Stay Sharp in Digital Engineering

What’s driving the future of manufacturing execution, MRO, and digital operations in aerospace and defense? In this special on-site episode of Stay Sharp in Digital Engineering, the Razorleaf team recaps their experience at the iBase-t Excelerate 2026 conference in National Harbor.Jonathan Scott and Juliann Grant share insights from customer presentations, emerging AI strategies, MES modernization efforts, and the growing push toward model-based manufacturing. From practical upgrade strategies to global deployment challenges, this episode explores how manufacturers are balancing innovation with operational realities.The event highlighted a clear industry shift: manufacturers are under increasing pressure to modernize quickly while maintaining quality, compliance, and production continuity. Discussions throughout the conference focused on pragmatic digital transformation, data integration across the “golden triangle” of ERP, PLM, and MES, and how AI can be securely and effectively embedded into enterprise systems.The team also discusses:GE Aerospace’s large-scale Solumina deployment for MRO and sustainment iBase-t’s practical AI strategy and security-first approach Real-world MES upgrade lessons from Honeywell and Razorleaf Global rollout strategies across multiple manufacturing sites Model-based work instructions and AI-powered data ingestion Integration architecture challenges and the role of connected data Why manufacturers are moving faster than ever to eliminate paper processes Beyond the technology, the episode captures the collaborative spirit of the iBase-t community — where even competitors openly share lessons learned to improve manufacturing outcomes across the industry.If you’re involved in MES, manufacturing operations, aerospace and defense, or digital transformation initiatives, this episode offers a grounded look at where the industry is heading next.Listen & SubscribeStay connected with Stay Sharp in Digital Engineering for conversations focused on digital transformation, manufacturing technology, PLM, MES, AI, and the future of product innovation. Music is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

What happens when traditional Product Lifecycle Management (PLM) meets the fast-moving world of retail and apparel?In this episode of Stay Sharp in Digital Engineering, hosts Juliann Grant and Jonathan Scott sit down with returning guest Brion Carroll to explore how PLM evolved beyond engineering-heavy industries into fashion, footwear, and retail.Brion shares firsthand insights from building one of the first retail-focused PLM solutions—revealing why apparel required a completely different mindset, how FlexPLM was born, and what lessons every industry can take from retail’s speed, complexity, and creativity.From colorways and line planning to supplier collaboration and real-time change, this conversation uncovers how retail pushed PLM to become more flexible, visual, and business-centric.Key Topics CoveredWhy traditional PLM didn’t work for apparel and retailThe shift from “parts and assemblies” to materials and stylesUnderstanding style, colorways, and seasonal product variationWhy costing comes before design in footwearThe role of suppliers as active collaborators in product developmentHow line planning and merchandising changed PLMThe need for visual, intuitive user experiencesManaging rapid, continuous change vs. formal engineering change processesThe importance of multi-team collaboration across the businessBuilding FlexPLM and lessons from early customers like Timberland and ReebokWhy a single, shared bill of materials (BOM) mattersConnecting PLM with upstream and downstream systems (ERP, supply chain, etc.)Key Takeaways1. PLM Must Serve the Entire BusinessRetail proved that PLM isn’t just for engineering—it must support design, merchandising, sourcing, supply chain, and more.2. One Product, Many ViewsA unified BOM with multiple views enables different teams to work from the same data without duplication or inconsistency.3. Speed Changes EverythingRetail operates in rapid, iterative cycles—requiring PLM systems to be flexible, responsive, and user-friendly.4. User Experience MattersCreative teams need visual, intuitive interfaces—not engineering-style data structures.5. Collaboration is CriticalFrom internal teams to global suppliers, successful PLM depends on seamless data sharing and connectivity.Notable Quote“There’s really no difference in the core of PLM across industries—the difference is how you apply it and who you bring into the process.” About the GuestBrion Carroll is CEO and Principal Consultant at Digital Solution Group, LLC and a pioneer in PLM, including early development of retail-focused solutions like FlexPLM. He has decades of experience helping organizations connect product data across the digital thread—from concept to market.Listen & SubscribeStay tuned for more conversations on digital engineering, PLM, and the technologies shaping product innovation.Music is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

What’s next for the Aras Innovator community heading into 2026?In this episode of Stay Sharp in Digital Engineering, the Razorleaf team recaps insights from ACE 2026—Aras Community Event (ACE) 2026—the annual gathering for users of Aras Innovator.Featured Hosts and Guests:Jonathan Scott – Co-host, Razorleaf Juliann Grant – Co-host, Razorleaf Milan Obradovic – Aras Pre-Sales Architect, Razorleaf Steven Binstock – Senior Solution Architect, Razorleaf From bold AI vision to the growing impact of Innovator Edge, the conversation explores how Aras is evolving beyond traditional PLM—focusing on user-centric experiences, flexible architectures, and empowering customers to build their own solutions.Whether you attended ACE or missed it, this episode delivers key takeaways, standout moments, and what it all means for the future of digital engineering. Key Takeaways:AI is the headline—but vision leads the story Rather than flashy product launches, ACE 2026 emphasized direction: how AI will be embedded into workflows, decision-making, and the broader digital thread. “Meet users where they are” is the new PLM mantra Aras is shifting toward task-based, accessible experiences that extend beyond traditional interfaces—bringing PLM to more users across the enterprise. InnovatorEdge is a major catalyst The platform enables lightweight, targeted apps and micro-experiences that connect users to PLM data without requiring full system access. The digital thread is becoming more actionable With AI and new architecture in place, organizations are closer than ever to truly connecting data across engineering, manufacturing, and service. Community remains a defining strength From open Q&A sessions to collaborative demos, ACE continues to stand out for its transparency and user-driven innovation. From AI-driven experiences to flexible app ecosystems, ACE 2026 made one thing clear: PLM is evolving—and Aras Corporation is building the foundation for what comes next.If You Found This Episode Valuable:Follow or subscribe to Stay Sharp on your favorite podcast platformLeave a review to help more listeners find the showShare this episode with a colleague or friendStay Sharp.Music is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

Is AI coming for PLM or saving it? This week on Stay Sharp in Digital Engineering, hosts Juliann Grant and Jonathan Scott are joined by special guest Ashish Kulkarni, Senior PLM Leader at Razorleaf International (Netherlands), for a dual-continent recap of CIMdata's Annual Market and Industry Conference — held simultaneously in Ann Arbor, Michigan, and Paris, France.Between them, the three cover the global PLM market data, the AI conversation dominating the industry, vendor vs. buyer disconnects, and what it all means if you work in digital engineering, PLM, or manufacturing technology.Key Takeaways:The global PLM market grew 8.7% to $87.3 billion — strong, but below the 9.3% forecastTop PLM investment priorities have shifted: knowledge management, global collaboration, and configurability are now leading over traditional part and BOM managementThe percentage of respondents saying PLM has "run its course" jumped from 22% in 2025 to 55% in 2026 — a striking shift in market sentimentAI is not replacing PLM — yet. But the question is now being asked openly, especially in EuropeArchitecture/Engineering/Construction (AEC) and Electronic Design Automation (EDA) were the surprise growth leaders, with AEC growth well above forecastCIMdata recategorized how it reports the market: moving from CPDM to "Product Innovation Platforms," with new scrutiny on how tools vs. platforms are classifiedSI/VAR growth significantly missed forecast (7.5% vs. 12.6% predicted) — reasons remain unclearA "fluency-deployment divide" is emerging end users are experimenting with AI tools like ChatGPT, but in-house enterprise AI deployments in PLM are still very earlyVendors are racing to embed AI capabilities; buyers are moving slower and prioritizing data readiness firstFear factors around AI — "your data has to be perfect before you can use it" — are being actively addressed by presenters like Diego TamburiniAbout Our GuestAshish Kulkarni is a Senior PLM Leader at Razorleaf International, based in the Netherlands. With over 23 years of experience driving enterprise-scale digital transformation across Europe and 15+ years in PLM (including ENOVIA), Ashish has led strategic growth across Europe and the Mediterranean region. He was instrumental in building and growing the Razorleaf India office.Resources & ReferencesCIMdata Annual PLM Market and Industry Conference (Ann Arbor, MI and Paris, France)CIMdata PLM Market Report — official publication expected May 2025CIMdata PLM Roadmap and PDT Conference — May (North America) and Fall (Sweden) Diego Tamburini — previous Stay Sharp episodes on Strategic Patterns for Implementing AI in Manufacturing and The AI Reality Gap – What You Need to Know Before Building at Scale.Topics mentioned: Music is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

Build, Buy or Wait, Navigating the AI Implementation Stack Is your company ready to build its own AI solution? In this episode of Stay Sharp in Digital Engineering, hosts Juliann Grant and Jonathan Scott welcome back Dr. Diego Tamburini — executive consultant and AI practice lead at CIMdata — for a deep dive into what it actually takes to move from AI experimentation to production-ready deployment in manufacturing and engineering organizations.Diego brings 25+ years of experience across PLM, CAD/CAM, digital manufacturing, and AI strategy, with past roles at Microsoft, Autodesk, and Siemens Digital Industry Software. In this episode, he cuts through the noise to give you a practical, honest look at the AI build-vs-buy landscape.What You'll Learn:The difference between AI workflows and true agentic AI — and why conflating the two leads to bad decisionsThe full spectrum of AI implementation options: from fully embedded vendor tools to building from scratch in PythonWhen it makes sense to use low-code/no-code platforms (like Microsoft Copilot Studio or Amazon Bedrock) vs. full custom developmentWhy subject matter experts — not just developers — are becoming the key builders of AI agentsHow the digital thread concept is getting new life in the AI era and why it matters for cross-system reasoningThe "make, buy, or wait" framework for prioritizing AI initiatives wiselyThe traceability and privilege elevation challenges that regulated industries must address in agentic AIWhat skill sets organizations actually need at each level of AI implementationGuest: Dr. Diego Tamburini Executive Consultant, AI Practice Lead at CIMdata, Former Director of Engineering Agility at Microsoft, Former Design & Manufacturing Strategist at Autodesk Connect with Diego for AI strategy consulting through CIMdataRelated Episode - Give it a Listen!#125 : Strategic Patterns for Implementing AI in ManufacturingConnect & Subscribe Have a question, topic idea, or guest suggestion? Reach out anytime at [email protected].🎧 Subscribe on your favorite podcast platform so you never miss an episode — and if this was valuable, leave us a review or share it with a colleague navigating the AI landscape in their organization.Music is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

