BITS&CHIPS EVENT 2026

Parallel sessions

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  Carlos Lopes (Proekspert)

  AI solutions driving real results in industrial operations

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  Carlos Lopes (Proekspert)

  AI solutions driving real results in industrial operations

  AI is already producing measurable results inside industrial operations – in field service, safety-critical reporting and mission-critical support. This talk is a close look at systems Proekspert has actually built and put into production for industrial and OEM clients, and what the work taught us along the way.

  The anchor is one of the most tangible forces facing European industry today: an aging, retiring workforce and the decades of hands-on knowledge that leave with it. We’ll walk through a field-service copilot built to capture and pass on that expertise – what it does, how it fits into the systems teams already use and why keeping the technician in control mattered. Alongside it, two further deployments – from safety-critical and mission-critical environments – show the same engineering demands under harder constraints.

  The through-line is practical, not theoretical: what these systems needed to be trusted in daily operations – grounded in the client’s own data, built onto the stack already running, with a human on the outcome. Lessons from building the work, not a framework.

  Carlos Lopes leads AI-Powered Digital Services at Proekspert, a European software engineering company with 30+ years building mission-critical and embedded software for industrial and smart-device manufacturers. He works with industrial and OEM clients across Europe on taking AI from proof-of-concept into dependable production.

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  Sjoerd van der Zwaan (Solid Sands)

  The hidden foundation of safe AI: why execution-layer trust determines real-world safety

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  Sjoerd van der Zwaan (Solid Sands)

  The hidden foundation of safe AI: why execution-layer trust determines real-world safety

  Everyone is talking about AI safety. But what if the biggest safety risk isn’t the AI?
  As robotic systems leave controlled factory cells and enter the real world, every autonomous decision ultimately becomes executable C/C++ code running on embedded processors. This execution layer translates AI intent into physical action and determines how a robot behaves.
  Although generally less algorithmically complex than the AI stack above it, the execution layer is often the most safety-critical. Compiler and runtime library defects can introduce latent, systematic faults that are rarely exposed through application testing alone, making trust in the execution layer a matter of objective evidence rather than assumption. Safety can’t be built on assumptions; it must be built on evidence.
  This talk reveals why trustworthy toolchains are a foundation of safe AI, using real examples of compiler and library defects that silently alter system behavior. We show how software-defined products, OTA updates, open-source adoption and emerging regulations are driving the need for objective, continuous qualification evidence throughout the software lifecycle. Finally, we present an architecture that combines continuous toolchain qualification with a monitored safety envelope, enabling autonomous systems to evolve without compromising safety.
  The future of safe AI depends on trustworthy execution.

  Sjoerd van der Zwaan is chief product officer at Solid Sands, supporting the industry with compiler and library qualification for safety-critical systems. With more than thirty years of experience in robotics and autonomous systems, he focuses on building trust in the toolchains that underpin modern AI-enabled products. Previously, as CTO at 2Getthere, he led the development and deployment of autonomous transit systems. His expertise spans the full robotics stack, from perception and control to functional safety and toolchain qualification, helping bridge the gap between rapid AI innovation and evidence-based safety assurance.

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  Marie-José Klerks (Alten)

  The AI pressure cooker: missing ingredients and failed dishes

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  Marie-José Klerks (Alten)

  The AI pressure cooker: missing ingredients and failed dishes

  AI surely is hot, and many companies are racing against each other and themselves to implement AI for any and all tasks. Success stories around increased output, more lines of code written, optimized pipelines and faster deliveries are all around the corner. One would assume AI is reshaping the Software Development Lifecycle (SDLC), and without it, you’ll miss out on engineering excellence, improved quality and efficient and streamlined developer productivity. But does this assumption hold up in the actual world? In this talk, we’ll examine whether greater productivity automatically translates into better business outcomes and what the “missing ingredient” is in the current business landscape. Hint: AI amplifies existing engineering capabilities, but it can’t compensate for poor processes or organizational inefficiencies. Using actual examples from the field, we’ll discover why adopting AI alone isn’t a shortcut to engineering excellence, what bottlenecks can be encountered and ultimately need to be considered and how to deal with pitfalls and downsides. Yes, AI can really be that game-changer for many companies, but not automatically so. Organizations that blindly introduce AI into inefficient development processes expecting expert results risk accelerating existing bottlenecks, increasing technical debt and driving up costs without realizing meaningful benefits. But if AI is viewed as an accelerator of well-designed engineering practices, and not as a replacement for them, true leveraging and increasing of efficiency and output can be expected. Ultimately, the true strength of AI is less about the tools themselves and more about creating the operational foundation that enables AI to generate measurable business impact throughout the organization.

