engineering succeeds when it solves real problems, not when it is adopted for its own sake. Cultural transformation is often more challenging than technology implementation. Early wins build credibility and momentum. Metrics help drive behavioral change and secure organizational support. Upskilling existing teams is often more effective than hiring new specialists. Celebrating success is critical for sustaining transformation efforts. About the Guest Chris Finlay is Vice President of Engineering Innovation at SAIC, where he leads enterprise digital engineering transformation initiatives spanning MBSE, digital thread, digital twin, and AI-enabled engineering. With more than 20 years of experience in defense systems engineering, Chris has helped scale digital engineering capabilities across major organizations and mission-critical programs. Connect With Stay Sharp in Digital Engineering Have questions about digital engineering transformation, MBSE adoption, or digital thread strategies? Leave a comment, connect with the Razorleaf team, or reach out to continue the conversation. Music is considered “royalty-free” and discovered on Story Blocks. Technical Podcast Support by Jon Keur at Wayfare Recording Co. © 2026 Razorleaf Corp. All Rights Reserved.

June 16, 202639 min

140: Share PLM Summit 2026 Recap

Human-Centered PLM, Practical AI, and the Future of Digital Engineering What happens when you take a traditional PLM conference out of a corporate convention center and place it inside a Spanish bodega with a dirt floor? According to the attendees of the Share PLM Summit 2026 , you create an environment where people—not technology—become the focus of the conversation. In this episode of Stay Sharp in Digital Engineering , hosts Juliann Grant and Jonathan Scott welcome Razorleaf International team members Ashish Kulkarni and Luc Van Helmerijck to share their firsthand experiences from the Share PLM Summit in Jerez de la Frontera, Spain. The discussion explores standout presentations, emerging AI use cases, organizational change management, and why Share PLM continues to redefine what a modern industry conference can be. Key Topics Discussed: A Different Kind of PLM Conference Unlike traditional industry events, Share PLM intentionally creates a more human-centered experience. The unique venue, informal atmosphere, and collaborative discussions encourage meaningful conversations about the people side of digital transformation. The Mood Barometer: Measuring Change Management Success One of the most memorable presentations came from Andreas Wank of Pepperl+Fuchs, who shared his company's PLM implementation journey through a "mood barometer." Instead of focusing solely on project milestones, the presentation tracked employee sentiment throughout the project lifecycle, highlighting the critical role organizational change management plays in successful PLM deployments. Practical AI Use Cases in PLM Antonio Casaschi from ASSA ABLOY presented eight real-world AI applications being used across the organization. Rather than discussing AI as a future possibility, the presentation demonstrated practical ways AI can help companies better capture, organize, and leverage institutional knowledge. Key takeaways included: AI should augment people, not replace them. The greatest value comes from solving business problems, not simply deploying technology. Organizations should focus on current-generation AI capabilities rather than outdated perceptions of AI tools. AI Happens With People, Not To People A presentation from Share PLM co-founder Helena Gutierrez emphasized a powerful concept: "Make AI something that happens with people and not to people." Her framework highlighted how organizations can automate commodity tasks while elevating uniquely human contributions such as creativity, decision-making, and strategic thinking. PLM's Role in the AI Era While AI dominated many conversations, attendees agreed that PLM remains foundational. Rather than replacing PLM, AI is creating new opportunities to improve adoption, simplify implementation, and enhance productivity across product development organizations. The Concept of "Cognitive Surrender" Industry thought leader Jos Voskuil explored both the promise and risks of AI, introducing the concept of "cognitive surrender"—the growing tendency for people to outsource thinking to AI systems. The discussion balanced optimism about innovation with caution about maintaining critical thinking skills in an AI-driven world. Networking That Actually Matters Beyond the presentations, attendees highlighted the value of the event's networking opportunities. The informal setting fostered meaningful conversations among consultants, software providers, customers, and industry leaders, leading to potential partnerships, customer discussions, and collaboration opportunities. Episode Highlights: Why Share PLM's unconventional format continues to resonate with attendees How Pepperl+Fuchs used employee sentiment to guide a PLM transformation Eight practical AI use cases being deployed at ASSA ABLOY Real-world examples of AI augmenting product lifecycle management The growing debate: Is AI evolutionary or disruptive for PLM? Lessons learned from industry leaders navigating digital transformation How Razorleaf's Clover integration platform sparked conversations across the event Featured Guests: Ashish Kulkarni Director of Growth, Razorleaf International Luc Van Helmerijck Business Development and Strategic Alliances Leader, Razorleaf International Listen and Subscribe If you enjoyed this episode, subscribe to Stay Sharp in Digital Engineering and join us as we explore the technologies, processes, and people shaping the future of product development and manufacturing. Music is considered “royalty-free” and discovered on Story Blocks. Technical Podcast Support by Jon Keur at Wayfare Recording Co. © 2026 Razorleaf Corp. All Rights Reserved.