The man who helped name an industry sits down with Stay Sharp in Digital Engineering to trace the winding path from Product Data Management's humble origins to today's AI ambitions — and delivers a blunt warning: fix your data integration first, or AI will fail you.About This EpisodeBrion Carroll, CEO/Principal Consultant at Digital Solution Group, is not just a PLM practitioner — he's one of the people who built the very first PDM system and coined the category name. In this episode, Brion joins Juliann Grant and Jonathan Scott for a rare firsthand account of how product data management came to be, how it evolved into PLM, and why decades later, the industry is still wrestling with the same fundamental challenge: getting data to flow across systems.Whether you're deep in a PLM implementation or just starting to think about your AI strategy, this episode is a grounding, practical reality check you won't want to miss.Key TakeawaysPDM was born as a defensive move — Computer Vision built it to protect its CAD customer base from competitors, not to transform the industryThe first PDM system sold for $1 million per seat and handled only four functions: backup/recovery, revision control, access/security, and archive/restorePortability was a watershed moment — Brion famously declared from a conference stage that their product would run equivalently across three competing operating systems, and delivered on it in six monthsThe evolution from PDM to PLM wasn't a grand vision — it was vendors needing new features to sell, starting with workflow engines to manage product lifecycle stagesWeb technologies (Java, JavaScript, TCP/IP) democratized access and pushed the shift toward client-server and eventually true cloud architecturesToday's AI problem is yesterday's integration problem — AI applied inside a silo gives narrow insight; real business intelligence requires harmonized data flowing across all systems~4% of AI initiatives have yielded measurable value (per BCG research cited in the episode), and Brion argues dirty, siloed data is the reason whyWhat We DiscussBrion takes us back to the mid-1980s and Computer Vision's "Project David" — the small team tasked with building a data management system to protect the company's installed CAD base. From there, the conversation moves through the birth of the PDM category name, the wild competitive landscape of early vendors (Sherpa, Workgroup Technology, CDC), and the technical leap of making software portable across VMS, Unix, and IBM VM/CMS environments.We then trace the shift to PLM — why workflow management changed everything, how web technology opened the door to broader connectivity, and how the retail industry became an unlikely early adopter of enterprise PLM. The conversation closes with a clear-eyed look at today's AI landscape and why Brion believes companies that skip the hard work of data integration will find AI disappointing at best and damaging at worst.Guest ResourcesBrion Carroll— CEO & Principal Consultant, Digital Solution GroupWebsite:digitalsolutiongroup.netEnjoyed This Episode?Leave a review, drop a comment, or share this episode. Reach out anytime at [email protected].👉 Subscribe and never miss an episode — and don't forget to Stay SharpMusic is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

PLM Is Changing Fast: AI, Cloud & 3DEXPERIENCE Insights from ENOVIA 2026What’s really happening with PLM, AI, and cloud adoption right now?In this episode of Stay Sharp in Digital Engineering, hosts Juliann Grant and Jonathan Scott, with their Razorleaf colleagues, François Schlub and Andrew Halley, break down the biggest takeaways from the ENOVIA User Conference 2026, hosted by Dassault Systèmes in Boston.From AI-powered virtual twins to cloud migration strategies and digital thread integration, this conversation goes beyond the keynote hype to share what real users, engineers, and manufacturers are actually experiencing today.👉 If you're working in product development, engineering, manufacturing, or PLM—this is what you need to know.🔑 What You’ll LearnWhy cloud migration is now a “how,” not “if” decision How AI is shaping the future of PLM (and what’s still missing) Why integration—not tools—is the biggest challenge What companies like Ford Motor Company are doing to move faster The growing gap between PLM beginners and advanced users Why organizational change management is critical to success 🧠 Key Topics Covered3DEXPERIENCE platform strategy and roadmap AI scalability and compute requirements Digital thread and system integration (ERP, MES, more) Supply chain collaboration and cloud adoption Real-world user stories from global manufacturers If you found this helpful:👍 Like the video 💬 Share your perspective in the comments 🔔 Subscribe for more insights on digital engineering, PLM, and AI Music is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

What happens when you take the digital twin concept beyond products and factories, and apply it to your entire business?In this eye-opening episode, we sit down with John Biagioni, President of Lampin Corporation and a leader with experience ranging from machinist to a billion-dollar company executive. John joins hosts Juliann Grant and Jonathan Scott to explore how a business-level digital twin can drive smarter, more resilient decisions across finance, operations, and customer relationships.From using value stream mapping as a foundational building block to integrating real-time IoT sensing for continuous calibration, John shares the practical steps any company, big or small, can take to build models that deliver true competitive advantage.Key Takeaways: Why You Need a Business Digital TwinBeyond Survivability: The model is not just for business continuity; it's also a tool for understanding how your business can thrive by layering financial modeling (leverage, bull/bear cases) on top of operational inputs and outputs.The Power of Iteration: The difference between a static "virtual twin" and an active "digital twin" is continuous iteration and calibration with live data (like IoT sensing) to reflect real-world performance.Stakeholder Trust: The digital twin is a relationship tool, building trust with your employees, board, and customers by providing confident, data-backed answers to complex questions about capacity, lead times, and financial performance.Resilience Over Efficiency: In a post-pandemic supply chain world, the core value of a business digital twin is not just efficiency but the resilience it provides against unforeseen disruptions.Thank you for joining us on Stay Sharp in Digital Engineering! If you enjoyed this conversation, please take a moment to like, share, and subscribe to our podcast.Got a question for John or the hosts? Send us a note at [email protected] or leave a comment on our post!Music is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

What happens when a company does everything you can do to a private jet - except build one from scratch?Aaron Lane has spent 25+ years at Duncan Aviation, navigating a PLM journey that went from literal paper boxes loaded onto departing aircraft, through a legacy ERP stretched beyond its limits, to SmarTeam, and finally to Aras Innovator. In this episode, he pulls back the curtain on what that transformation actually looked like - the messy parts included.Whether you're greenfield, brownfield, or somewhere in between, this conversation is packed with hard-won, practical wisdom.Key TakeawaysWhy Duncan Aviation's "product" is actually a service - and why that changes everything about PLM requirementsHow to manage uncontrolled vendor technical data from thousands of OEM suppliers at scaleThe power and the peril of a DIY customization cultureWhy you must clarify governance before go-live - not afterHow Duncan is now using Aras to automate tribal knowledge and eliminate paperwork gapsGuestAaron Lane - PLM Lead, Duncan Aviation A 25+ year Duncan veteran who started as an assistant finish tech and has held roles spanning production planner, project manager, certification coordinator, and engineering team leader. Aaron has been the driving force behind Duncan's PLM evolution from SmarTeam to Aras Innovator.Resources & Links MentionedDuncan Aviation - duncanaviation.aeroAras Innovator - PLM platform used by Duncan AviationDuncan Aviation Case Study - Available at razorleaf.com (published separately)SmarTeam - Legacy PLM system (Dassault Systèmes, now end-of-life)CATIA - CAD platform used by Duncan's European OEM partnerCMMC - Cybersecurity Maturity Model Certification, relevant to Duncan's manufacturing divisionHave a question for Aaron or want to connect with Duncan Aviation? Reach out via the podcast community.👉 Send topic ideas or guest suggestions: [email protected]🔔 Subscribe so you never miss an episode ⭐ Leave a review - it helps more engineers find the show 💬 Drop a comment - the hosts actually read themStay Sharp in Digital Engineering is the podcast about tools, trends, and tactics shaping digital transformation in product manufacturing. New episodes drop regularly.Music is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

Inside Solumina: The Digital Backbone for Aerospace & Defense ManufacturingWhat does it take to manage manufacturing where failure simply isn’t an option?In this episode of Stay Sharp in Digital Engineering, hosts Juliann Grant and Jonathan Scott continue their digital product series with Sung Kim, CTO of iBase-t, for a deep dive into the Solumina platform—a manufacturing operations management system designed specifically for complex, highly regulated industries like aerospace and defense.Unlike traditional manufacturing systems that simply record what happened, Solumina is designed to actively guide production processes, enforce quality requirements, and maintain full traceability across the product lifecycle. Sung explains how the platform connects engineering intent to shop floor execution, integrating capabilities like MES, embedded quality management, supplier quality, MRO, and model-based manufacturing into a unified operational data model.The conversation explores the architecture behind the platform—from early two-tier systems to today’s cloud-native, microservices-based infrastructure—and how Solumina enables organizations to scale across global manufacturing sites while maintaining compliance, security, and operational continuity.If you’re curious about how modern manufacturing systems evolve from systems of record into systems that guide what happens next, this episode delivers a rare look under the hood.What You’ll Learn in This EpisodeWhy MES alone isn’t enough for complex aerospace and defense manufacturingHow Solumin integrates MES, quality management, MRO, and supplier quality into one platformWhy a unified operational data model is critical for AI in manufacturingHow manufacturers integrate Solumina with PLM, ERP, and shop floor systemsWhat model-based manufacturing looks like in real-world productionWhy cloud-native architecture and microservices matter for manufacturing softwareHow digital systems help preserve institutional knowledge as experienced workers retireKey Topics DiscussedManufacturing Operations Management (MOM) platformsAerospace and defense manufacturing systemsDigital thread and model based enterpriseEmbedded quality management systems (EQMS)Supplier quality integrationMaintenance, repair, and overhaul (MRO) workflowsAI-driven manufacturing operationsCloud-native industrial software architectureAbout the Guest:Sung Kim is the Chief Technology Officer at iBase-t, where he leads the company’s long-term technology vision and product architecture for the Lumina manufacturing operations platform. With more than 20 years of experience as a technology architect and computer scientist, Sung focuses on building scalable, secure systems for complex, highly regulated manufacturing environments.Before joining iBase-t, Sung worked in telecommunications and academia, teaching undergraduate and graduate students while publishing research in leading international journals and conferences, including ACM and IEEE. His work today centers on advancing modern, cloud-native manufacturing platforms that connect engineering, production, quality, and maintenance across the digital thread.📩 Subscribe for more conversations on digital engineering and product innovation💬 Share your experiences or questions in the commentsMusic is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