  Marie-José Klerks is information security officer, subject matter expert and practice manager at Alten. She works as a transformation leader and strategic coach for process optimization within organizations using Agile, DevOps and AI, with a big focus on cybersecurity and compliance.

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  Jochem Vlaardingerbroek (Ministry of Defense)

  The future of combat unmanned ground systems (CUGS)
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  Robert Howe (Ministry of Defense)

  Starting from scratch: building a CUGS innovation operational capability

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  Robert Howe (Ministry of Defense)

  Starting from scratch: building a CUGS innovation operational capability

  The CUGS program must deliver both a combat operational capability and the innovation lifecycle needed to sustain and evolve it. For the Royal Netherlands Army, this means mastering a new discipline: continuous engineering of a complex, integrated system. The ambition is bold – updating deployed systems within days, or even hours, through an agile engineering approach. The greatest hurdles aren’t technological, but organizational: changing structures, processes and mindsets to make continuous engineering a reality.

  Robert Howe is lead systems engineer, responsible for the CUGS program’s technical content, process, methods and tools. He’s previously founded two software engineering companies and provides systems engineering services to industrial and defense organizations.

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  Ben Pronk (TNO-ESI)

  CUGS: systems engineering in a rapidly changing domain

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  Ben Pronk (TNO-ESI)

  CUGS: systems engineering in a rapidly changing domain

  How do you engineer combat unmanned ground systems while autonomous technologies, operational concepts and military tactics are changing at speed? The CUGS program combines Incose-based systems engineering with MBSE to address key technical challenges and architectural trade-offs. At its heart is an adaptable architecture designed to remain relevant in a rapidly evolving operational and technological environment.

  Ben Pronk studied physics in Delft and Leiden and has over forty years of experience in systems engineering and architecting of high-tech systems. He’s been a systems architect in various domains, including the medical, lighting and semiconductor industries, and worked on diverse applications like MRI scanners, large-scale connected lighting systems, digital consumer ICs and robotics. He joined TNO-ESI in 2021 as a research fellow and has been involved in applied research projects in the fields of systems engineering and system performance with ESI partners since then. He currently works for the Ministry of Defense, establishing a sound systems architecture for the CUGS program.

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  Nick Atanasov & Tommy Tietjen (Forterra)

  More than mobility: the autonomous mission systems powering CUGS

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  Nick Atanasov & Tommy Tietjen (Forterra)

  More than mobility: the autonomous mission systems powering CUGS

  Mobility is what you can see. Mission success depends on everything that enables it. Forterra’s work within CUGS integrates RNLA mission autonomy software with autonomous navigation, sensing, compute and communications, four pillars that together turn a platform into something interoperable, scalable and capable of extending reach into contested environments no soldier should have to enter. This talk asks why autonomous navigation is the fundamental enabling technology beneath that architecture and how Forterra and CUGS are building toward it together as one integrated system rather than four separate capabilities.

   

  Nick Atanasov is VP of emerging technology and Tommy Tietjen is mission operations lead, both at Forterra.