AI is everywhere right now—but in digital engineering and manufacturing, many leaders are still asking the same question: where does it actually help?In this episode of Stay Sharp in Digital Engineering, hosts Juliann Grant and Jonathan Scott sit down with Dr. Diego Tamburini of CIMdata to separate hype from implementation reality. With decades of experience spanning Microsoft, Autodesk, and Siemens Digital Industries, Diego shares how organizations are applying AI today—not in theory, but inside real engineering and manufacturing environments.The discussion introduces five practical patterns of AI adoption, explains why many proof-of-concepts fail to scale, and explores emerging applications like AI-assisted workflows, predictive models, and natural-language interaction with engineering systems. Most importantly, the conversation reframes AI not as a technology trend, but as a decision framework leaders must apply carefully to solve the right problems.Key TakeawaysWhy today’s AI surge is driven largely by generative AI exposure—not a sudden invention of new intelligenceThe five patterns companies are using to implement AI, from vendor-embedded tools to fully custom modelsHow Retrieval-Augmented Generation (RAG) allows organizations to connect AI across enterprise systems without retraining modelsWhy many AI pilots fail due to unclear use cases, poor measurement, or data that cannot scaleHow AI is changing the way engineers interact with software—moving from menus to natural-language workflowsReal industrial applications already delivering value, including predictive maintenance, quality analysis, and simulation accelerationThe importance of aligning AI adoption with skills, governance, and measurable KPIs from the start👤 Guest InformationDr. Diego TamburiniExecutive Consultant, CIMdataLeads the company’s AI practice, helping industrial organizations apply AI to digital engineering and manufacturing transformation.Former Director of Engineering Agility at Microsoft, where he helped integrate AI into engineering workflows and marketplace platforms.Previously held leadership and strategy roles at Autodesk and Siemens Digital Industries Software, with more than 25 years of experience in CAD, CAM, CAE, and PLM innovation. 👉 Connect with Dr. Tamburini to learn more about practical AI adoption in industrial environments.If this episode helped clarify how AI fits into engineering and manufacturing:Subscribe to Stay Sharp in Digital Engineering on your favorite podcast platformShare this episode with a colleague evaluating AI initiatives Leave a review to help more listeners find the showMusic is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

In this episode of Stay Sharp in Digital Engineering, we break down the biggest themes and takeaways from 3DEXPERIENCE World (formerly SolidWorks World), held this year in Houston.The message was loud and clear: AI is here — and Dassault Systèmes is betting big on it.From the headline-making partnership with NVIDIA to live AI demos inside the 3DEXPERIENCE platform, the event showcased ambitious plans for AI-driven engineering workflows. But beyond the stage announcements, what are customers actually asking about? And what does this shift mean for data strategy, PLM adoption, and long-term system decisions?Juliann Grant discusses the highlights of the event with the attending Razorleaf team, Jonathan Scott, Francois Schlub, and Andrew Halley as they share what really stood out — including conversations happening off-stage.Key Themes from the EventAI Everywhere — But What Does It Really Mean?AI agents embedded in SolidWorks workflowsLive demos showing rapid simulation and design iterationPartnership announcement between Dassault Systèmes and NVIDIAThe broader message: AI as a force multiplier, not just a chatbotData Is the FoundationWhy clean, structured product data matters more than everThe push toward centralizing data in the 3DEXPERIENCE platformIntegration challenges across ERP, PDM, and PLM systems“Garbage in, garbage out” — especially with AIAdoption Still Matters More Than HypeReal-world customer questions about migration and workflowsPDM Pro vs. Manage vs. 3DEXPERIENCE decisionsCloud adoption realitiesLegacy systems vs. startup-native cloud environmentsEducation & the Next GenerationExpanded focus on 3DEXPERIENCE EDUHigh school and university programs teaching platform tools earlyThe long-term shift in engineering workforce readinessThe Big Question: Is AI Replacing Engineers?A recurring theme throughout the conference:If AI compresses hours of work into minutes… what changes for engineering teams?We explore the tension between productivity gains and workforce impact — and what it may mean for the future of digital engineering.Guests in This EpisodeJuliann Grant – HostJonathan Scott – HostAndrew Halley – Senior Director of PartnershipsFrançois Schlub– Sales ExecutiveThe Event TakeawaysAI dominated the headlines.But customers are still focused on:Getting PLM foundations rightManaging migration pathsStructuring and governing product dataEnsuring successful user adoptionThe shift is real — but the groundwork still matters.If you couldn’t make it to Houston, this recap gives you the highlights, insights, and honest takeaways from the floor.👉 Have questions about 3DEXPERIENCE, AI strategy, or PLM adoption?Reach out to the team at Razorleaf.Music is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

Digital engineering gets a lot of attention. But what happens after the design is complete?In this episode of Stay Sharp in Digital Engineering, we sit down with Naveen Poonian, CEO of iBase-t, to explore why execution — not just engineering — is the real battleground of digital transformation in aerospace and defense.From Manufacturing Execution Systems (MES) and Manufacturing Operations Management (MOM) to Supplier Quality Management (SQM) and Maintenance, Repair & Overhaul (MRO), we unpack how digital tools connect engineering, production, service, and compliance into a true lifecycle ecosystem.We also explore: Why complex discrete manufacturing requires a different approachThe shift toward model-based enterpriseHow AI is being applied to real execution problemsWhat makes digital transformation succeed (and fail)The culture behind iBase-t’s family-owned legacyIf you're navigating digital manufacturing, aerospace innovation, or operational transformation, this conversation delivers practical insight grounded in real-world execution.Key TakeawaysExecution is the missing link between digital engineering and real-world manufacturing outcomes. Aerospace and defense demand precision, traceability, and compliance at every stage.MES and MOM platforms must connect deeply with supply chain and MRO processes.AI must solve real operational problems — not just exist as a feature.Digital transformation requires partnership, focus, and strong organizational alignment.The future is model-based, interoperable, and data-driven. Guest -Naveen PoonianCEO, iBase-tAerospace and defense technology leader focused on manufacturing execution, lifecycle transformation, and operational excellence.Resources & MentionsiBase-tiBase-t Excelerate ConferenceModel-Based Enterprise (MBE)Manufacturing Execution Systems (MES)Manufacturing Operations Management (MOM)Supplier Quality Management (SQM)Maintenance, Repair & Overhaul (MRO)Connect With Us📩 Have questions or topic ideas? Email: [email protected]💬 Leave a comment — we read them all⭐ Subscribe for future conversations on digital engineering and manufacturingIf you found value in this episode, please share it with a colleague in aerospace, defense, or advanced manufacturing.Music is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

AI may dominate headlines, but the real transformation in product development is happening elsewhere—in how teams manage complexity across mechanics, electronics, and software without slowing time to market.In this episode of Stay Sharp in Digital Engineering, hosts Juliann Grant and Jonathan Scott continue their conversation on Model-Based Systems Engineering (MBSE) with Eran Reinshmidt and Safae El Abkari of Dassault Systèmes. This discussion moves beyond aerospace and defense to explore how MBSE is reshaping consumer product development—from small appliances and power tools to connected products and manufacturing systems.The conversation dives into virtual prototyping, multidisciplinary collaboration, faster trade studies, platform thinking, product line engineering, and why MBSE is becoming essential for consumer companies that need speed without chaos.🔑 Key TakeawaysWhy consumer products now face the same complexity challenges as aerospace systemsHow MBSE enables parallel work across mechanical, electrical, and software teamsUsing virtual prototypes to test software months earlier than physical buildsHow parametric trade studies unlock better product decisions without slowing timelinesThe role of MBSE in product line engineering, modularity, and upgradeabilityWhy verification and validation must start earlier—and happen continuouslyHow MBSE principles are extending into manufacturing and factory variability👤 Guest Information Eran Reinshmidt Solution Leader, Consumer Industries – Dassault Systèmes Over 20 years of experience spanning furniture, home goods, appliances, sporting goods, apparel, and connected products.Safae El Abkari PhD, Engineering Sciences Leads the Perfectly Connected Product Solution at Dassault Systèmes, specializing in multidisciplinary product development and MBSE adoption.👉 Follow both guests on LinkedIn for insights on MBSE and consumer product innovation.If this episode helped clarify how MBSE applies beyond aerospace:Subscribe to Stay Sharp in Digital Engineering on your favorite podcast platformShare this episode with a colleague working in product development or manufacturingLeave a review to help more listeners find the showMusic is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

In this episode of Stay Sharp in Digital Engineering, hosts Juliann Grant and Jonathan Scott continue the digital product series with a deep dive into mechanical variation management and tolerance analysis. Joined by James Stoddard, co-founder and research fellow at Sigmetrix, the conversation explores how tolerance analysis acts as a critical bridge between ideal CAD models and real-world manufactured parts.The discussion unpacks why variation can never be eliminated, how poor tolerance decisions quietly drive cost and quality issues, and why managing variation across the entire product lifecycle is essential for modern, model-based enterprises.Key TakeawaysWhy tolerance analysis is more than a final design check-it's a lifecycle disciplineHow variation breaks the digital thread between design and manufacturingThe tradeoff between tighter tolerances, higher quality, and rising costWhy GD&T is a language—and how misunderstanding it drives manufacturing riskHow tolerance analysis supports better decisions in design, manufacturing, and inspectionThe role of tolerance analysis in the transition from virtual models to real-world productionGuest:James StoddardCo-Founder & Research Fellow, SigmetrixJames has spent over 25 years advancing tolerance analysis and mechanical variation management technologies, helping organizations improve quality while controlling cost.Resources Mentioned●      Mechanical Variation Management●      Tolerance Analysis●      Model-Based Definition (MBD)●      Geometric Dimensioning & Tolerancing (GD&T)●      Digital Thread & Model-Based Enterprise (MBE) If you found this episode valuable, subscribe to Stay Sharp in Digital Engineering, leave a review, and share this episode with a colleague working in design, manufacturing, or quality.Music is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

AI is everywhere right now—but in digital engineering and manufacturing, many leaders are still asking the same question: where does it actually help? In this episode of Stay Sharp in Digital Engineering, hosts Juliann Grant and Jonathan Scott sit down with Dr. Diego Tamburini of CIMdata to separate hype from implementation reality. With decades of experience spanning Microsoft, Autodesk, and Siemens Digital Industries, Diego shares how organizations are applying AI today—not in theory, but inside real engineering and manufacturing environments.The discussion introduces five practical patterns of AI adoption, explains why many proof-of-concepts fail to scale, and explores emerging applications like AI-assisted workflows, predictive models, and natural-language interaction with engineering systems. Most importantly, the conversation reframes AI not as a technology trend, but as a decision framework leaders must apply carefully to solve the right problems.Key TakeawaysWhy today’s AI surge is driven largely by generative AI exposure—not a sudden invention of new intelligenceThe five patterns companies are using to implement AI, from vendor-embedded tools to fully custom modelsHow Retrieval-Augmented Generation (RAG) allows organizations to connect AI across enterprise systems without retraining modelsWhy many AI pilots fail due to unclear use cases, poor measurement, or data that cannot scaleHow AI is changing the way engineers interact with software—moving from menus to natural-language workflowsReal industrial applications already delivering value, including predictive maintenance, quality analysis, and simulation accelerationThe importance of aligning AI adoption with skills, governance, and measurable KPIs from the start👤 Guest InformationDr. Diego TamburiniExecutive Consultant, CIMdataLeads the company’s AI practice, helping industrial organizations apply AI to digital engineering and manufacturing transformation.Former Director of Engineering Agility at Microsoft, where he helped integrate AI into engineering workflows and marketplace platforms.Previously held leadership and strategy roles at Autodesk and Siemens Digital Industries Software, with more than 25 years of experience in CAD, CAM, CAE, and PLM innovation. 👉 Connect with Dr. Tamburini to learn more about practical AI adoption in industrial environments.If this episode helped clarify how AI fits into engineering and manufacturing:Subscribe to Stay Sharp in Digital Engineering on your favorite podcast platformShare this episode with a colleague evaluating AI initiativesLeave a review to help more listeners find the showMusic is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

Episode SummaryHow risky is it to buy engineering software from a company owned by private equity? Does SaaS actually reduce risk—or introduce new problems? And what should technology buyers really be evaluating in today’s rapidly consolidating digital engineering market?In this episode of Stay Sharp, hosts Juliann Grant and Jonathan Scott sit down with industry analyst Monica Schnitger, President and Principal Analyst at Schnitger Corporation. With nearly two decades of experience advising software vendors, investors, and technology buyers, Monica offers a grounded, behind-the-scenes look at private equity, SaaS adoption, cloud realities, and how buyers can make smarter, lower-risk decisions.This conversation cuts through common myths and focuses on what actually matters when selecting engineering, PLM, CAD, and simulation software in 2026 and beyond.Key TakeawaysWhy private equity ownership is often less risky than buyers assumeWhat really determines software risk: usability, fit, vendor trust, and longevityHow SaaS and cloud delivery are reshaping buying expectations—and support gapsWhy reseller and channel consolidation is accelerating across the industryThe difference between AI hype and practical, usable innovationHow digital twins, UX improvements, and hybrid cloud models are quietly advancingPractical advice for evaluating software purchases without chasing shiny objectsAbout the GuestMonica Schnitger is President and Principal Analyst at Schnitger Corporation, where she advises engineering software vendors, investors, and enterprise buyers. She brings deep expertise across CAD, CAE, PLM, and digital engineering ecosystems, with a background in Naval Architecture and Marine Engineering from MIT and an MBA from Babson College.Resources Mentioned●      Engineering software risk evaluation●      SaaS and cloud adoption in digital engineering●      Private equity trends in software●      Digital twins and PLM evolution If you found this episode valuable:●      ✅ Follow or subscribe to Stay Sharp on your favorite podcast platform●      ⭐ Leave a review to help more listeners find the show●      📤 Share this episode with a colleague evaluating engineering softwareMusic is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

Model-Based Systems Engineering (MBSE) is often viewed as a heavyweight discipline reserved for aerospace, defense, or highly regulated industries. In this episode of Stay Sharp, hosts Juliann Grant and Jonathan Scott challenge that assumption.Joined by Eran Reinshmidt and Safae El Abkari from Dassault Systèmes, the conversation explores how MBSE principles apply directly to fast-moving consumer markets. From coffee machines and vacuum cleaners to furniture and connected appliances, the guests unpack why changing consumer trends, regulatory pressure, and competitive intensity demand a more connected, model-driven approach to product development.Through clear examples and memorable analogies, this episode shows how MBSE helps consumer product teams manage requirements, behavior, variants, and cross-disciplinary complexity without slowing innovation.Key TakeawaysMBSE is not about product size or industry. It is about rate of change and system complexityConsumer products face continuous requirement churn from sustainability, regulation, and competitionDocument-based requirements and behavior models break down as products become multidisciplinaryA shared system model improves traceability, alignment, and decision-making across teamsBehavioral modeling is critical for integrating mechanical, electronic, and software systemsProduct Line Engineering (PLE) enables scalable variant management without restarting from scratchGuestsEran ReinshmidtSolution Leader, Consumer Industries, Dassault SystèmesExpert in PLM and systems engineering for consumer products across home goods, appliances, lifestyle, and wearable industriesSafae El Abkari, PhDSolution Engineering Consultant, Dassault SystèmesSpecialist in connected products, multidisciplinary systems, and embedded systems engineeringResources MentionedModel-Based Systems Engineering (MBSE)Product Line Engineering (PLE)Connected and smart consumer productsDigital engineering for consumer industriesIf this episode challenged how you think about product development, subscribe to Stay Sharp on your favorite podcast platform.Leave a review or share this episode with a colleague navigating complex product systems.Have a topic you want us to cover next? Email [email protected] is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

In this episode of the Stay Sharp podcast, Juliann and Jonathan continue their digital product series with returning guest Oleg Shilovitsky, Co-Founder and CEO of OpenBOM. With over 25 years of experience in PLM and engineering software, Oleg unveils what truly sets OpenBOM apart—and why traditional PLM systems fail modern manufacturing organizations.From the shift from single-company databases to interconnected digital networks, to how product data must support real-time collaboration across engineering, procurement, and manufacturing, Oleg explains how OpenBOM tackles an industry-wide pain point: sharing the right data with the right people at the right time.He also introduces the concept of product memory—a foundational element for enabling AI and next-generation decision-making across engineering lifecycles.Key Discussion TopicsWhy traditional PLM systems were built for single-company control, not interconnected supply chainsThe “Google Sheets paradigm” and why customers value OpenBOM’s ease of adoptionHow OpenBOM enables secure data sharing across multiple companies without compromising independenceThe technology driving it: graph-based data models, polyglot persistence, and cloud-native microservicesSignals that a company is ready for OpenBOM: complex products, limited resources, and fast-paced innovation culturesUsing OpenBOM to bridge engineering and procurement (and eradicate Excel chaos)Introducing Product Memory—the data layer that enables AI-driven design and lifecycle intelligenceMemorable Quote“AI starts with the right data. If you can’t feed the AI with clean product memory, you’ll just get noisy answers. That’s why OpenBOM builds the data foundation first—everything else comes from that.”— Oleg ShilovitskyIf this episode helped clarify what modern PLM tools must deliver—and how product data can become a strategic advantage—make sure to:Follow the podcast so you don’t miss upcoming episodes in our digital product series. Leave a review sharing your biggest insight from today’s conversationSend us your topic ideas at [email protected]—We’d love to hear what you want us to dissect next.Stay tuned and stay sharp.Music is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

What will digital engineering and manufacturing really look like in 2026? In this forward-looking episode of Stay Sharp in Digital Engineering, hosts Juliann Grant and Jonathan Scott step back from day-to-day execution and examine the trends, technologies, and curveballs shaping the next phase of the industry. From AI-driven data enrichment and digital twins moving beyond PLM, to ERP vendors entering new territory, humanoid robotics, additive manufacturing at scale, and even quantum computing, this conversation blends grounded experience with thoughtful speculation. The result is a candid, wide-ranging discussion about what feels inevitable, what feels risky, and what may arrive faster than expected. Key Topics & Takeaways Why AI’s real value may be cleaning up decades of messy engineering data How ERP vendors could become unlikely leaders in digital twin platforms The growing importance of semantic data and context, not just volume Why multi-modal AI inputs (speech, sketches, visuals) could change engineering workflows The return of additive manufacturing headlines through mass customization How vertically integrated digital manufacturing companies could disrupt today’s ecosystems What humanoid and collaborative robots mean for factory integration The unresolved risks of AI autonomy, liability, and regulation Why quantum computing remains a wild card worth watching If you enjoyed this episode: Subscribe to Stay Sharp in Digital Engineering Leave a rating or review on your favorite podcast platform Share this episode with a colleague navigating digital transformation  Have a take on 2026 or want to join the conversation? 📩 Email: [email protected] Music is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

As 2025 comes to a close, Stay Sharp in Digital Engineering takes a look back at a year of standout conversations, memorable insights, and practical lessons from across the digital engineering landscape.In this special year-end episode, hosts Juliann Grant and Jonathan Scott revisit powerful soundbites from guests who helped shape the show’s most meaningful discussions. Spanning AI, digital thread and digital twin, model-based systems engineering (MBSE), PLM lessons learned, and emerging industry trends, this mashup captures the ideas that resonated most with listeners and continue to influence how organizations design, build, and manage products.This episode runs a bit longer than the usual format, but it’s packed with clarity, perspective, and a few laughs along the way.Episode 116 also marks a milestone moment for Stay Sharp in Digital Engineering, celebrating over 100 episodes and a growing, engaged listener community. Juliann and Jonathan extend heartfelt thanks to their guests, production team, and listeners for making 2025 such a meaningful year for the podcast.Have ideas for future topics or guests? The team would love to hear from you.📩 Send suggestions to: [email protected] 🌐 Visit the new podcast hub: staysharpindigitalengineering.com If you enjoyed this episode, please consider leaving a review or sharing it with a colleague, and as always, thanks for listening. Stay sharp. Music is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

Episode SummaryAI is everywhere, but in engineering and manufacturing, hype often outpaces reality. In this episode of Stay Sharp in Digital Engineering, we unpack what it actually means to be “AI-ready” and why most organizations are struggling to get there.Hosts Juliann Grant and Jonathan Scott are joined by Graham Law, PLM Solution Architect at Razorleaf, to explore the unglamorous but essential foundation of successful AI initiatives: clean, governed, connected engineering data. With over 16 years in PLM and a deep IT background, Graham offers a grounded perspective on what works, what fails, and where organizations should realistically start.This conversation cuts through buzzwords to focus on practical steps, real risks, and how PLM enables AI to deliver meaningful insight rather than confident misinformation.🔑 Key TakeawaysAI success in engineering is 80% data hygiene and 20% technologyMessy, duplicated, or poorly linked data leads to confidently wrong AI answersPLM provides the structure, context, and governance AI depends onOrganizations should start small, not attempt to “boil the ocean”AI can surface insights humans miss, but only if the data foundation is solidGovernance is just as important as cleanup—stop creating bad data going forward👤 GuestGraham LawPLM Solution Architect, Razorleaf16+ years in Product Lifecycle Management Experience with Windchill, Teamcenter, Aras, SOLIDWORKS PLM                                                                   Former IT Manager with deep systems expertise📣 Call to ActionIf this episode helped sharpen your thinking about AI and engineering data:●      Subscribe to Stay Sharp in Digital Engineering●      Leave a review on Apple Podcasts or Spotify●      Share this episode with a colleague working on AI or PLM initiativesMusic is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