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  Florian Loosen (Zeiss SMT)

  From systems architecture to service excellence – integrating service requirements early to maximize lifecycle value

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  Florian Loosen (Zeiss SMT)

  From systems architecture to service excellence – integrating service requirements early to maximize lifecycle value

  In complex high-tech systems, service excellence is often perceived as an operational challenge. In reality, it’s largely determined long before a product reaches the field. Critical capabilities such as maintainability, diagnostics, upgradeability, observability and availability are rooted in early systems architecture and design decisions.
  This talk explores how service requirements can be systematically integrated into product development from the very beginning. Drawing on practical examples from the semiconductor industry, it demonstrates how systems engineering can bridge the gap between product development and lifecycle support. Attendees will gain insights into architectural principles, design trade-offs and cross-functional collaboration approaches that enable superior service performance throughout the product lifecycle.
  The talk highlights why service shouldn’t be treated as an afterthought, but as a core design objective that creates long-term customer value, operational excellence and sustainable business success.

  Florian Loosen works at Zeiss Semiconductor Manufacturing Technology, where he focuses on high-NA EUV lithography systems and lifecycle-oriented engineering. His professional journey spans optics, applied physics and optical design, including a PhD at Friedrich-Alexander University (FAU) Erlangen-Nuremberg and the Max Planck Institute for the Science of Light (MPL). Since joining Zeiss, he’s worked across customer support, requirements engineering and system integration, including a long-term assignment at ASML in the Netherlands. Combining expertise in systems architecture, requirements engineering, project management and design thinking, he enjoys bringing together different disciplines and perspectives to solve complex challenges. Drawing on experiences from both development and operational environments, he’s passionate about turning diverse perspectives into practical solutions that create lasting impact across organizations and throughout the product lifecycle.

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  Robin Lawson (Robin Lawson Engineering)

  The boring spreadsheet invented by the military and why skipping it can cost millions

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  Robin Lawson (Robin Lawson Engineering)

  The boring spreadsheet invented by the military and why skipping it can cost millions

  Failure modes and effects analysis didn’t start out as a nice-to-have. It was formalized by the US military in 1949, adapted by NASA for the Apollo missions and later migrated into automotive and consumer product development. It remains one of the most rigorously proven risk mitigation tools in engineering, and yet, it’s chronically under-utilized.
  Drawing on 20 years of mechanical-design leadership in deep tech across aerospace, aviation and consumer hardware, this talk makes the case for treating FMEA as a living design tool owned by engineering, not a compliance checklist completed by quality. It also asks the harder engineering ethics question: Why do rigorous, well-understood risk processes erode under schedule and cost pressure, even when everyone involved knows better?
  The talk utilizes industry case studies and real incidents from the speaker’s career, including a moment where a “good enough” compromise quietly became the new lowered standard. It examines how small, individually defensible compromises accumulate into systemic failure.
  This is not a call for more paperwork. It’s a look at personal and organizational conditions that let good engineers make bad decisions, and how the FMEA process can objectively safeguard against them.
  Attendees will leave with a concrete framework for applying FMEA as an early, cross-functional design tool and a clearer, more honest picture of why risk processes succeed or quietly fail.

  Robin Lawson is a 4th-generation mechanical engineer with over twenty years of experience leading product development from concept through mass production, across aerospace (Boeing and Sikorsky programs), FAA-certified aviation electronics (Telex, a Bosch brand) and consumer sporting goods (Trek). She’s led NPI programs, DFMEA processes, DFM analyses and warranty root-cause investigations that led to substantial improvements. A 2015 TEDx Madison speaker, entrepreneur and former calculus instructor, she now runs an independent mechanical design consulting practice based in Eindhoven.

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  Xaviera Reynhout (Koers & Koffie)

  What do we need a product manager for? (Can’t AI do that …)

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  Xaviera Reynhout (Koers & Koffie)

  What do we need a product manager for? (Can’t AI do that …)

  I’ve been asked this to my face, more than once, walking into a new R&D team: “Yet another product manager. What do we need you for?” Usually, it’s the systems architect asking. Fair question, and AI has made it sharper.
  Here’s my answer. The architect and I do the same job from two sides. The architect is the technical conscience: What can we build, what holds together, what’s possible? The product manager is the business conscience: What’s worth building, what will the market pay for, what actually ships and sells? AI is brilliant at producing more: more concepts, more options, more half-finished work thrown over the fence. Deciding which of it is worth anything is the part AI can’t do. And that part only works when architect and product manager are aligned.
  Expect a provocative, lively session, with stories straight from R&D-driven companies, including the ones where I had to win this argument on the floor.