In this episode, Juliann and Jonathan sit down with John Salyers and Korey Greene of Sea Box, a company transforming standard shipping containers into high-engineering, mission-ready solutions.This is a refreshingly honest look at a PLM journey filled with false starts, side-hustle implementation work, CAD file chaos, revision control challenges, and the realities of deploying PLM in a fast-moving engineering organization.John and Korey share how Sea Box went from a home-grown Microsoft Access database that crashed “every other day” to a modern PLM system tied directly to CAD, BOMs, and ERP. They walk through what they would do differently, what worked, and how the engineering + project-management partnership has been key to moving everything forward.If you’re on your own PLM or ERP journey, you’ll hear something familiar in their story—and you’ll walk away with practical lessons to avoid the same pitfalls.Key Takeaways• False starts happen—and they’re recoverable.Sea Box had to abandon their first PLM integrator and restart the project, losing time and budget in the process.• “Just stand it up” creates long-term debt.Rushing to replicate old systems (like their EPN database) created unnecessary customization and downstream headaches.• CAD chaos is a universal pain point.Without revision control and file governance, something as simple as quoting a replacement part becomes a scavenger hunt.• CAD Connector changed everything.Push/pull of CAD models, drawings, and revisions now ties engineering design directly to BOMs and ERP.• ERP forced better discipline.Migrating to Business Central required rigor around BOM structure, revision control, and part history.• Multi-perspective leadership matters.A PM + engineer co-admin partnership allowed them to weigh impact on both engineering workflows and business processes.• Community accelerates progress.Sea Box credits the Razorleaf community and user conference for solving problems they thought were unique.• Always use a dev environment.You will break things. You should. But do it safely.If you enjoyed this conversation, please follow the podcast, leave us a rating, or share your biggest takeaway in the comments.Have a topic you'd like us to explore next? Email us at [email protected] is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

In this episode of Stay Sharp in Digital Engineering, hosts Juliann Grant and Jonathan Scott sit down with globally recognized PLM pioneer Dr. Martin Eigner to unpack the evolving landscape of PLM, digital threads, configuration management, and cross-enterprise integration.Dr. Eigner brings decades of research, academic leadership, and industry experience to dissect topics many engineering leaders struggle with:  • What configuration items really are  • Why extended digital threads matter  • Why companies are starting to value integration more than best-of-breed functionality  • How PLM, ERP, MES and requirements tools must work together  • Why AI and graph databases could shape the next phase of engineering digitizationThis is a dense, high-value conversation for anyone looking to modernize engineering systems, understand digital transformation beyond buzzwords, or align organizational leadership around PLM strategy. Key Takeaways● Configuration items span far beyond CAD models; there are typically 200–300 essential objects across the product lifecycle—from requirements to manufacturing process plans.● A PLM system is only one piece of product lifecycle management; the full lifecycle includes concept, requirements, engineering, production, service, and recycling.● Many companies now see integration as more valuable than functional specialization.● The extended digital thread connects configuration items across systems, enabling true change impact analysis.● Legacy systems create siloed data; extended threads aim to mask these silos through better connectivity.● Graph databases may be essential to future PLM and digital-thread performance.● Organizational challenges—not technology—are the biggest roadblocks to transformation.● Change requires leadership ownership, better alignment between vertical and horizontal teams, and sometimes a rethink of organizational structure.Memorable Quote“There’s a trend that companies are evaluating integration higher than best-in-function—and that is new, but extremely important.” — Dr. Martin Eigner Music is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

Why Data Models Matter in Digital Engineering (Now More Than Ever)In this episode, Juliann Grant and Jonathan Scott dive deep into the growing conversation around data models in digital engineering. With increasing pressure to enable the digital thread, digital twins, and emerging AI capabilities, understanding how data is structured and why it varies across systems is more critical than ever.Together, they unpack:What a data model really is and why “model” is the key wordWhy every engineering and business system represents data differentlyThe mounting challenges created by siloed, mismatched data structuresHow digital twin initiatives have heightened the urgency for clean, connected dataReal-world examples showing why context, meaning, and structure matterThe risks and limitations of approaches like data lakesHow manufacturers can begin evaluating, modeling, and aligning their data for desired business outcomesWhy there will never be a universal data model — and why that’s okayBest practices for getting started, staying adaptable, and keeping data meaningful as technology evolvesThis episode is especially relevant for anyone interested in:Digital TransformationPLM / PDM ModernizationDigital Thread InitiativesDigital Twin StrategyAI Readiness in Engineering and ManufacturingNotable Quote:"If the AI doesn't understand the data, and it's just doing statistical prediction, the predictions can be junk. In a safety-critical situation, that's not cool." – Jonathan Scott Have questions or thoughts on this episode? Leave a comment or email [email protected]. Music is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

In this episode of Stay Sharp in Digital Engineering, hosts Jonathan Scott and Juliann Grant sit down with Oleg Shilovitsky, CEO and co-founder of OpenBOM, for a candid conversation about why so many engineering and manufacturing companies struggle with product data—and what they can do differently. Oleg breaks down the realities of managing product structure, BOMs, and cross-system data flow, and explains why connecting these elements early is essential for companies trying to scale.The team explores the cultural, technical, and process-driven challenges organizations face when they attempt to modernize their digital infrastructure—especially when legacy tools, disconnected databases, and informal workflows get in the way.Discussed In This EpisodeThe Product Data Gap:Why companies often underestimate the complexity of product information—and how this gap causes friction between engineering, manufacturing, supply chain, and procurement.Document-Centric vs. Data-Centric Thinking:Oleg explains why traditional document-driven approaches fall short and how a shift to connected, granular data changes everything. BOM Management Reality Check:Why spreadsheets still dominate BOM management, when they break down, and how to transition to structured, traceable product data.Connecting Systems, Not Just Software:The pitfalls of building tools in isolation and why establishing a shared “system of product truth” prevents downstream chaos.Cultural and Organizational Resistance:Why digital transformation isn’t just a tooling problem—it’s a mindset challenge across teams who have “always done it this way.”Scalability and Supply Chain Insight:How connected product data improves visibility, reduces surprises, and helps companies navigate supply chain complexity. Key Takeaways•   Product information isn’t just CAD files—it’s a living structure that must stay connected across the entire company.•   Moving from documents to data creates clarity, consistency, and the ability to scale.•   Spreadsheets may feel convenient, but they break under pressure as products grow more complex.•   A unified view of product structure strengthens communication between engineering, manufacturing, and supply chain.•   True digital transformation only sticks when the organization aligns culturally—not just technologically.Notable Quote“You can build the best software in the world, but if the data is disconnected, nothing works. The magic happens when all the pieces come together.” — Oleg Shilovitsky Listen & SubscribeStay up to date on all things digital engineering—from PLM and BOM management to digital thread strategy.Subscribe on Apple Podcasts, Spotify, or watch the conversation on YouTube. Music is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

In this episode of Stay Sharp in Digital Engineering, hosts Juliann Grant and Jonathan Scott sit down with Razorleaf’s Vice President of Business Development, Derek Neiding, to unpack how manufacturers can start smart when implementing complex digital engineering systems like PLM (Product Lifecycle Management) and MES (Manufacturing Execution Systems). The trio explores practical strategies for setting up successful projects—from process analysis and system selection to executive alignment and user adoption.In This EpisodeGetting Started Right: Why the “just start using the software” approach often backfires and how to balance speed with strategic vision.Building a Roadmap: The importance of aligning short-term goals with long-term growth so today’s choices don’t limit tomorrow’s innovation.Proof of Concept vs. Pilot vs. Quick Start: Derek breaks down what each approach actually means, when to use them, and how they fit together.Executive Buy-In and Business Cases: How to educate leadership, define success metrics, and prevent misalignment between tactical and strategic goals.Process Improvement and Adoption: Why optimizing processes first matters—and how education accelerates adoption rather than slowing it down.Consultants, Culture, and Customization: When to bring in outside expertise, how to balance it with internal knowledge, and how company culture shapes implementation success.Key TakeawaysSuccess isn’t about the software—it’s about alignment, education, and adaptability.A roadmap helps avoid costly restarts and ensures scalability as business needs evolve.Quick wins are important, but they must connect to a larger strategic vision.Every organization’s culture and maturity level should guide its implementation path.Adoption hinges on people understanding why changes are happening, not just what to click.Notable Quote“Education isn’t a delay—it’s an accelerator. At some point, you’ll need to know how these systems connect, so you can either learn it when everything’s on the floor or before you start.” — Derek NiedingListen & SubscribeStay up to date on all things digital engineering—from PLM and MES to digital thread strategy.Subscribe on Apple Podcasts, Spotify, or watch on YouTube.Music is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

In this episode of Stay Sharp in Digital Engineering, hosts Juliann Grant and Jonathan Scott continue their digital product series with Eric Schrader, Chief Product Officer at Propel Software. Together, they explore how Propel’s Product Value Management (PVM) platform expands beyond traditional PLM to unify teams, processes, and data across the entire product lifecycle—from concept to customer.Eric, a serial entrepreneur and product leader with experience at Agile Software, Coupa, and BetterWorks, shares how Propel’s SaaS solution helps high-tech, medtech, and consumer goods companies connect engineering, quality, and go-to-market teams around a single digital thread of product information.💡 Key Topics CoveredWhat is Product Value Management (PVM)? Eric explains how PVM connects every stage of a product’s journey—engineering, manufacturing, quality, marketing, and customer support—creating a unified “product thread.” Unlike traditional PLM, PVM bridges the gap between technical and commercial data, democratizing access to product information across departments.Technology Behind Propel Built on the Salesforce Platform, Propel leverages the scalability, data security, and AI capabilities of Salesforce while maintaining its independence as an OEM provider. Eric shares how the team uses Flow for low-code automation, Lightning Web Components for custom UIs, and Agentforce AI to deliver context-aware assistance—transforming PLM from a static database into a dynamic, guided experience.AI & the Future of Product Management Propel is pushing PLM into the AI era by using agent-based automation and large language model (LLM) integrations to extract value from unstructured data—like reading product documents and generating training quizzes or summarizing change requests in seconds.If you’re curious how modern PLM platforms are evolving into connected, intelligent ecosystems that empower both engineers and marketers, this episode offers a clear, practical look at how PVM redefines collaboration, compliance, and customer value.Music is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

In this episode of Stay Sharp in Digital Engineering, hosts Juliann Grant and Jonathan Scott continue the Digital Product Series with a deep dive into First Resonance, a company redefining how modern manufacturers operate.Our guest, Devin Patel, Head of Solutions at First Resonance, shares how their flagship platform ION—a modular, data-driven factory operating system—helps manufacturers move fast without losing control. From aerospace and defense to climate tech, robotics, and energy, First Resonance empowers teams to prototype quickly, scale complex hardware production, and stay agile in an ever-changing market.What You’ll Learn in This Episode:How First Resonance differs from traditional MES and ERP systemsWhy speed with control is the key to modern manufacturingThe kinds of companies best suited for ION (hint: advanced, complex hardware)Real-world examples, including how Epirus went from prototype to field-ready product in under a yearHow First Resonance’s culture, rooted in the “SpaceX Mafia” spirit, fuels rapid iteration and innovationWhere the company is heading with agentic AI, automation, and adaptive manufacturingDevin also shares insights into the company’s origins, customer-first approach, and how they’re working to give a 10-person startup the same visibility and control as an enterprise manufacturer—all while maintaining startup speed.If you’ve ever wondered how digital manufacturing is evolving beyond rigid, legacy systems, this conversation will open your eyes to what’s possible.👉 Subscribe to Stay Sharp in Digital Engineering on your favorite podcast platform or YouTube, and stay tuned for more episodes in the Digital Product Series.Music is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

In this episode, the team reconnects with Michael Finocchiaro to unpack his research into 300+ startups transforming the digital engineering landscape. From PLM and CAD to industrial AI and adaptive manufacturing, Michael reveals how new technologies, global innovation hubs, and AI-driven design tools are reshaping how products are developed, simulated, and produced.Listeners will gain a data-driven look at where agility, investment, and artificial intelligence are fueling the next wave of disruption in digital twin, simulation, MES, and smart manufacturing ecosystems.Key TakeawaysInnovation in digital engineering is no longer centralized. Emerging players from North America, Europe, and Asia are building faster, more agile systems that challenge industry giants.AI isn’t just a feature—it’s a foundation. From design automation to code refactoring and predictive analytics, startups are embedding intelligence across every phase of the product lifecycle.The economic model for engineering software is changing: token-based consumption, multi-agent systems, and new interoperability standards could disrupt traditional licensing structures.The future of PLM is modular, AI-assisted, and built by an ecosystem—not a single vendor.About the GuestMichael Finocchiaro is a Franco-American technology evangelist, consultant, and recognized voice in PLM, digital twin, and engineering software. With over 30 years of experience at HP, IBM, PTC, and Dassault Systèmes, he now advises startups, VCs, and enterprise clients on competitive strategy and digital transformation.Music is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

In this episode, the Razorleaf team continues the Digital Product Series by spotlighting Propel Software—a next-generation PLM company built on the Salesforce platform. Juliann and Jonathan sit down with Tom Shoemaker, VP of Product Marketing at Propel, to explore how the company is redefining product lifecycle management by unifying engineering, sales, marketing, and service.Tom shares how Propel bridges the gap between product development and commercialization, enabling manufacturers to bring products to market faster through connected data, collaboration, and AI.💡 Key Topics Discussed• The Propel Vision Propel helps manufacturers manage everything required to make, market, sell, and service products successfully—not just engineering data. By combining PLM, QMS, and PIM in one platform, Propel helps unify the product journey from concept to customer.• Built on Salesforce Propel was founded in 2015 to modernize PLM using the Salesforce platform. By leveraging Salesforce’s proven infrastructure, Propel focuses on business logic, collaboration, and innovation—allowing customers to scale faster with open, configurable systems.• Industry Focus & Use Cases Propel is designed for discrete manufacturers that rely on contract manufacturing and global supply chains, including:MedTech and medical device manufacturersHigh-tech and consumer electronicsIndustrial equipment and smart home technologiesConsumer products with configurable or long-life products• Success Story: Savant & GE Lighting Savant Industries, owner of the GE Lighting brand, adopted Propel to streamline product management and accelerate commercialization. Results include:📈 35% revenue growth in 2 years⚡ 74% faster product introduction cycles💼 50% reduction in order entry labor Notably, after acquiring a new company, Savant ingested all product data and commercialized it the same day using Propel’s unified Salesforce-powered system.• Product Value Management (PVM) Tom introduces the concept of Product Value Management (PVM)—a unified approach that combines PLM, QMS, and PIM to drive both cost reduction and revenue growth, while mitigating risk across the product lifecycle.• The Future: AI + Interoperability Propel’s next phase centers on AI-driven automation (Propel One) and multi-CAD interoperability.AI is embedded with guardrails for data trust and human oversight.New tools will simplify CAD-to-PLM integration across mechanical, electrical, and PDM systems—reducing complexity and cost for engineering teams.Learn more about Propel Software at propelsoftware.com.Got questions for Tom or thoughts on this episode? Leave a comment or email [email protected] is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

In this episode of Stay Sharp in Digital Engineering, hosts Juliann Grant and Jonathan Scott sit down with Devin Patel, Head of Solutions at First Resonance, to explore how manufacturing companies—startups and established players alike—can rethink the way they build and scale their operations.Devin shares insights on moving away from traditional monolithic systems like ERP and MES toward a more modular, data-driven approach that prioritizes flexibility, scalability, and real-world results. Together, they dive into:●      Why a strong data footprint matters more than rigid systems.●      How cloud computing, open APIs, and AI are enabling faster, more nimble manufacturing strategies.●      Real-world examples from aerospace, energy, and medical device companies that are embracing modular approaches.●      The unique challenges (and advantages) startups face compared to large, established manufacturers.●      The role of digital thread and digital twins in creating visibility, traceability, and agility across teams.  From building satellites and space thrusters to streamlining complex assembly, Devin explains how manufacturers can transform operations by solving one problem at a time—without years-long IT projects.If you’ve ever wondered how to build a future-proof digital backbone for manufacturing, this episode offers a blueprint for rethinking the status quo.🔗 Resources & Links●      Learn more about First Resonance●      Connect with Devin Patel on LinkedIn●      Subscribe to Stay Sharp in Digital Engineering for more conversations on digital transformation in manufacturing  Music is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

🔍 Episode OverviewIn this episode, the Razorleaf team unpacks insights from the Global Product Data Interoperability Summit (GPDIS) in Phoenix — one of the industry’s most collaborative events where aerospace and manufacturing leaders come together to solve shared challenges around data, digital engineering, and interoperability.From AI skepticism to digital thread strategy, Juliann, Jonathan, Tony, and François discuss what’s changing fast, what’s still a struggle, and why cooperation between competitors like Boeing, Airbus, and Lockheed Martin is key to advancing the industry.💡 Key Topics Discussed• Event Overview & Collaboration GPDIS brings together major OEMs, suppliers, and vendors from across aerospace, defense, and manufacturing to discuss digital transformation challenges. Despite being competitors, attendees openly shared lessons and standards to advance interoperability across systems and companies.• AI in Aerospace Artificial intelligence dominated conversations—but with healthy skepticism. Attendees debated AI’s limits, data accuracy, and the future role of AI in engineering workflows.• Digital Thread Maturity The “digital thread” remained the central theme. While most companies are still building point-to-point integrations, speakers emphasized the need for hub-and-spoke models and long-term data strategies to achieve true interoperability.• MBSE on the Factory Floor A strong focus on model-based systems engineering (MBSE) emerged, highlighting how manufacturing itself should be viewed as a system that benefits from model-based practices.• Emerging Standards: DDP, TDP & CASCADE Jonathan shared updates on evolving data standards like Digital Data Packages (DDP) and Technical Data Packages (TDP)—and how new frameworks such as CASCADE aim to improve how organizations link and share digital data.• Legacy Systems & Integration Challenges Many manufacturers are still running decade-old PLM and ERP systems, which complicates integration and modernization efforts. François noted that upgrading legacy systems is often the biggest barrier to achieving a seamless digital thread.• Governance & Co-Creation Tony and François emphasized that successful digital transformation requires joint ownership between engineering and IT—not siloed efforts. Strong governance and “co-creation” across teams are critical to managing PLM evolution and integration projects.🧭 Key TakeawaysCollaboration > Competition: True interoperability demands industry-wide cooperation and shared standards.AI Is Not a Silver Bullet: It’s a powerful tool, but human oversight remains essential—especially in safety-critical industries.Legacy Systems Hold Back Progress: Companies must modernize infrastructure before pursuing advanced digital thread initiatives.Governance Matters: Structured decision frameworks and cross-functional collaboration are essential for scaling PLM and MBSE efforts.Digital Thread Is a Journey: Most organizations are still early in building connected, intelligent ecosystems across engineering, manufacturing, and supply chains.🗣️ Memorable Quote“Everybody raise your hand—who wants to fly in a plane built entirely by AI?”🔗 Connect with RazorleafVisit Razorleaf.com for insights, solutions, and resources on PLM, digital thread, and systems integration.Music is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

In this episode of Stay Sharp in Digital Engineering, hosts Juliann Grant and Jonathan Scott welcome back Steve Nichols, head of Razorleaf Government Solutions, to explore how digital engineering is transforming government contracts and supply chains.From DOD digital engineering requirements to data rights and risk management, they unpack what contractors—especially small businesses—need to know to stay competitive. The conversation covers:How digital engineering requirements impact primes, subcontractors, and suppliers.Why awareness is as important as readiness when pursuing federal contracts.The role of digital twin, digital thread, and model-based systems engineering (MBSE) in government programs.Strategies for small business teaming and winning set-aside work.Navigating data rights, intellectual property protection, and information sharing.Factoring the cost of digital deliverables—from CAD models to lifecycle data—into bids.Building strong government–industry relationships through collaboration, industry days, and broad agency announcements (BAAs).Whether you’re a prime contractor, a subcontractor, or a supplier in the defense and aerospace sector, this episode offers practical insights into meeting digital engineering compliance and shaping better outcomes for government customers.🎧 Listen now and learn how to integrate digital engineering best practices into your government program strategy.Music is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

In this episode of Stay Sharp in Digital Engineering, hosts Juliann Grant and Jonathan Scott sit down with Mark Borcher from Razorleaf Government Solutions to tackle a rarely discussed but critical topic: retiring legacy business systems.Mark brings nearly two decades of experience in engineering, system integration, and enterprise transformation, and he shares what really goes into shutting down old PLM, ERP, CRM, and supply chain systems—and moving organizations onto modern platforms.From outdated DOS-based tools to massive migrations involving hundreds of systems, Mark explains the technical, organizational, and people-related obstacles that can derail a system retirement—and how to overcome them.What You’ll Learn in This Episode:When it’s time to retire a system — from end-of-life support to functionality gaps and security risks.How to plan a smooth transition — data archiving, cleaning up “junk” data, and mapping functionality to modern tools.The biggest roadblocks organizations face — user resistance, licensing challenges, security concerns, and integration hurdles.Why people are the hardest (and most important) part — strategies for training, managing change, and turning skeptics into champions.Mark’s best advice — focus on data cleanliness, open communication, and embracing change as an opportunity, not a burden.Whether you’re sunsetting a small PDM tool or migrating hundreds of interconnected legacy systems, this conversation will help you understand the hidden challenges—and how to get ahead of them.Music is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