  Xaviera Reynhout is a product management leader with over twenty years of hands-on experience across Philips, Canon Production Printing and Legrand. Today, she’s interim product manager at EV charger manufacturer Peblar. She specializes in physical high-tech products and brings them to market. She works where R&D, marketing, sales and product meet and where the hard trade-offs get made. Based in Brainport Eindhoven, she takes on interim missions in R&D-driven companies, sharpening priorities and aligning teams. She founded Koers&Koffie. She’s walked into more than one room that wasn’t sure it needed a product manager. She makes the case anyway.

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  Laura Calvino (Philips)

  One platform, many procedures: the architectural trade-offs behind extensible intervention systems

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  Laura Calvino (Philips)

  One platform, many procedures: the architectural trade-offs behind extensible intervention systems

  Image-guided intervention systems must support diverse clinical procedures, customer segments and regional needs while remaining dependable through a long product lifecycle. This creates an architectural tension: Shared capabilities need stability, while procedure-specific applications and AI-enabled capabilities need to evolve at different speeds. This talk presents a platform approach for Azurion. A durable core provides the common clinical, system and safety foundations – apps that address procedure- and segment-specific workflows on a multi-year cadence. A rapidly evolving AI-enabled layer can extend those workflows through controlled integrations, without forcing changes in the core. Three architecture decisions frame the discussion: which capabilities belong in the stable platform, which should remain application-specific and when a repeated need justifies promotion into the core. Stable interfaces, compatibility rules and clear ownership let each layer evolve independently while preserving the overall system. The case offers lessons for any complex high-tech product family: A platform makes variability explicit and manageable, protecting the long-lived foundation while enabling focused innovation.

  Laura Calvino is a principal systems architect for X-ray Core at Philips Image Guided Therapy. She shapes the architecture and roadmap for the imaging chain in Azurion, Philips’ platform for image-guided, minimally invasive procedures. With fifteen years in imaging, she’s worked across power systems, computing platforms, operating systems, workspots, infrastructure and imaging architecture. Her work connects hardware, software, clinical workflow and product strategy. She helps multidisciplinary teams navigate trade-offs among customer value, safety, quality, cost, performance and speed. She holds a PDEng in applied physics from Eindhoven University of Technology and an MSc in electronic engineering.

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  Bedir Tekinerdogan (Wageningen University & Research)

  Software engineering for AI: architecting reliable AI-enabled high-tech systems

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  Bedir Tekinerdogan (Wageningen University & Research)

  Software engineering for AI: architecting reliable AI-enabled high-tech systems

  Artificial intelligence is increasingly being embedded into high-tech systems, ranging from autonomous machines and robotics to manufacturing equipment, medical devices and other software-intensive products. This opens up many new opportunities, but it also brings new engineering challenges. Unlike traditional software components, AI components learn from data, deal with uncertainty and their behavior may change as models, data and operating conditions evolve.
  This talk discusses what this means for the way we design and build reliable AI-enabled systems. The focus isn’t on AI as a standalone model, but on AI as part of a larger system that needs to be safe, robust, maintainable and useful in practice. The talk addresses topics such as requirements, architecture, validation, monitoring, human oversight and the collaboration needed between software engineers, data scientists, system architects and domain experts.
  The main message is that successful AI-enabled systems aren’t created by better models alone. They also require careful engineering decisions, clear system boundaries, continuous evaluation and a realistic understanding of where AI creates value and where it introduces risk. The talk offers practical insights for engineers, architects and technology leaders working on the next generation of intelligent high-tech systems.