In this episode of Stay Sharp in Digital Engineering, we sit down with Frank Patz-Brockmann, Chief Product & Technology Officer at CONTACT Software, to explore one of the most mature yet under-the-radar platforms in the PLM space.Frank shares how CONTACT Software—best known in Germany but lesser-known in North America—has evolved from its early days as "CIM Database" into the highly modular and extensible platform now known as CONTACT Elements.We cover:The origins and evolution of the CONTACT Elements platformWhat makes their modular “elements” approach unique—like a periodic table for PLM, MES, and IoTThe powerful integration between PLM, MES (Manufacturing Execution Systems), and IIoTUse cases where customers seamlessly connect engineering and shop floor dataWhy many global clients are choosing CONTACT’s cloud deployment options (SaaS, PaaS, and hybrid)How CONTACT's long-standing use of Python and open APIs empowers extensibilityThe rise of energy-aware manufacturing and AI-enabled analyticsKey takeaway: CONTACT Software might just be one of the most powerful, composable digital engineering platforms you’ve never heard of—until now.🔗 Learn more: contact-software.com📩 Questions or feedback? Email us at [email protected] or leave a comment wherever you listen.🎧 Don’t forget to subscribe, rate, and review—every click helps spread the word.Music is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

In this special 100th episode of Stay Sharp in Digital Engineering, the team celebrates with a twist—turning the show into a game of acronym bingo! Host Juliann welcomes back Jennifer Ferello, alongside Jonathan Scott and Eric Doubell, for a fast-paced contest to identify 100 acronyms from the world of digital engineering, PLM, and beyond.Expect laughter, a few stumpers, plenty of partial credit, and who will be ultimately crowned the “King/Queen of PLM.” The crew reflects on the fun (and occasional frustration) of decoding acronyms while celebrating the milestone with listeners who made it all possible.👑 Acronyms, banter, and bingo—what better way to mark 100 episodes?Music is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

In this episode of Stay Sharp in Digital Engineering, hosts Juliann Grant and Jonathan Scott sit down with AI expert Alex Bruskin to cut through the hype and explore the real impact of artificial intelligence on the world of digital engineering. From the history of AI and its convergence of compute power, algorithms, and data — to practical, high-value use cases in PLM, CAD, MBSE, and manufacturing — Alex explains where AI truly adds value, where human oversight is essential, and how organizations can prepare their data for successful adoption.Whether you’re curious about AI-driven data enrichment, smarter migration projects, or bridging the gap between engineering documentation and manufacturing, this conversation is packed with insights and actionable examples.What You’ll Learn in This Episode:Why AI’s current capabilities are less about “intelligence” and more about predictionHow the “language of engineering” can benefit from large language modelsWhy training data quality is critical — and how to keep a human in the loopReal-world AI use cases in digital engineering:Data enrichment for cleaner, more searchable part databasesAccelerating and improving PLM/CAD data migrationsAutomating PDF-to-digital conversions for technical publicationsThe difference between generative AI and specialized solvers — and how they work togetherLinks & Resources:Follow Alex Bruskin on LinkedInContact Razorleaf: [email protected] this episode on YouTubeSubscribe to Stay Sharp in Digital Engineering for more conversations on digital transformation, PLM, and manufacturing innovationEnjoyed this episode? Follow Razorleaf’s Stay Sharp in Digital Engineering, rate the show in your favorite podcast app, and share it with a colleague who’s exploring AI in engineering.Music is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

In this episode of Stay Sharp in Digital Engineering, we kick off our Digital Product Series with a deep dive into CONTACT Software—a company that has been shaping the digital engineering space for over 30 years but remains relatively unknown in North America.Our guest, Dimitri Baumtrok, Head of International Sales at CONTACT Software, joins Juliann Grant and Jonathan Scott to share the company’s story, its global expansion, and its unique definition of digital engineering.What You’ll Learn in This Episode:What is “Top Floor to Shop Floor”? How CONTACT Software connects innovation at the design stage with execution in manufacturing and beyond.Who They Serve: Why mid-sized and upper mid-sized companies are their sweet spot, and how industries from automotive to industrial machinery—and even fashion—benefit from their platform.The Secret’s Out: How a “best-kept secret” in Europe is expanding globally through partnerships, OEM collaborations, and customer-driven innovation.Company Culture & History: From its founding in the 1990s to today’s family-owned, privately held structure focused on “energizing great minds.”The Future of Digital Engineering: CONTACT’s vision for AI-driven product lifecycle management, mobile-first solutions, and international growth.Dimitri also shares how CONTACT works closely with customers to co-develop solutions, ensuring their platform evolves alongside real-world needs.If you’ve been curious about lesser-known players in the digital engineering space—or want to understand how CONTACT Elements stacks up against big-name PLM and MES providers—this is a must-listen.🎧 Tune in to discover why CONTACT Software might just be digital engineering’s best-kept secret.Music is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

In this forward-looking episode of Stay Sharp in Digital Engineering, hosts Juliann Grant and Jonathan Scott sit down with PLM authority Michael “Fino” Finocchiaro to unpack how AI, emerging startups, and evolving technologies are transforming the Product Lifecycle Management (PLM) landscape. From industry giants like Dassault Systèmes, Siemens, and PTC to disruptive newcomers, the conversation covers current innovations, potential disruptors, and bold predictions—touching on everything from digital threads and agentic AI to quantum computing’s role in engineering.What You’ll Learn in This Episode:How AI is reshaping PLM across major platforms like Dassault, Siemens, and PTCThe rise of agent-based AI orchestration and cross-platform integrationThe role of startups—like Propel, Duro, and Aras—in pushing PLM forwardWhy quantum computing and advanced manufacturing could redefine the industry’s capabilitiesEmerging technologies beyond AI that could impact the future of PLMInsights into evolving business models and economic considerations for PLM adoptionIf this episode was helpful, follow Razorleaf’s Stay Sharp in Digital Engineering, share it with your PLM team, and rate/review in your podcast app.Tell us what you’re testing next: agents, RAG search, or cloud PDM? Drop a comment and we may feature your question in a future episode.Want more like this? Subscribe and get new episodes the moment they drop.Music is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

In Part 2 of our conversation with MBSE expert David Long, we dive deeper into the evolution of model-based systems engineering, tracing its roots, tool development, and growing relevance across industries. You’ll hear how MBSE emerged as a way to improve communication between disciplines, especially between systems and software engineers, and why it's becoming an indispensable part of modern engineering practices.We explore:The historical context and drivers behind MBSEThe critical role of SysML v2 and why its release is a game-changerHow MBSE enables cross-domain collaboration and digital thread continuityKey software tools and vendors shaping the MBSE ecosystemThe convergence of PLM and MBSE in the age of digital transformationWhat MBSE has in common with the evolution from drafting to CADWhether you're a seasoned systems engineer or just learning about digital engineering, this episode offers an insightful look into the tools, standards, and thought leaders shaping the future.🛠️ MBSE Tools & Platforms:Cameo Systems Modeler by Dassault Systèmes (formerly MagicDraw)Enterprise Architect by Sparx SystemsCapella by ThalesGENESYS by VitechInnoslate by SPEC InnovationsMBSE tools from Ansys and MathWorks📚 Thought Leaders & Trainers:Sanford Friedenthal (SysML / MBSE thought leader)Ed Seidewitz (UML & SysML standards contributor)Lenny Delligatti – Author of SysML DistilledTim Weilkiens – MBSE Trainer and Consultant🧪 Standards Bodies:INCOSE (International Council on Systems Engineering)OMG (Object Management Group) – Developers of UML, SysML, UAF🔗 Learn More About SysML v2:SysML v2 Initiative at OMGSysML v2 Release Updates & Resources📩 Contact & Subscribe:Have questions for David or our hosts? Leave a comment or email us at [email protected].👉 Be sure to subscribe to Stay Sharp in Digital Engineering on your favorite podcast platform or watch full episodes on YouTube.🔗 YouTube: Razorleaf YouTube ChannelMusic is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

In this episode of Stay Sharp in Digital Engineering, hosts Juliann Grant and Jonathan Scott sit down with Fernando Valera, Chief Technology Officer at Visure Solutions, to tackle one of the most complex challenges in modern product development: aligning hardware and software lifecycles through integrated requirements engineering.With decades of experience in requirements management, Fernando offers deep insight into how PLM (Product Lifecycle Management), ALM (Application Lifecycle Management), and MBSE (Model-Based Systems Engineering) can come together to create smarter, faster, and safer product development cycles. The conversation also explores how AI is transforming requirements processes and what the future holds for digital engineering.🔍 Topics Covered:What PLM and ALM really mean—and where requirements engineering fits inThe cultural divide between hardware and software teams—and how to bridge itHow systems engineering and MBSE provide a common language across domainsThe role of digital twins in syncing product cadencesHow AI is already improving requirements validation, traceability, and complianceWhy system engineers are key players in modern product integrationWhat organizations must consider when blending ALM and PLM in real-world use🧠 Key Quotes:“AI can now do 80% of what a requirements engineer does—but it’s the boring 80%.” “Digital twins are speeding up hardware development the same way DevOps transformed software.” “MBSE isn’t just about models. It’s about giving people better ways to see and simulate complexity.”👤 Guest Bio:Fernando Valera is a Certified Professional in Requirements Engineering and CTO at Visure Solutions. With over 20 years of experience helping organizations streamline complex product delivery, Fernando brings a global perspective and deep technical expertise to digital transformation initiatives in safety-critical industries.📩 Got Questions? Drop us a comment on our LinkedIn post or email us at [email protected].✅ Don’t forget to like and subscribe on your favorite podcast platform or watch the full episode on YouTube.🎧 Stay sharp, and see you in the next episode!Music is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

In this episode of Stay Sharp in Digital Engineering, hosts Juliann Grant and Jonathan Scott welcome back Steve Nichols, head of the Public Sector and Defense Group at Razorleaf. Together, they unpack the foundational steps government agencies need to take to successfully implement digital engineering (DE) practices—whether you're in the Department of Defense, NASA, Homeland Security, or any other federal agency managing complex systems.Steve outlines six key components for digital engineering success:Integrated Tools and Data InteroperabilityCollaborative Digital EnvironmentsAuthoritative Sources of Truth (ASOTs)Digital Thread Planning and MaintenanceWorkforce Readiness and Culture ChangeGovernance and Policy AlignmentThe conversation dives into practical approaches for getting started, even if you're not at the beginning of an acquisition cycle. From digitizing artifacts and improving basic workflows to developing a “digital first” mindset, Steve explains why success starts with clear strategy, small wins, and a vision for long-term sustainability.💡 Key takeaways: – Don’t try to “boil the ocean”—start small and build momentum – Digital transformation requires cultural and organizational shifts, not just new tools – Programs should consider lifecycle interoperability and future workforce expectations from day one – External guidance and internal advocacy are both critical for success📍 Whether you’re supporting legacy programs or launching new initiatives, this episode offers a clear roadmap for navigating digital engineering in government.👉 Got questions or want to join the conversation? Drop us a comment or email us at [email protected]. 🔔 Don’t forget to subscribe and stay sharp!Music is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

In this episode of Stay Sharp in Digital Engineering, hosts Juliann Grant and Jonathan Scott are joined by David Ewing, Director of Mission Integration at SAIC and architect of the award-winning Ready One digital engineering platform. Together, they tackle the myths and misconceptions surrounding digital twins.They explore the difference between digital models and true digital twins, the importance of having a physical counterpart, and why configuration management is crucial for maintaining a digital thread. Dave emphasizes that a digital twin isn’t just a model—it’s a living representation that evolves alongside its physical asset, incorporating real-time data and changes over time.The conversation also covers:The nuances between terms like digital twin, digital shadow, surrogate, and virtual twinWhy CAD models alone don’t qualify as digital twinsHow deviations in manufacturing and maintenance create one-of-a-kind digital twin instancesWhy robust configuration management and a traceable digital thread are essentialReal-world applications in aerospace and defense, including mission-specific modeling and sensor feedbackThe growing role of AI in connecting systems, automating documentation, writing test cases, and refining models—and why human oversight is still essentialDavid also shares a few laughs with the hosts, poking fun at the overuse of buzzwords and “digital trophies,” and stressing the importance of context, scalability, and ethics in digital engineering.Listeners will walk away with a clearer understanding of what a digital twin is (and isn’t), where AI fits in, and how to start building toward a truly connected, model-based future.If you enjoyed this conversation, be sure to like this episode and subscribe to Stay Sharp on your favorite podcast platform or on YouTube. Got questions or feedback for the hosts? Drop a comment or email us at [email protected] next time—stay sharp.Music is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

In this foundational episode, we kick off a two-part conversation with renowned MBSE thought leader David Long, former president of INCOSE and long-time advocate for model-based systems engineering. Hosts Juliann Grant and Jonathan Scott explore the role MBSE plays in enabling Digital Twins, especially in early lifecycle phases, and clarify how MBSE supports—not replaces—high-fidelity simulation and engineering tools.We cover:What MBSE is and isn’t (hint: it’s not its own silo)Where MBSE fits into the Digital Twin journeyHow MBSE supports architecture across the product, factory, and enterpriseThe importance of first-order (0D/1D) models in early systems thinkingMBSE’s relationship to simulation, sustainability, and organizational designWhy the middle management layer is the key to successful adoptionDavid also introduces the idea of MBSE acting as the “connective tissue” that unifies disciplines—not a high-fidelity replacement tool, but a crucial framework for clarity, collaboration, and continuous evolution.🧰 Resources & Links Mentioned:📘 MBSE & Digital Twin Concepts:MBSE Primer (co-authored by David Long)INCOSE – International Council on Systems EngineeringDigital Twin Types: Surrogate, Shadow, and Full TwinConway’s Law – How Organizational Structure Impacts System Design🧠 Simulation, Modeling & Architecture:Functional Mock-up Interface (FMI)Virtual Twin vs. Digital Twin (Dassault Systèmes)📩 Contact & Subscribe:🎧 Subscribe to Stay Sharp in Digital Engineering on your favorite podcast platform ▶️ Watch full episodes on Razorleaf’s YouTube Channel 📬 Got questions for David Long? Send us an email at [email protected] is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

How do simulations truly integrate into the world of digital twins—and what role do surrogate models and AI play in driving smarter design?In this episode, hosts Juliann Grant and Jonathan Scott continue the Digital Twin Series with a deep dive into simulation, featuring guest expert Shawn Freeman from Vias3D. With over 30 years of experience in CAE and simulation-driven product development, Shawn helps demystify how traditional CAE, surrogate modeling, and emerging technologies like AI are transforming how we design, manufacture, and operate products.🔍 Topics covered:Why traditional simulations alone aren’t enough for real-time digital twinsHow surrogate modeling helps speed up decision-makingThe four key components of simulation: inputs, outputs, model, and solverHow simulation results are stored, trusted, and integrated into PLM systemsOperational use cases, from vehicle design to in-flight aircraft assessmentsThe rising impact of AI in generating richer, faster simulation models🎧 Whether you're designing consumer products or managing aircraft performance, this episode gives you a comprehensive look at how simulation fits into the digital twin ecosystem.👉 Got questions or comments? Email us at [email protected] or comment on our latest post. Until next time—stay sharp.Music is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

In this episode, hosts Juliann Grant and Jonathan Scott are joined by Patrick Harrigan, VP of Partnerships at Caddi, to explore the transformative role of AI in unlocking the potential of unstructured data in manufacturing.While most conversations in digital engineering focus on structured data—PLM, ERP, and CAD—this episode dives deep into the massive (and often untapped) world of unstructured data: paper documents, legacy drawings, tribal knowledge, and more.💡 Topics Covered:What unstructured data actually means in a manufacturing contextWhy up to 80% of valuable data remains unused—and how AI is changing thatThe difference between systems of record and systems of insightHow AI is accelerating the conversion of historical documents and tribal knowledge into searchable, useful intelligenceReal-world applications for AI-powered insights—from reducing engineering inefficiencies to improving quality controlWhat makes manufacturing data uniquely challenging for general AI tools—and how purpose-built platforms are adaptingThe future of connected insights across structured and unstructured data domainsWhy “agentic AI” and human-in-the-loop workflows matter now more than ever🔧 Key Insight:AI isn’t just a buzzword—it’s a powerful tool for surfacing decades of buried knowledge and connecting data silos across the digital thread. Whether it’s improving design reuse, surfacing legacy quality fixes, or simply saving engineers from being “librarians,” the potential is vast.🎧 Listen now on your favorite podcast platform or watch on YouTube. 📩 Questions or feedback? Email us at [email protected] Sharp—and stay curious.Music is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

In this special 25th anniversary episode, we’re taking a trip down memory lane with Razorleaf’s CEO and co-founder, Eric Doubell. Hosts Juliann Grant and Jonathan Scott sit down with Eric to reflect on the pivotal moments, lessons learned, and guiding values that shaped Razorleaf’s journey from a scrappy startup to a global digital engineering leader.💡 In this episode, we cover:The founding story of Razorleaf — how an unexpected turn led to its creationBehind-the-scenes tales, including the surprising role 9/11 played in team formationLessons learned from growing a business with heart, integrity, and adaptabilityWhy being “people first” has driven Razorleaf’s culture and long-term succesThe evolution of the digital engineering landscape — and how Razorleaf has stayed aheadHow global growth has challenged and enriched the company’s perspectiveThe “hard things” Razorleaf chooses to take on — and why that matters for innovationWhat’s next for Razorleaf in an age of AI, cloud PLM, and multi-tenant systems🔥 Whether you’re an entrepreneur, PLM expert, digital engineering leader, or longtime Razorleaf partner, this episode offers insight into building a resilient, values-driven company in a rapidly changing tech world.📩 Have a question for Eric or the team? Email us at: [email protected] 👍 Like this episode? Subscribe and leave a review on your favorite platform, and follow Razorleaf on social media.🔗 Learn more at razorleaf.comMusic is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

In this episode of Stay Sharp in Digital Engineering, we go beyond the product digital twin and dive into the transformative world of virtual twins for manufacturing processes. Juliann and Jonathan are joined by Kevin Sullivan of Dassault Systèmes to explore how leading manufacturers are using process twins to simulate, optimize, and future-proof their factory operations.You’ll learn:  ✅ The difference between digital twins and virtual twins  ✅ How process twins drive efficiency, lean manufacturing, and pull-based production  ✅ Real-world use cases from bottling lines to automotive to greenfield factory builds  ✅ Why simulation matters more than ever in high-speed, high-volume production  ✅ How virtual twins support sustainability, supply chain resilience, and even human ergonomicsWhether you’re designing a new facility or trying to modernize an existing one, this episode will give you practical insights on how to use virtual twins to cut costs, reduce risk, and increase adaptability.Topics Discussed:What sets a “virtual twin” apart from a standard digital twinExamples of product vs. process value in different industriesPlanning new factory builds with simulation-first strategiesCreating human and robot twins for safety and efficiencyIntegrating sustainability into manufacturing process designA roadmap for getting started and scaling virtual twin technologyResources  Contact: Have questions or want to connect with our guest? Drop us a line at 📧 [email protected]📌 Don’t forget to like, subscribe, and leave a review on your favorite podcast platform!Music is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.

In this episode of Stay Sharp in Digital Engineering, hosts Juliann Grant and Jonathan Scott welcome back Dr. Patrick Hillberg for his fourth appearance on the show. A professor and thought leader in PLM, systems thinking, and digital transformation, Dr. Hillberg joins the conversation to explore powerful and practical use cases for digital twins across industries.From Hollywood film sets and football fields to harbor cranes, commercial airliners, and collapsed buildings, this episode dives into how digital twins—and more importantly, digital threads—are being used to simulate, diagnose, and even prevent catastrophic events.🔍 Highlights from the Episode:How Apollo 13's analog twin scene inspired a new way to understand digital twin valueReal-world failure analysis: a Texas harbor crane collapse and the missed opportunity for a front-running simulationThe tragic 737 door plug and MAX incidents—and what could have been prevented with a robust digital threadDigital twins in consumer tech: how your car app may already be a sparse but effective digital twinWhy insurance companies might lead the charge in demanding front-running simulations for risk mitigationA strong case for designing your digital thread before you build your productDr. Hillberg also walks us through the six foundational pillars of product lifecycle management, originally laid out by Michael Grieves, and reframes them as essential elements of a functioning digital twin ecosystem.Whether you're an engineer, innovator, or executive, this episode challenges you to rethink how you capture, use, and respond to real-time data—and how digital twins can be your most valuable asset in designing for safety, efficiency, and accountability.🎧 Tune in to hear:The critical difference between a digital twin and a digital threadWhy sparse twins can still deliver massive valueHow front-running simulations could prevent billion-dollar mistakes—and save lives👉 Got a question for Patrick? Want to suggest a future topic? Leave us a comment or send an email to [email protected] is considered “royalty-free” and discovered on Story Blocks.Technical Podcast Support by Jon Keur at Wayfare Recording Co.© 2024 Razorleaf Corp. All Rights Reserved.