  Bedir Tekinerdogan is a computer scientist with over 30 years of experience in software engineering, systems engineering and software-intensive high-tech systems. He’s a full professor and chair of the Information Technology Group at Wageningen University & Research and holds MSc and PhD degrees in computer science from the University of Twente. His work focuses on software and systems architecture, AI-enabled systems, cyber-physical systems, product line engineering and model-based systems engineering. He’s contributed to many industrial and research projects in domains such as automotive, defense, energy, precision agriculture and other high-tech sectors.

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  Neil Langmead (Codeclinic)

  Untangling the code: Can an AI agent become your architecture assistant?

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  Neil Langmead (Codeclinic)

  Untangling the code: Can an AI agent become your architecture assistant?

  Refactoring a large software system can feel like trying to untangle a knot without knowing which thread to pull. Architects must identify hidden dependencies, remove unwanted coupling, extract reusable functionality and reorganize components – often without reliable design documentation. The work is valuable, but painstaking and difficult to perform manually.
  This talk demonstrates how an AI agent can work directly with software architecture analysis tools to make that process faster and more systematic. Using dependency structure matrices and the Model Context Protocol, the agent can explore a codebase, detect architectural violations, identify tightly connected components and recommend practical refactoring steps. It can also evaluate architectural patterns – such as layered architecture – and suggest how existing modules could be rearranged to achieve them.
  The approach is demonstrated on IsoAgLib, a 50,000-line embedded software codebase, where the agent discovered layer violations and produced concrete proposals for improvement. Early experiments achieved a 17.8 percent reduction in coupling, outperforming conventional rule-based techniques.
  For software architects, this points towards a compelling future: AI that doesn’t merely generate code, but helps understand, simplify and reshape entire software systems.

  Refactoring a large software system can feel like trying to untangle a knot without knowing which thread to pull. Architects must identify hidden dependencies, remove unwanted coupling, extract reusable functionality and reorganize components – often without reliable design documentation. The work is valuable, but painstaking and difficult to perform manually.
  This talk demonstrates how an AI agent can work directly with software architecture analysis tools to make that process faster and more systematic. Using dependency structure matrices and the Model Context Protocol, the agent can explore a codebase, detect architectural violations, identify tightly connected components and recommend practical refactoring steps. It can also evaluate architectural patterns – such as layered architecture – and suggest how existing modules could be rearranged to achieve them.
  The approach is demonstrated on IsoAgLib, a 50,000-line embedded software codebase, where the agent discovered layer violations and produced concrete proposals for improvement. Early experiments achieved a 17.8 percent reduction in coupling, outperforming conventional rule-based techniques.
  For software architects, this points towards a compelling future: AI that doesn’t merely generate code, but helps understand, simplify and reshape entire software systems.

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  Robert van Uden (Alten)

  AI won’t save your legacy systems, architecture will

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  Robert van Uden (Alten)

  AI won’t save your legacy systems, architecture will

  AI can generate code faster than ever before. But when it comes to legacy systems, speed alone isn’t the solution. Without architectural direction, AI can make the problem worse by producing more code, more complexity and more technical debt at a higher pace. In this talk, Robert van Uden explores why architecture remains the deciding factor in successful AI-augmented software engineering. Drawing on his experience as a software architect in the high-tech industry, he shows how AI becomes truly valuable when combined with clear architectural boundaries, strong engineering practices and deliberate validation. He also argues that AI adoption isn’t primarily a tooling challenge, but a methodological one: Success depends on structure, responsibilities and maintainable ways of working. This talk is for anyone dealing with technical debt, modernization pressure and the promise of AI. It offers a practical perspective on how to use AI to modernize legacy systems responsibly and why, in the end, architecture is what makes the difference.

  Robert van Uden is a senior software architect at Alten and a software architecture trainer with more than twenty years of experience in the high-tech industry. He’s worked with leading companies in logistics, semiconductors and healthcare, helping them design, evolve and modernize complex software-intensive systems. Throughout his career, he’s worked extensively on legacy systems and software modernization. In recent years, he’s focused on the impact of AI on software engineering, especially in legacy environments where domain knowledge, maintainability and architectural control are critical. His work combines software architecture, legacy modernization and AI-augmented development methods that help teams adopt AI in a deliberate and effective way.